MODELLING AND OPTIMIZATION OF PID CONTROLLER’s PARAMETERS FOR DEEP SPACE ANTENNA POSITIONING SYSTEM USING GENETIC ALGORITHM

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Author

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Department of Engineering

ABSTRACT
Proportional-Integral-Derivative (PID) controllers have been widely used in process industry for decades, from small industry to high technology industry, but they still remain poorly tuned by use of conventional tuning methods like the Zeigler-Nichols method. In this work, PID controller’s parameters for deep space antenna positioning system were optimized using Genetic Algorithm (GA). Using genetic algorithm, the tuning of the controller results in the optimum controller being evaluated for the system every time. The system was modelled using Bond-Graph in 20Sim environment and the PID Controller was optimized using GA in Matlab/Simulink environment in order to get the optimum value for its parameters. Simulation result shows that the performance of the optimized PID Controller using Genetic Algorithm (GA) for deep space antenna positioning system at response values of 2.2412sec rise time, 2.9861sec settling time and 0% overshoot and undershoot is better than the conventionally, Zeigler-Nichols method, tuned Controller at response values of 0.8568sec rise time, 9.2289sec settling time, 66.3812% overshoot and 23.1264% undershoot; thereby comparing the work at an amplifier gain value of 100. Results for different amplifier gain values also show that the system response at an amplifier gain of 250 produced the best response in terms of rise time, settling time and overshoot but has a problem of peaking in its transient state characteristics.