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Cám ơn anh Lan !
Hoan nghinh anh Hanh đã mở một chủ đề rất hay ...
Thuyền không rành mấy về lãnh vực này, tuy nhiên, hình như muốn có tài liệu về Automatic Control Systems & Feedback Systems, thì vô lấy trong IEEE website đó .
Vô website của IEEE, search với keywords đó, bạn sẽ có không dưới hàng ngàn articles và theories viết về nó . Tuy nhiên, bạn phải lựa lọc ra với ứng dụng đặc biệt vì các ứng dụng của lý thuyết này bao la lắm bạn à ... Anh Hạnh làm về ứng dụng gì của các lý thuyết này vậy ?
Đừng nói đâu xa trong ngành computer & electrical mà ngay trong Y khoa, nguoi ta cùng áp dụng vô .
Thí dụ, bài viết sau đây của một tay ứng dụng lý thuyết này dùng để ... đánh thuốc mê cho bệnh nhân của mình :
http://bja.oupjournals.org/cgi/content/full/85/6/818
----------------

Introduction:


Computers are increasingly used for delivering anaesthesia and monitoring patients. Automatic control systems will probably soon help to improve safety and reduce repetitive tasks.1?"4
Minimal and low-flow techniques of general anaesthesia are gaining popularity for different reasons. Cost and environmental issues5 6 favour low-flow systems.7 On the other hand, low-flow systems require more expertise, and because the changes in the fresh gas concentration have a delayed effect on the end-tidal concentration of inhalation agents, more adjustments of the vaporizer setting are needed. Automatic control of end-tidal anaesthetic concentration could facilitate low-flow anaesthesia and prove cost-effective.
The ideal variable for the control of anaesthesia is still a matter of debate. An indirect variable (e.g. mean arterial pressure, heart rate) is often chosen, and the EEG-derived bispectral index (BIS) has been used recently in a closed-loop feedback control system.8 Another easily measurable variable is the end-tidal concentration of an inhalation anaesthetic. It closely represents the brain concentration and can easily be measured breath-to-breath by a non-invasive procedure. In clinical practice, a certain level of anaesthesia is sought by observing the end-tidal concentration of the volatile agent by adjusting the inspired anaesthetic concentration manually. Previous studies have shown that, by controlling the end-tidal concentration of the anaesthetic, induction is shortened and arterial and brain concentrations are more stable.9 During the induction of anaesthesia, the inspired concentration is often set well above the desired brain tension to speed the induction process (the overpressure technique).10
We set a control system to adjust the end-tidal anaesthetic concentration for a variety of surgical interventions and patient characteristics, and compared it with manual control.
Methods


