现代控制工程第三章.pptVIP

Principle of Automatic Control Prof. Xie Hongwei College of Mechatronic and Automation National University of Defense Technology April ~July 2008 2-1 System modeling ---introduction 1. To control complex systems suitably, one must understand the systems thoroughly. 了如指掌，方能随心所欲。 The tools and platforms for analyzing and understanding the systems are the quantitative mathematical models. Qualitative models are far from enough for engineering. 2. Formula describing the input-output relationship of the systems are call mathematical models. Dynamic in nature for the systems under consideration, the descriptive equations are usually differential equations. They are the start points of control engineering. 3、Many physical systems from different fields that seem to be far apart may share the same differential equations describing their dynamic behavior. They are called analogous systems. The common differential equations apply equally well to them. The spring-mass-damper system and electrical RLC circuit can be described by a common differential equation. 4、Approximation and reasonability Since most physical systems are nonlinear, an important issue in system modeling is the model linearization. Not all systems have reasonable linear approximations. Only Linear Time-invariant Continuous Systems will be discussed. This allows us to use Laplace transform methods and get insightful understanding of the system behavior. 5. Models Developing a. Mechanism Modeling The differential equations describing the dynamic performance of a physical system are obtained by utilizing the physical laws of the process. This approach applies equally to different kinds of systems, but more suitable for simple system modeling. For example, Newton’s second Law. b. Experiment Modeling Using typical test signals as inputs to stimulate the syste