进行仿真和设计。
This course introduces the basic principles and tools for the design and analysis of feedback systems. It is intended to
serve a diverse audience of scientists and engineers who are interested in understanding and utilizing feedback in
physical, biological, information and social systems. A major goal of this course is to present a concise and insightful
view of the current knowledge in feedback and control systems. In developing this course, we have attempted to
condense the current knowledge by emphasizing fundamental concepts. We believe that it is important to understand
why feedback is useful, to know the language and basic mathematics of control and to grasp the key paradigms that
have been developed over the past half century. It is also important to be able to solve simple feedback problems using
back-of-the-envelope techniques, to recognize fundamental limitations and difficult control problems and to have a feel
for available design methods.
Topics include:
◦ Introduction and course overview – automatic control, why and where is it used (examples) overview of main
concepts: feedback vs. open loop control, performance measures, analogue and digital control.
◦ Laplace transforms – review of methods and standard results, especially the solution of linear differential equations,
transfer functions, block diagrams.
◦ Dynamic modeling and model properties - differential equations, transfer functions, state-space forms of system
models; conversion between types; block diagrams and prototype feedback control systems, performance metrics,
standard first-order and second-order systems, impulse and step responses, effect of poles and zeros, steady-state
error.
◦ PID control – definition, effects of the proportional, integral and derivative terms, choice of gains in simple cases,
Ziegler-Nichols methods.
◦ Root locus methods – characteristic equation, definition of the root locus (RL), rules for sketching the RL, control
system design using root locus techniques, lead and lag compensators, Matlab RLTOOL, pre-compensators and
sensitivity function.
◦ Frequency response methods – frequency response function, Bode plots, Nyquist plots, stability conditions, gain
and phase margins, relative stability, M-circles, lead/lag compensator designs.
◦ State-space control – stability, full state feedback, controllability, control canonical form, pole placement, state
observer, observer canonical form and placement of observer poles, introduction to linear optimal control.
The course makes wide use of Matlab to represent and simulate control systems. A group final project on control
system design is included in the course; this makes use of Matlab and Simulink for simulation and design.
External reference:
◦ SUSTech ME307: Fundamentals of control engineering
◦ SUSTech ME331: Robot modeling and control
◦ UMICH ME461: Automatic control
◦ MIT 2.14: Analysis and Design of Feedback Control Systems
Through lectures, lab sessions and final project, students should have mastered the following abilities:
◦ Find differential equation and transfer function of single-input, single-output mechanical system.
◦ Draw feedback system block diagram and find closed-loop transfer function.
◦ Translate time-domain specifications into frequency-domain requirements.
◦ Determine steady-state error to step and ramp inputs and disturbances.
◦ Given a system transfer function, find time-domain behavior (impulse, step and frequency response).
◦ Design PI, PD, PID, lead, and lag compensators to meet control goals.
◦ Use software tools to design state-space controllers to meet control goals.
◦ Use software tools to translate continuous-time controllers into digital equivalent.
◦ Find closed-loop transfer function, system poles, frequency response using software tools.
◦ Simulate system behavior using software tools.