Patients
With institutional ethics committee approval and written, informed consent from the subjects, we studied 22 ASA I?"III patients (18?"75 yr) undergoing elective surgical procedures (neurosurgery, ENT, abdominal and orthopaedic surgery). We excluded patients with a history of coronary artery disease or with arterial hypertension that was poorly controlled.
The patients were given lorazepam 1?"2 mg orally 30 min before induction of anaesthesia. An i.v. cannula was placed in a peripheral vein, and we monitored 3-lead ECG, arterial pressure (either non-invasively or invasively, at the discretion of the anaesthetist), and pulse oximetry. Anaesthesia was performed by experienced anaesthetists with more than 2 yr of training.
The patients were assigned randomly (by lot) to one of two treatment groups for the first phase of anaesthesia. Group A patients were anaesthetized by manual adjustment of the concentration of isoflurane. Group B patients were anaesthetized with an automatic feedback control system to adjust the end-tidal isoflurane concentration.
The anaesthetist was asked to make four step changes of the target end-tidal isoflurane concentration, either manually or by setting the target value for the feedback controller, after the beginning of surgery. The anaesthetists were in a realistic clinical situation and had to make the changes as best they could while fulfilling other clinical tasks. Before the first step change and after each subsequent step, an equilibration period of approximately 10 min was allowed so that a constant end-tidal concentration could be maintained. The end-tidal target concentration was increased in two steps (+0.3 and +0.6 vol%) and decreased in two steps (?"0.3 and ?"0.6 vol%).
The sequence of the four step changes was chosen by the anaesthetist according to clinical needs and anticipated surgical stimulation, but the chosen step had to be sustained for a minimum time of 10 min. If the mean arterial blood pressure decreased by more than 20% after an increasing step-change, a single dose of ephedrine (5 mg i.v.) was allowed or an equivalent decreasing step-change of the end-tidal isoflurane concentration was sought. If the mean arterial pressure increased by more than 20% after a decreasing step change, ad***ional fentanyl (1?"2 µg kg?"1) was given.
After this first phase of four step changes, the method of adjusting the end-tidal isoflurane concentration was changed to the other method for a second phase, i.e. patients randomized to Group A (manual control) were now assigned to the automatic feedback control system for the next four step changes, and vice versa for Group B patients.
After a total of eight changes, the study finished and control continued with the second method. All the changes were made within the first 2 h of surgery. All changes were within a range of 0.3?"1.2 vol% of the end-tidal isoflurane concentration.
Anaesthesia was induced with fentanyl (2 µg kg?"1) and thiopental (3?"5 mg kg?"1). The trachea was intubated after muscle relaxation with vecuronium (0.1 mg kg?"1). Ad***ional doses of vecuronium were given to maintain 0?"2 responses of TOF stimulation at the ulnar nerve. After tracheal intubation, controlled ventilation was adjusted to maintain the end-tidal carbon dioxide at 4.5% (fixed respiratory rate of 10 per min, tidal volume variable), and anaesthesia was maintained with 70% N2O in oxygen, isoflurane and boluses of fentanyl (1?"2 µg kg?"1) as necessary.
After tracheal intubation, the fresh gas flow was set to 6 litre min?"1. Ten minutes later the flow was reduced to 1 litre min?"1 and at the end of the surgery it was reset to 6 litre min?"1 in both groups. The control system was started after the beginning of the operation. An equilibration period of 10 min was allowed for initialization of the controller before step changes of the end-tidal isoflurane concentration were undertaken. The sampling frequency for data collection was 10 per min, corresponding to a respiratory rate of 10 per min.
The control system
We used the Cicero workstation (Drägerwerke, Germany) with an isoflurane vaporizer (Dräger Vapour 19.3). It is able to monitor the following values: ECG, arterial pressure, pulse oximetry and sidestream measurements of oxygen, nitrous oxide, isoflurane and other inhalation agents. For safety reasons, isoflurane, nitrous oxide and oxygen concentrations were also measured with a sidestream anaesthetic gas analyser (Datex Capnomac; AVL, Switzerland). Both sampling lines were connected to a stop**** at the breathing filter (HME filter, nos 22 and 25; PALL, Switzerland) fitted to the endotracheal tube. All analysers were calibrated before use, according to the instructions of the manufacturers.
The end-tidal controller is a model-based state feedback controller (see Appendix A), uses two input signals (end-tidal and inspiratory isoflurane concentrations) and produces one output signal?"the isoflurane concentration in the fresh gas supply, i.e. the vaporizer setting. The Dräger 19.3 vaporizer is adjusted by an external servo-motor. The servo-motor itself is driven by an analogue amplifier controlled by a PID (Proportional Integral Derivative; for explanation see Appendix A), which in turn is controlled by a conventional electronic interface. The vaporizer and the PID control system are calibrated so that known concentrations are delivered in response to the input voltage. Two Hi-Tech (Bronkhorst Hi-Tech, Ruurlo, Netherlands) nitrous oxide and oxygen mass flow controllers are used *****pply a precise flow of gases. They are able to deliver gas flows between 0 and 10 litre min?"1 with ±1% accuracy. The anaesthetist can control the feedback system with a touchscreen panel. This panel has buttons for the selection of the end-tidal isoflurane concentration and the fresh gas flow. The Cicero vaporizer and flowmeters are bypassed when the feedback control system is operating. However, the anaesthetist can revert to manual control at any time.
The control algorithms are implemented on a VME-board power PC using the real-time programming language XOberon (Institute of Robotics, Swiss Federal Institute of Technology, Zurich, Switzerland). Dedicated parts of the program are used to send data for display and storage to a standard PC via an Ethernet link.
Data analysis
The control of the end-tidal isoflurane concentration was judged by comparing the step changes of the target end-tidal isoflurane concentration under the two modes of control (manual/automatic feedback), using the following performance criteria (Tables 2 and 3).
Table 2 Increasing step changes of FE. Values are mean (SD). The sampling frequency for data collection was 10 per min, corresponding to a respiratory rate of 10 per min. Response time=time to reach the target value, from 10 to 90% of the step height. Maximum overshoot=maximum amount the system overshot its target value, expressed as a percentage of the step height. Stability=deviation of the measured end-tidal isoflurane concentration from the target value, expressed as percentage frequency distributions of the deviation (measured minus desired) of the end-tidal isoflurane concentration. *P<0.05

Table 3 Decreasing step changes of FE. Values are mean (SD). The sampling frequency for data collection was 10 per min, corresponding to a respiratory rate of 10 per min. *P<0.05


1. Response time: time to reach the target value:
(a) increasing step change: time to reach the target value, from 10 to 90% of the step height (e.g. for an increasing step change of 0.6%, from 0.5 to 1.1%, the response time would be defined as the time to reach 1.04% from 0.56%);
(b) decreasing step change: time to reach the target value, from 10 to 90% of the step height (e.g. for a decreasing step change of 0.3%, from 0.8 to 0.5%, the response time would be defined as the time to reach 0.53 from 0.77%).
2. Maximal overshoot/undershoot: maximum amount the system overshoots or undershoots its target value, expressed as a percentage of the step height. Observation starts after the target value has been reached for the first time.
3. Stability: deviation of the measured end-tidal isoflurane concentration from the target value, expressed as percentage frequency distributions of the deviation (measured minus desired) of the end-tidal isoflurane concentration. Observation starts after the target value has been reached for the first time.
The number of changes of the vapour setting (0.05 vol%) was also recorded.
Numerical variables in the two groups were compared by the paired t-test when data were normally distributed, otherwise the Wilcoxon signed rank test was used. A P value <0.05 was considered statistically significant. The statistical package used was Sigma Stat, version 2.0 (Jandel Corporation, San Rafael, California, USA).
Results


