1 / 15

CH 1 Introduction

CH 1 Introduction. Prof. Ming-Shaung Ju Dept. of Mechanical Engineering NCKU. 1. Introduction. What is adaptive control? An adaptive controller is a controller with adjustable parameters and a mechanism for adjusting the parameters. Adaptive control systems have two loops

bedros
Download Presentation

CH 1 Introduction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CH 1 Introduction Prof. Ming-Shaung Ju Dept. of Mechanical Engineering NCKU

  2. 1. Introduction • What is adaptive control? An adaptive controller is a controller with adjustable parameters and a mechanism for adjusting the parameters. • Adaptive control systems have two loops • A normal feedback with process and controller • A parameter adjustment loop (slower dynamics)

  3. Structure of Adaptive Systems

  4. History of adaptive control theory • 1950s design of autopilots for high performance aircraft (gain scheduling) speeds & altitude • 1960s control theories : state space & stability, dynamic programming, system identification • 1970s different estimation schemes combined with various design methods • Late 1970s-1980s proofs for stability of adaptive systems, merge of robust control and system identification

  5. USA X-15 experimental aircraft

  6. History of adaptive control theory (cont’d) • 1990s robustness of adaptive controllers, nonlinear system theory help understanding adaptive control • 2000s related to learning in computer science, artificial intelligence

  7. Why adaptive control system? • Linear feedback has limited capability to cope with parameter changes of the process and variations in disturbance characteristics • Process variations may due to • Nonlinear actuators • Large deviation of operating point • Examples of variations in disturbance • frequency contents of disturbance

  8. Adaptive Schemes • Gain scheduling • Model-reference adaptive control • Self-tuning regulator • Dual control

  9. Gain Scheduling Speed (Mach no.) Altitude Note: command & control signal are not utilized

  10. Model-Reference Adaptive Control Performance specification e = ym-y

  11. Self-Tuning Regulator Indirect adaptive Desired System identification Certainty equivalent principle: estimates are used as if they are true parameters

  12. Dual Control • Limitation of above schemes: parameter uncertainties not considered • When Certainty Equivalence Principle is not valid • Augment process state and parameters into a new state and formulate a nonlinear stochastic control problem (stochastic optimal control ) • Nonlinear estimator: conditional probability distribution of state p(z｜y, u) (hyper-state) • Feedback controller maps hyperstate to control • Maintain good control and small estimation errors (dual)

  13. Dual Control

  14. Adaptive Control Problem • Process Model • State space model • Transfer function (matrix) • Continuous-time or discrete-time • Controller structure • A controller with adjustable parameters • Direct adaptive control • Parameters tuned without characteristics of the process and its disturbance • Indirect adaptive control • Process model and disturbance characteristics are estimated then use these information to design the controller

  15. Design Procedures • Characterize desired behavior of closed-loop system (stability, performance) • Determine a control law with adjustable parameters • Find a mechanism for adjusting the parameters • Implement the control law

More Related