Manufacturing systems: Scheduling and deposition process control. Power industry: Motor control, power control/distribution. and load estimation Process controL: Temperature, pressure, and level control, failure diagnosis, distillation column control, and desalination processes Robotics: Position control and path planning This list is only representative of the range of possible applications for the methods of this book. Others have already been studied while still others are yet to be identified 31
31 • Manufacturing systems: Scheduling and deposition process control. • Power industry: Motor control, power control/distribution, and load estimation. • Process control: Temperature, pressure, and level control, failure diagnosis, distillation column control, and desalination processes. • Robotics: Position control and path planning. This list is only representative of the range of possible applications for the methods of this book. Others have already been studied, while still others are yet to be identified
The primary goal of control engineering is to distill and apply knowledge about how to control a process so that the resulting control system will relia bly and safely achieve high performance operation. In this chapter we show how fuzzy logic provides a methodology for representing and implementing our knowledge a bout how best to control a process 32
32 The primary goal of control engineering is to distill and apply knowledge about how to control a process so that the resulting control system will reliably and safely achieve highperformance operation. In this chapter we show how fuzzy logic provides a methodology for representing and implementing our knowledge about how best to control a process
2.2 Fuzzy Control: Tutorial Introduction Ouestions a How do we choose fuzzy controller inputs and outputs a How do we put control knowledge in to rule-bases? How do we quantify the knowledge in fuzzy controller design Why do that? 33
33 2.2 Fuzzy Control: A Tutorial Introduction Questions ◼ How do we choose fuzzy controller inputs and outputs ? ◼ How do we put control knowledge in to rule-bases? How do we quantify the knowledge in fuzzy controller design? Why do that?
What are a fuzzy controller composed? A block diagram of a fuzzy control system is shown in Figure 2.1. The fuzzy controller is composed of the following four elements 34
34 What are a fuzzy controller composed? A block diagram of a fuzzy control system is shown in Figure 2.1. The fuzzy controller is composed of the following four elements:
模糊控制器 参考输入 输入 输出 r(t) 模L解 u(t 过程 糊 模 化 糊 规则库 igure 2.2 Fuzzy Control 35
35 Figure 2.2 Fuzzy Control 模糊控制器 模 糊 化 解 模 糊 推理机 规则库 过程 输入 u(t) 输出 y(t) 参考输入 r(t)