The two groups were similar with respect to ***, age, weight and duration of surgery (Table 1).
Table 1 Patient characteristics and duration of surgery. Values are mean (SD)


In both groups, two patients had only one series of step changes because the operation finished early. The remaining 18 patients were studied after the protocol, i.e. they all had four step changes performed in the manual and in the automatic mode. Therefore, a total of 80 step changes were analysed in each group.
The performance of the feedback control was superior to that of the manual control in terms of overshoot and stability, with increasing as well as decreasing step changes (Tables 2 and 3 and Figs 1, 2, 3 and 4). The response time for the increasing step changes was shorter in the automatic mode for the larger steps only; for the smaller steps it was shorter in the manual mode. The response time for the decreasing step changes did not differ statistically between the two groups
...
................
(Thuyenxaxu cắt bỏ, xin vô đọc trong link trên nếu muốn biết thêm chi tiết ...)
...
.........
Structure of the model-based feedback controller. It consists of three components: an observer (with the state feedback K and the correction gain L), the integrator and the feedforward term F:
x''''(t) = Ax(t) + Bu(t)
y(t) = Cx(t) + Du(t)
where x(t) is the state vector, x''''(t) is the time derivative of x(t), u(t) is the control input and y(t) is the measurement output. In our case, x(t) represents the partial pressure in the different body compartments and the breathing system and u(t) represents the vaporizer position: y(t) is a vector composed of the measurements of inspired and expired isoflurane concentrations. The coefficients A, B, C and D are constant matrices. For details of the model, see Appendix B. Linear systems are idealizations since most real-world dynamic processes, and in particular physiological processes, are non-linear. However, most non-linear systems can be approximated by linear systems in a narrow working range. Even with larger working ranges it is often possible to achieve good controller performance with controller designs based on linearizations. The term ?~state feedback?T is used to describe a control algorithm in which the control signal is computed as a linear combination of various system states. Mathematically, the relationship between the controller output and the system states can be written as
u = ?"Kx(t)
where K is again a constant matrix. This generic model-based state feedback controller is augmented with a feedforward term (F) and an integrator ().17 18 The feedforward term accounts, for example, for the steady-state vaporizer position required to achieve a certain end-tidal target value. The integral term mainly compensates for modelling errors. Through these modifications, the state feedback control algorithm has some similarities to a classical PID controller. In such a controller, the control action has three components: (i) an action which is proportional (hence ?~P?T) to the error between the set point and the system output; (ii) an action proportional to the integral (hence ?~I?T) of this error; and (iii) an action that is proportional to the derivative (hence ?~D?T) of this error. In the case of the augmented state feedback controller, the feedforward term (F) plays an analogous role as the P part. The integral term acts identically in both types of controller. The state feedback acts like a derivative term. The important difference is that it does not introduce just first-order derivative action but rather derivatives up to an order equal to the number of states in the state vector x(t). This makes it possible to design considerably more aggressive controllers.
Because in most cases the states of the system (e.g. the partial pressure of isoflurane within an organ) cannot be measured, an ?~observer?T (parallel model of the system to be controlled) is used to compute an estimate of the states ((t)). This state estimate is then used in the control algorithm instead of the actual state. The state estimates usually differ from the true states because an observer cannot fully describe the reality and the initial con***ions are not known precisely. To achieve fast convergence of the state estimates towards the true states, a correction gain (L) is introduced. This gain leads to correction of the state estimates based on the difference between the measurements and the predictions of the parallel model. Note that in our case the measurements refer to the measurement vector y(t), which contains the inspired as well as the end-tidal isoflurane concentration measurement. Typically, L is a constant gain which must be chosen so that the rate of convergence of the state estimation is faster than the desired response of the controller. Using a non-linear-modified gain, however, artefacts can be rejected easily.
Được thuyenxaxu sửa chữa / chuyển vào 03:40 ngày 17/05/2005

Cám ơn anh Lan !
Hoan nghinh anh Hanh đã mở một chủ đề rất hay ...
Thuyền không rành mấy về lãnh vực này, tuy nhiên, hình như muốn có tài liệu về Automatic Control Systems & Feedback Systems, thì vô lấy trong IEEE website đó .
Vô website của IEEE, search với keywords đó, bạn sẽ có không dưới hàng ngàn articles và theories viết về nó . Tuy nhiên, bạn phải lựa lọc ra với ứng dụng đặc biệt vì các ứng dụng của lý thuyết này bao la lắm bạn à ... Anh Hạnh làm về ứng dụng gì của các lý thuyết này vậy ?
Đừng nói đâu xa trong ngành computer & electrical mà ngay trong Y khoa, nguoi ta cùng áp dụng vô .
Thí dụ, bài viết sau đây của một tay ứng dụng lý thuyết này dùng để ... đánh thuốc mê cho bệnh nhân của mình :
http://bja.oupjournals.org/cgi/content/full/85/6/818
----------------

