Fuzzy Control

Example: design a cruise control system After gaining an intuitive understanding of the plant's dynamics and establishing the design objectives, the control engineer typically solves the cruise control problem by doing the following: 1. Developing a model of the automobile dynamics (which may model vehicle and power train dynamics, tire and suspension dynamics, the effect of road grade variations, etc.). 2. Using the mathematical model, or a simplified version of it, to design a controller (e.g., via a linear model, develop a linear controller with techniques from classical control). 3. Using the mathematical model of the closed-loop system and mathematical or simulation-based analysis to study its performance (possibly leading to redesign). 4. Implementing the controller via, for example, a microprocessor, and evaluating the performance of the closed-loop system (again, possibly leading to redesign). Mathematical model of the plant: – never perfect – an abstraction of the real system – " is accurate enough to be able to design a controller that will work. " ! – based on a system of differential equations " Fuzzy Control " Performance Objectives: 1. Disturbance rejection properties (e.g., for the cruise control problem, that the control system will be able to dampen out the effects of winds or road grade variations). 2. Insensitivity to plant parameter variations (e.g., for the cruise control problem, that the control system will be able to compensate for changes in the total mass of the vehicle that may result from varying the numbers of passengers or the amount of cargo).