江苏大学智能控制双语课件Chapter 1 Introduction

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Scope

Artificial intelligence techniques applied to control system design. Topics include: Fuzzy Sets, Artificial Neural Networks, methods for designing fuzzy-logic controllers and neural network controllers; application of computer-aided design techniques for designing fuzzy-logic and neural-network controllers. The main principles of genetic algorithms are introduced. The application of genetic algorithms in system optimization is discussed.
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wrt: with regard to
Conventional Control Techniques

“Modern” Control Techniques: 1. Linear quadratic regulator (LQR): Minimize a cost function (maximize a performance index Optimal control). 2. Pole placement: Locate system poles (eigenvalues) to modify the modes (i.e., fundamental free natural responses) with respect to stability, speed of response, etc. modal control.
A smart person learns from his/her mistakes; but a wise person learns from others’ mistakes Definition of Intelligent Quotient: Definition of Emotional Quotient:
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Group of Process Information Engineering
Intelligent Control & Systems
Prof. Tianhong Pan
Department of Automation Jiangsu University
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Chapter 1. Introduction
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Textbook
1. 刘金琨. 智能控制. 电子工业出版社. 2. Nazmul Siddique. Intelligent Control. A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms. Springer International Publishing
IQ Person's Intelligence Average intelligence of persons of same age
EQ
Person's emotional behavior Average emotional behavior of persons ofsame age
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Conventional Control Techniques

Broad Division: 1. Time domain techniques (Differential equations wrt time t; can be nonlinear) 2. Frequency domain techniques (Transfer functions algebraic wrt frequency ω; typically linear) Servo Control: To track a specified trajectory (Commonly uses proportional-integral-derivative or PID control; typically linear) Compensators: Hardware/software modules that “compensate” for the controller shortcomings in achieving the required system performance (Lead, Lag, Lead-Lag)
That’s why we have may words that describe human intelligence based on situations. For example, General: Clever, Bright, Brilliant, Wise, Sharp, Smart, Business: Shrewd, Perceptive, Insightful, Arts: Gifted, Talented, Creative Trades: Resourceful, Ingenuous, Inventive, Skillful Reasoning: Rational, Logical, Reasonable, Sound, Sensible, Quick witted,

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Grade Composition

Attendance/Participation Simulation & Report Final Exam/Project Total
= 10% = 20% = 70% = 100%
Project to formulate a realistic control problem (preferably related to his/her own research, or otherwise we can help), to do analysis and design for the problem using the course material, to analyze the designed controller in simulation (and in implementation if possible), to give a seminar, and to submit a report
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Semester Plan
Introduction Fuzzy Sets and Fuzzy Logic Fuzzy Control Neural Networks Neural Network Control Evolutionary Computing/Genetic Algorithms
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A Feedback Control System
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Terminology
Plant or Process: System to be controlled Inputs: Excitations (known, unknown) to the system Outputs: Responses of the system Sensors: They measure system variables (excitations, responses, etc.) Actuators: They drive various parts of the system. Controller: Device that generates control signal Control Law: Relation or scheme according to which the control signal is generated Control System: Plant + controller, at least (Can include sensors, signal conditioning, etc.) Feedback Control: Control signal is determined according to plant “response” Open-loop Control: No feedback of plant response to controller Feed-forward Control: Control signal is determined according to plant “inputs” not “outputs”
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Conventional Control Techn: 1. Linear Quadratic Gaussian (LQG) Control: LQR plus a Kalman filter. When inputs and the measurements have noise 2. Nonlinear Feedback Control (Feedback Linearization Technique or FLT): Feedback signal (based on measurements or an analytical model of the plant) is applied to compensate for (remove) nonlinear effects 3. Adaptive Control: Controller parameters (e.g., PID parameters) are adjusted (tuned) according to a performance criterion. Nonlinear. 4. Sliding Mode Control: A switching controller. Control signal is switched between control laws to push the response towards a desired region (sliding surface). Nonlinear. 5. H-infinity Control: H-infinity norm (a performance criterion) is minimized. Linear (uses system transfer function).