Introduction:


Computers are increasingly used for delivering anaesthesia and monitoring patients. Automatic control systems will probably soon help to improve safety and reduce repetitive tasks.1?"4
Minimal and low-flow techniques of general anaesthesia are gaining popularity for different reasons. Cost and environmental issues5 6 favour low-flow systems.7 On the other hand, low-flow systems require more expertise, and because the changes in the fresh gas concentration have a delayed effect on the end-tidal concentration of inhalation agents, more adjustments of the vaporizer setting are needed. Automatic control of end-tidal anaesthetic concentration could facilitate low-flow anaesthesia and prove cost-effective.
The ideal variable for the control of anaesthesia is still a matter of debate. An indirect variable (e.g. mean arterial pressure, heart rate) is often chosen, and the EEG-derived bispectral index (BIS) has been used recently in a closed-loop feedback control system.8 Another easily measurable variable is the end-tidal concentration of an inhalation anaesthetic. It closely represents the brain concentration and can easily be measured breath-to-breath by a non-invasive procedure. In clinical practice, a certain level of anaesthesia is sought by observing the end-tidal concentration of the volatile agent by adjusting the inspired anaesthetic concentration manually. Previous studies have shown that, by controlling the end-tidal concentration of the anaesthetic, induction is shortened and arterial and brain concentrations are more stable.9 During the induction of anaesthesia, the inspired concentration is often set well above the desired brain tension to speed the induction process (the overpressure technique).10
We set a control system to adjust the end-tidal anaesthetic concentration for a variety of surgical interventions and patient characteristics, and compared it with manual control.
Methods


