Servocontrol of a Mobile Robot by Using Genetic Algorithms
Jun Tang*, Keigo Watanabe** and Katsutoshi Kuribayashi*
*Department of Mechanical Engineering, Faculty of Engineering, Yamaguchi University, 2557 Tokiwadai, Ube 755-8611, Japan
**Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, Honjomachi-1, Saga 840-8502, Japan
One problem that not yet solved in optimum servocontroller design is determination of positive definite matrices Q and R for the Riccati equation, although such servocontrollers have been applied in many complex control processes. We propose a way to tune weighting matrices by applying genetic algorithms (GAs) to type 1 and 2 optimum linear servocontrollers for a mobile robot. Simulation verified the controller’s effectiveness.
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