교류서보전동기의 속도제어를 위한 GA-PI 제어기 설계

Abstract

Instead of using general controllers, genetic algorithm based on a PI is used to control AC servo motors. Genetic algorithm techniques are considered as tools of artificial intelligence and are finding widespread applications in different areas of science and engineering problems. AC servo systems are competed with DC servo systems for motion control. Because of their favorable electrical, mechanical properties, good dynamics and a high efficiency, the AC servo motor has covered most servo-applications in robotics, machine tools and positioning devices. Permanent magnet synchronous motor is receiving attention for servo drive applications during recent years because of its high torque to inertia ratio, superior power density and high efficiency. Recent development of high energy materials such as neodymium has focussed attention on wide variety of speed and position control applications. The PI controller has the features of simple structure, stability and reliability. But it has limitations in complex system control and can not remain above virtues under the conditions of parameters and environment uncertainties. With development of microprocessor and power electronics, numerous adaptive control, optimal control, robot control and so on, have been practically implemented in many control schemes. Comparing with PI, these methods have nonlinear control and highly complex system but they depend on accurate model excessively and need long time and complex computation. The effects of modern control theory are diminishe when unmodeled dynamics of the system emerge. In order to reduce mechanical parameter variation, and to obtain a good dynamic performance at the viewpoint and wide speed range, an intelligent controller is employed. The genetic algorithm can be adopted widely, however the convergence speed is limited by its constant learning rate. The genetic algorithm based self tuner of coefficient , consists of position value. In this paper, genetic algorithm based on a PI is proposed and executed in a DSP, for the implementation of high performance speed control system. A 32-bit DSP, TMS320LF2407 has been used, which is capable of high speed and floating point calculation. The design technicue of self tuning PI controller using genetic algorithm with the newly proposed learning algorithm is presented, and the designed controller is used to the accurate position control of unmodeled AC servo systems with uncertainty. To show the effectiveness of the proposed scheme, several simulation studies has been performed. Computer simulations were performed to show the usefulness of the proposed controller in case of AC servo motor control. As shown in results of simulations, proposed controller has good performance and robust properties even though disturbance exists. The genetic algorithm has been used to find quickly, random practical optimum solution, can solve problems concentrating to local minima because of taking many input at the same time as well as an input of reference space. Therefore, there is no continuously differential condition in the object function, is able to parallel calculation and same time-optimization as encoding many variable to one string. We executed controller to apply driver of AC Servo motors with genetic algorithm-PI controller(GA-PI Controller) to realize precision control and application of robot actuator in industry. The proposed controller for good tracking command values for motor driving is verified through the computer simulation. The system is designed to improve set-point tracking capability. The simulation and experimental results show that this genetic algorithm system provides precise response.