Patients
With institutional ethics committee approval and written, informed consent from the subjects, we studied 22 ASA I?"III patients (18?"75 yr) undergoing elective surgical procedures (neurosurgery, ENT, abdominal and orthopaedic surgery). We excluded patients with a history of coronary artery disease or with arterial hypertension that was poorly controlled.
The patients were given lorazepam 1?"2 mg orally 30 min before induction of anaesthesia. An i.v. cannula was placed in a peripheral vein, and we monitored 3-lead ECG, arterial pressure (either non-invasively or invasively, at the discretion of the anaesthetist), and pulse oximetry. Anaesthesia was performed by experienced anaesthetists with more than 2 yr of training.
The patients were assigned randomly (by lot) to one of two treatment groups for the first phase of anaesthesia. Group A patients were anaesthetized by manual adjustment of the concentration of isoflurane. Group B patients were anaesthetized with an automatic feedback control system to adjust the end-tidal isoflurane concentration.
The anaesthetist was asked to make four step changes of the target end-tidal isoflurane concentration, either manually or by setting the target value for the feedback controller, after the beginning of surgery. The anaesthetists were in a realistic clinical situation and had to make the changes as best they could while fulfilling other clinical tasks. Before the first step change and after each subsequent step, an equilibration period of approximately 10 min was allowed so that a constant end-tidal concentration could be maintained. The end-tidal target concentration was increased in two steps (+0.3 and +0.6 vol%) and decreased in two steps (?"0.3 and ?"0.6 vol%).
The sequence of the four step changes was chosen by the anaesthetist according to clinical needs and anticipated surgical stimulation, but the chosen step had to be sustained for a minimum time of 10 min. If the mean arterial blood pressure decreased by more than 20% after an increasing step-change, a single dose of ephedrine (5 mg i.v.) was allowed or an equivalent decreasing step-change of the end-tidal isoflurane concentration was sought. If the mean arterial pressure increased by more than 20% after a decreasing step change, ad***ional fentanyl (1?"2 µg kg?"1) was given.
After this first phase of four step changes, the method of adjusting the end-tidal isoflurane concentration was changed to the other method for a second phase, i.e. patients randomized to Group A (manual control) were now assigned to the automatic feedback control system for the next four step changes, and vice versa for Group B patients.
After a total of eight changes, the study finished and control continued with the second method. All the changes were made within the first 2 h of surgery. All changes were within a range of 0.3?"1.2 vol% of the end-tidal isoflurane concentration.
Anaesthesia was induced with fentanyl (2 µg kg?"1) and thiopental (3?"5 mg kg?"1). The trachea was intubated after muscle relaxation with vecuronium (0.1 mg kg?"1). Ad***ional doses of vecuronium were given to maintain 0?"2 responses of TOF stimulation at the ulnar nerve. After tracheal intubation, controlled ventilation was adjusted to maintain the end-tidal carbon dioxide at 4.5% (fixed respiratory rate of 10 per min, tidal volume variable), and anaesthesia was maintained with 70% N2O in oxygen, isoflurane and boluses of fentanyl (1?"2 µg kg?"1) as necessary.
After tracheal intubation, the fresh gas flow was set to 6 litre min?"1. Ten minutes later the flow was reduced to 1 litre min?"1 and at the end of the surgery it was reset to 6 litre min?"1 in both groups. The control system was started after the beginning of the operation. An equilibration period of 10 min was allowed for initialization of the controller before step changes of the end-tidal isoflurane concentration were undertaken. The sampling frequency for data collection was 10 per min, corresponding to a respiratory rate of 10 per min.
The control system
We used the Cicero workstation (Drägerwerke, Germany) with an isoflurane vaporizer (Dräger Vapour 19.3). It is able to monitor the following values: ECG, arterial pressure, pulse oximetry and sidestream measurements of oxygen, nitrous oxide, isoflurane and other inhalation agents. For safety reasons, isoflurane, nitrous oxide and oxygen concentrations were also measured with a sidestream anaesthetic gas analyser (Datex Capnomac; AVL, Switzerland). Both sampling lines were connected to a stop**** at the breathing filter (HME filter, nos 22 and 25; PALL, Switzerland) fitted to the endotracheal tube. All analysers were calibrated before use, according to the instructions of the manufacturers.
The end-tidal controller is a model-based state feedback controller (see Appendix A), uses two input signals (end-tidal and inspiratory isoflurane concentrations) and produces one output signal?"the isoflurane concentration in the fresh gas supply, i.e. the vaporizer setting. The Dräger 19.3 vaporizer is adjusted by an external servo-motor. The servo-motor itself is driven by an analogue amplifier controlled by a PID (Proportional Integral Derivative; for explanation see Appendix A), which in turn is controlled by a conventional electronic interface. The vaporizer and the PID control system are calibrated so that known concentrations are delivered in response to the input voltage. Two Hi-Tech (Bronkhorst Hi-Tech, Ruurlo, Netherlands) nitrous oxide and oxygen mass flow controllers are used *****pply a precise flow of gases. They are able to deliver gas flows between 0 and 10 litre min?"1 with ±1% accuracy. The anaesthetist can control the feedback system with a touchscreen panel. This panel has buttons for the selection of the end-tidal isoflurane concentration and the fresh gas flow. The Cicero vaporizer and flowmeters are bypassed when the feedback control system is operating. However, the anaesthetist can revert to manual control at any time.
The control algorithms are implemented on a VME-board power PC using the real-time programming language XOberon (Institute of Robotics, Swiss Federal Institute of Technology, Zurich, Switzerland). Dedicated parts of the program are used to send data for display and storage to a standard PC via an Ethernet link.
Data analysis
The control of the end-tidal isoflurane concentration was judged by comparing the step changes of the target end-tidal isoflurane concentration under the two modes of control (manual/automatic feedback), using the following performance criteria (Tables 2 and 3).
Table 2 Increasing step changes of FE. Values are mean (SD). The sampling frequency for data collection was 10 per min, corresponding to a respiratory rate of 10 per min. Response time=time to reach the target value, from 10 to 90% of the step height. Maximum overshoot=maximum amount the system overshot its target value, expressed as a percentage of the step height. Stability=deviation of the measured end-tidal isoflurane concentration from the target value, expressed as percentage frequency distributions of the deviation (measured minus desired) of the end-tidal isoflurane concentration. *P<0.05

Table 3 Decreasing step changes of FE. Values are mean (SD). The sampling frequency for data collection was 10 per min, corresponding to a respiratory rate of 10 per min. *P<0.05


1. Response time: time to reach the target value:
(a) increasing step change: time to reach the target value, from 10 to 90% of the step height (e.g. for an increasing step change of 0.6%, from 0.5 to 1.1%, the response time would be defined as the time to reach 1.04% from 0.56%);
(b) decreasing step change: time to reach the target value, from 10 to 90% of the step height (e.g. for a decreasing step change of 0.3%, from 0.8 to 0.5%, the response time would be defined as the time to reach 0.53 from 0.77%).
2. Maximal overshoot/undershoot: maximum amount the system overshoots or undershoots its target value, expressed as a percentage of the step height. Observation starts after the target value has been reached for the first time.
3. Stability: deviation of the measured end-tidal isoflurane concentration from the target value, expressed as percentage frequency distributions of the deviation (measured minus desired) of the end-tidal isoflurane concentration. Observation starts after the target value has been reached for the first time.
The number of changes of the vapour setting (0.05 vol%) was also recorded.
Numerical variables in the two groups were compared by the paired t-test when data were normally distributed, otherwise the Wilcoxon signed rank test was used. A P value <0.05 was considered statistically significant. The statistical package used was Sigma Stat, version 2.0 (Jandel Corporation, San Rafael, California, USA).
Results


