江苏大学智能控制双语课件Chapter 1 Introduction

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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.
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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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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
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Intelligent Systems
In a broad sense, a smart machine must necessarily possess five essential elements to qualify as an "intelligent agent": (1)Input (sensing); (2)Output (actuation); (3)Memory (database); (4)Rules (interpretation); and (5)Ability to modify or augment one or more of the above components as necessary (adaptation). In general, Unmanned Vehicle Systems (UVS) operations comprise one or more of the following modes: (1)Manual: The system requires a human operator to control the vehicle. (2)Semi-autonomous or supervised: The system temporarily controls the operation of the vehicle and seeks supervision of the operator at planned or unplanned schedule or event. (3)Autonomous or automatic: The system controls the vehicle operation for an extended period.
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Semester Plan
Introduction Fuzzy Sets and Fuzzy Logic Fuzzy Control Neural Networks Neural Network Control Evolutionary Computing/Genetic Algorithms
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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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.
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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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)
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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Intelligent
Human Intelligence is complicated and multifaceted. The interpretation of intelligence is subjective and relative. Depends on who you talk to, there is not a single definition that fits all.
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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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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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Conventional Control Techniques

Байду номын сангаас
Other Techniques: 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).