- •Introduction to control Part I
- •Text 1. Control System
- •8. Make a list of terms from Text 1 referring to control and memorize them.
- •9. Read and translate Text 2 Text 2. Basic Feedback Loop
- •10. Make a list of terms from Text 2 referring to control and memorize them.
- •11. Read and give a short summary of Text 3 Text 3. An example
- •12. Make a list of terms from Text 3 referring to control and memorize them.
- •13. Translate Text 4 in written form: Text 4. Regulators and Servomechanisms
- •17. Analyse the grammatical structure of the following sentences and translate them:
- •Text 5. Stability and performance
- •16. Supply synonyms for the following words:
- •19. Make a list of terms from Text 5 referring to control and memorize them.
- •23. Supply synonyms for the following words: Meet, to take place, because of, as regards, breakdown, to consider
- •24. Analyse the grammatical structure of the following sentences and translate them:
- •25. Translate Text 6: Text 6. The uncertainties
- •25. Make a list of terms from Text 6 referring to control and memorize them.
- •26. Read and translate Text 7. Text 7
- •27. Make a list of terms from Text 7 referring to control and memorize them.
- •28. Read and translate Text 8 without a dictionary. Text 8. Representations of Uncertainty
- •30. Give derivatives of the following words and translate them into Russian:
- •32. Supply synonyms for the following words:
- •Text 9. Servomechanism
- •Text 10. Performance: Tracking and Disturbance Rejection
- •43. Make a list of terms from Text 10 and memorize them. Rart II
- •1. Read and translate Text 11.
- •Text 11. The Philosophy of Classical Control
- •Make a list of terms from Text 11 and memorize them.
- •Read and translate Text 12. Text 12. Classical control theory: the closed-loop controller
- •Make a list of terms from Text 12 and memorize them.
- •Read and translate Text 13. Text 13. Controllability and Observability
- •Make a list of terms from Text 13 and memorize them.
- •Read and translate Text 14. Text 14. Control Specifications
- •Make a list of terms from Text 14 and memorize them.
- •Read and translate Text 15. Text 15. Model Identification and Robustness
- •System identification
- •Analysis
- •Constraints
- •Make a list of terms from Text 15 and memorize them.
- •Read and translate Text 16 Text 16. Control Objectives
- •Make a list of terms from Text 16 and memorize them
- •Give a short summary of Text 17 Text 17. Control Objectives
- •(From Ch.Schmid. Course on Dynamics of multidisplicinary and controlled Systems )
- •Make a list of terms from Text 17 and memorize them
- •Give a short summary of Text 18 (in written form) Text 18. Main control strategies
- •Pid controllers
- •Optimal control
- •Adaptive control
- •Intelligent control
- •17. Make a list of scientific terms that are used in Text 18, give their Russian equivalents and memorize them.
- •18. Give a short summary of Text 19 (in written form) Text 19. Feedback
- •Application of feedback in mechanical engineering
- •Make a list of terms from Text 19 and memorize them.
- •Give a short summary of Text 20 Text 20. Pid controller
(From Ch.Schmid. Course on Dynamics of multidisplicinary and controlled Systems )
Make a list of terms from Text 17 and memorize them
Give a short summary of Text 18 (in written form) Text 18. Main control strategies
Every control system must guarantee first the stability of the closed-loop behavior. For linear systems, this can be obtained by directly placing the poles. Non-linear control systems use specific theories (normally based on Aleksandr Lyapunov's Theory) to ensure stability without regard to the inner dynamics of the system. The possibility to fulfill different specifications varies from the model considered and the control strategy chosen. Here a summary list of the main control techniques is shown:
Pid controllers
The PID controller is probably the most-used feedback control design, being the simplest one. "PID" means Proportional-Integral-Derivative, referring to the three terms operating on the error signal to produce a control signal. PID controllers are the most well established class of control systems: however, they cannot be used in several more complicated cases, especially if MIMO systems are considered.
Optimal control
Optimal control is a particular control technique in which the control signal optimizes a certain "cost index": for example, in the case of a satellite, the jet thrusts needed to bring it to desired trajectory that consume the least amount of fuel. Two optimal control design methods have been widely used in industrial applications, as it has been shown they can guarantee closed-loop stability. These are Model Predictive Control (MPC) and Linear-Quadratic-Gaussian control (LQG). The first can more explicitly take into account constraints on the signals in the system, which is an important feature in many industrial processes. However, the "optimal control" structure in MPC is only a means to achieve such a result, as it does not optimize a true performance index of the closed-loop control system. Together with PID controllers, MPC systems are the most widely used control technique in process control.
Adaptive control
Adaptive control uses on-line identification of the process parameters, or modification of controller gains, thereby obtaining strong robustness properties. Adaptive controls were applied for the first time in the aerospace industry in the 1950s, and have found particular success in that field.
Intelligent control
Intelligent control use various AI computing approaches like neural networks, Bayesian probability, fuzzy logic, machine learning, evolutionary computation and genetic algorithms to control a dynamic system
Non-linear control systems
Processes in industries like robotics and the aerospace industry typically have strong non-linear dynamics. In control theory it is sometimes possible to linearize such classes of systems and apply linear techniques: but in many cases it can be necessary to devise from scratch theories permitting control of non-linear systems. These normally take advantage of results based on Lyapunov's theory. Differential geometry has been widely used as a tool for generalizing well-known linear control concepts to the non-linear case, as well as showing the subtleties that make it a more challenging problem. (3000)