The two groups were similar with respect to ***, age, weight and duration of surgery (Table 1).
Table 1 Patient characteristics and duration of surgery. Values are mean (SD)


In both groups, two patients had only one series of step changes because the operation finished early. The remaining 18 patients were studied after the protocol, i.e. they all had four step changes performed in the manual and in the automatic mode. Therefore, a total of 80 step changes were analysed in each group.
The performance of the feedback control was superior to that of the manual control in terms of overshoot and stability, with increasing as well as decreasing step changes (Tables 2 and 3 and Figs 1, 2, 3 and 4). The response time for the increasing step changes was shorter in the automatic mode for the larger steps only; for the smaller steps it was shorter in the manual mode. The response time for the decreasing step changes did not differ statistically between the two groups
...
................
(Thuyenxaxu cắt bỏ, xin vô đọc trong link trên nếu muốn biết thêm chi tiết ...)
...
.........
Structure of the model-based feedback controller. It consists of three components: an observer (with the state feedback K and the correction gain L), the integrator and the feedforward term F:
x''''(t) = Ax(t) + Bu(t)
y(t) = Cx(t) + Du(t)
where x(t) is the state vector, x''''(t) is the time derivative of x(t), u(t) is the control input and y(t) is the measurement output. In our case, x(t) represents the partial pressure in the different body compartments and the breathing system and u(t) represents the vaporizer position: y(t) is a vector composed of the measurements of inspired and expired isoflurane concentrations. The coefficients A, B, C and D are constant matrices. For details of the model, see Appendix B. Linear systems are idealizations since most real-world dynamic processes, and in particular physiological processes, are non-linear. However, most non-linear systems can be approximated by linear systems in a narrow working range. Even with larger working ranges it is often possible to achieve good controller performance with controller designs based on linearizations. The term ?~state feedback?T is used to describe a control algorithm in which the control signal is computed as a linear combination of various system states. Mathematically, the relationship between the controller output and the system states can be written as
u = ?"Kx(t)
where K is again a constant matrix. This generic model-based state feedback controller is augmented with a feedforward term (F) and an integrator ().17 18 The feedforward term accounts, for example, for the steady-state vaporizer position required to achieve a certain end-tidal target value. The integral term mainly compensates for modelling errors. Through these modifications, the state feedback control algorithm has some similarities to a classical PID controller. In such a controller, the control action has three components: (i) an action which is proportional (hence ?~P?T) to the error between the set point and the system output; (ii) an action proportional to the integral (hence ?~I?T) of this error; and (iii) an action that is proportional to the derivative (hence ?~D?T) of this error. In the case of the augmented state feedback controller, the feedforward term (F) plays an analogous role as the P part. The integral term acts identically in both types of controller. The state feedback acts like a derivative term. The important difference is that it does not introduce just first-order derivative action but rather derivatives up to an order equal to the number of states in the state vector x(t). This makes it possible to design considerably more aggressive controllers.
Because in most cases the states of the system (e.g. the partial pressure of isoflurane within an organ) cannot be measured, an ?~observer?T (parallel model of the system to be controlled) is used to compute an estimate of the states ((t)). This state estimate is then used in the control algorithm instead of the actual state. The state estimates usually differ from the true states because an observer cannot fully describe the reality and the initial con***ions are not known precisely. To achieve fast convergence of the state estimates towards the true states, a correction gain (L) is introduced. This gain leads to correction of the state estimates based on the difference between the measurements and the predictions of the parallel model. Note that in our case the measurements refer to the measurement vector y(t), which contains the inspired as well as the end-tidal isoflurane concentration measurement. Typically, L is a constant gain which must be chosen so that the rate of convergence of the state estimation is faster than the desired response of the controller. Using a non-linear-modified gain, however, artefacts can be rejected easily.
Được thuyenxaxu sửa chữa / chuyển vào 03:40 ngày 17/05/2005

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(Trich Hanh114212 Gửi lúc 20:54, 16/05/05)
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Nhưng nếu như bạn nói thì có lẽ chúng ta chưa theo đuổi kịp công nghệ tiên tiến trên thế giới là phải!!!
.................................................................................................
update được các tài liệu khác, có English thì càng tốt.
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Khía cạnh nào đó cơ bản là không lạc hậu, giới thiệu Hệ thống Định vị Toàn cầu (Global Positioning System - gọi tắt là GPS) vì vấn đề nầy hiện nay khá nóng và liên quan nhiều ngành, lãnh vực khác nhau; nhưng đã được McGraw Hill Book Company giới thiệu trong Electronics Engineers?T HandBook từ những năm 90 của thế kỹ 20 (Về sơ đồ chức năng hay nguyên lý):
Ví dụ1:
Trìch trang 28, Electronic Engineering Technology của Học viện Capitol Radio Engineering Institute - bản tiếng Việt của USOM, Hãng Television Associates of Indiana, USOM và Đại học Michigan khuyến cáo:

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Ví dụ2:
Trìch trang 1227, Electronics Engineers?T HandBook của McGraw Hill Book Company do Nhà xuất bản KHKT-VN dịch và phát hành 1996, giới thiệu nguyên lý làm việc của GPS:

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Ví dụ3:
Trìch trang 1236, Electronics Engineers?T HandBook của McGraw Hill Book Company do Nhà xuất bản KHKT-VN dịch và phát hành 1996, giới thiệu Tầm bao quát của vệ tinh GPS:

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- Liên hệ làm rỏ ví dụ2 và ví dụ3:

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- Liên hệ làm rỏ Artificial Neural Networks (khía cạnh nội suy, lọc, khử nhiễu):
Applications of Artificial Neural Networks (ANN): ANN is a multi-disciplinary field and as such its applications are numerous including:
- Finance
- Industry
- Agriculture
- Business
- Physics
- Statistics
- Cognitive science
- Neuroscience
- Weather forecasting
- Computer science and engineering
- Spatial analysis and geography

Unit 188 - Artificial Neural Networks for Spatial Data Analysis, NCGIA Core Curriculum in Geographic Information Science, Written by Sucharita Gopal Department of Geography and Centre for Remote Sensing Boston University, Boston MA 02215
URL: http://www.ncgia.ucsb.edu/giscc/units/u188/u188.html
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URL: http://www.levity.com/mavericks/glossary.htm
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THÂN!
Được lan0303 sửa chữa / chuyển vào 05:59 ngày 11/06/2006

Kính Gửi: Bác Hanh114212!
(Trich Hanh114212 Gửi lúc 20:54, 16/05/05)
===========================================
Nhưng nếu như bạn nói thì có lẽ chúng ta chưa theo đuổi kịp công nghệ tiên tiến trên thế giới là phải!!!
.................................................................................................
update được các tài liệu khác, có English thì càng tốt.
===========================================
Khía cạnh nào đó cơ bản là không lạc hậu, giới thiệu Hệ thống Định vị Toàn cầu (Global Positioning System - gọi tắt là GPS) vì vấn đề nầy hiện nay khá nóng và liên quan nhiều ngành, lãnh vực khác nhau; nhưng đã được McGraw Hill Book Company giới thiệu trong Electronics Engineers?T HandBook từ những năm 90 của thế kỹ 20 (Về sơ đồ chức năng hay nguyên lý):
Ví dụ1:
Trìch trang 28, Electronic Engineering Technology của Học viện Capitol Radio Engineering Institute - bản tiếng Việt của USOM, Hãng Television Associates of Indiana, USOM và Đại học Michigan khuyến cáo:

===========================================
Ví dụ2:
Trìch trang 1227, Electronics Engineers?T HandBook của McGraw Hill Book Company do Nhà xuất bản KHKT-VN dịch và phát hành 1996, giới thiệu nguyên lý làm việc của GPS:

===========================================
Ví dụ3:
Trìch trang 1236, Electronics Engineers?T HandBook của McGraw Hill Book Company do Nhà xuất bản KHKT-VN dịch và phát hành 1996, giới thiệu Tầm bao quát của vệ tinh GPS:

===========================================
- Liên hệ làm rỏ ví dụ2 và ví dụ3:

===========================================
- Liên hệ làm rỏ Artificial Neural Networks (khía cạnh nội suy, lọc, khử nhiễu):
Applications of Artificial Neural Networks (ANN): ANN is a multi-disciplinary field and as such its applications are numerous including:
- Finance
- Industry
- Agriculture
- Business
- Physics
- Statistics
- Cognitive science
- Neuroscience
- Weather forecasting
- Computer science and engineering
- Spatial analysis and geography

Unit 188 - Artificial Neural Networks for Spatial Data Analysis, NCGIA Core Curriculum in Geographic Information Science, Written by Sucharita Gopal Department of Geography and Centre for Remote Sensing Boston University, Boston MA 02215
URL: http://www.ncgia.ucsb.edu/giscc/units/u188/u188.html
===========================================
URL: http://www.levity.com/mavericks/glossary.htm
===========================================
THÂN!
Được lan0303 sửa chữa / chuyển vào 10:37 ngày 17/05/2005

(tiep tuc)
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Intelligent Process control
URL: http://www.segherskeppel.com/sk/home.nsf/_/9A5D45DF46D2CCFBC1256CBC002B05B7
Intelligent Process control nầy là của Lai Sun Hong Kong, Intelligent Process control của Việt Nam mình đã sữa xong
rồi nhưng đang chờ đưa vào hoạt động.
For dedicated control and monitoring of our biological treatment installations we have developed the
BIOscan-BIOmaster® system. It enables the client to control the installation on actual waste water and effluent quality
as well as on actual process parameters.
BIOSCAN®
The BIOSCAN® is the automatic monitoring instrument for waste water treatment plants. The BIOSCAN® combines
on-line multistream sampling and monitoring. This way a better control of the biological process can be achieved.
Bioscan.jpg
Principle
The sampling and monitoring system is constructed as a compact unit that is placed in the center of the wastewater
treatment plant.
The unit is connected with all essential activated sludge compartments and the waste water by a network of piping.
A sampling pump takes all sludge and influent samples to the central unit where all measurements take place. The
central unit consists of two compartments ; one for inline measuring of pH, DO, temperature and other relevant
parameters if wanted. The other for semi continuous measuring of biological activity and biological degradability using
respirometry.
Advantages
The operator receives realtime data of the biological process and the influent quality. All necessary reactors and
streams are monitored with one set of monitoring devices. As a result the BIOSCAN® represents a highly favourable
ratio of price / available monitoring data
BIOSCAN - BIOMASTER®
Intensive applied research and 20 years of experience in design, construction and operation of waste water treatment
plants have resulted in the development of the BIOSCAN-BIOMASTER®
BIOSCAN-BIOMASTER® is the automatic monitoring and control instrument for biological waste water treatment
plants.
It combines on-line multistream sampling, monitoring and data-interpretation. It provides an excellent automated
support for the control of the biological process.
Principle
The sampling and monitoring system is constructed in a compact unit that is placed in the center of the wastewater
treatment plant.
The unit is connected with all essential activated sludge compartments and the pretreated waste water by a network of
piping.
bioscan_schema.gif
A sampling pump takes all sludge and influent samples to the central unit where all measurements take place. The
central unit consists of two compartments ; one for inline measuring if pH, DO, temperature and other relevant
parameters if wanted. The other for semi continuous measuring of biological activity and biological degradability using
respirometry.
This sampling and monitoring device is connected to an automatic pilot unit. The automatic pilot is able to interpret
biological processes and process parameters of the WWTP in ad***ion to the technical state of the WWTP, being
monitored and controlled by the standard PC-PLC control and visualisation.
Advantages
With the BIOSCAN-BIOMASTER® a large number of places and samples are monitored with one set of monitoring
devices and as a result a highly favourable ratio of price / available monitoring data is obtained.
The control of the central unit, the advanced data interpretation and interface with the WWTP-PLC are all managed by
a PC.
The operator continuously receives accurate process information, also being able to interfere or interact with the
automatic monitoring system.
References
Bioscan_Lai_Sun.jpg
Lai Sun (Hong Kong)

Mới tìm hiểu về ĐKTĐ thì bạn nên tìm đọc hai cuốn:
Lý Thuyết Điều khiển tuyến tính - Phước N.D.
Lý Thuyết Điều khiển phi tuyến- Phước N.D.
Hai quyển này viết khá hay và kỹ về cơ sở lý thuyết của điều khiển tự động.
Sau đó thí bạn có thể đọc về:
- Điều khiển tối ưu
- Điều khiển bền vững
- Nhận dạng hệ thống điều khiển
- Điều khiển thích nghi
- Điều khiển phân tán
- Điều khiển mờ
- Mạng Neural (Có lẽ hỏi các bác CNTT trong này thì biết sẽ biết rõ)
Sách tiếng Anh thì có cuốn: Modern Control System - R.C.Dorf (Về điều khiển tuyến tính), Optimal Control Theory, Control Theory
Indentification and Optimal Control, cuối các cuốn sách của Nguyến Doãn Phước đều có rất nhiều tài liệu tham khảo bằng tiếng Anh hay Đức bạn có thể tìm hiểu thêm.
À mình mới chỉ nghe nói về các bộ điểu khiển P, PI, PID, PID lai chứ chưa biết về SPID.
Được freigling sửa chữa / chuyển vào 08:35 ngày 18/05/2005

Mới tìm hiểu về ĐKTĐ thì bạn nên tìm đọc hai cuốn:
Lý Thuyết Điều khiển tuyến tính - Phước N.D.
Lý Thuyết Điều khiển phi tuyến- Phước N.D.
Hai quyển này viết khá hay và kỹ về cơ sở lý thuyết của điều khiển tự động.
Sau đó thí bạn có thể đọc về:
- Điều khiển tối ưu
- Điều khiển bền vững
- Nhận dạng hệ thống điều khiển
- Điều khiển thích nghi
- Điều khiển phân tán
- Điều khiển mờ
- Mạng Neural (Có lẽ hỏi các bác CNTT trong này thì biết sẽ biết rõ)
Sách tiếng Anh thì có cuốn: Modern Control System - R.C.Dorf (Về điều khiển tuyến tính), Optimal Control Theory, Control Theory
Indentification and Optimal Control, cuối các cuốn sách của Nguyến Doãn Phước đều có rất nhiều tài liệu tham khảo bằng tiếng Anh hay Đức bạn có thể tìm hiểu thêm.
À mình mới chỉ nghe nói về các bộ điểu khiển P, PI, PID, PID lai chứ chưa biết về SPID.
Được freigling sửa chữa / chuyển vào 08:35 ngày 18/05/2005