DESIGN AND OPTIMIZATION OF PID CONTROLLER USING GENETIC ALGORITHM

Natural evolution is mimicked by Genetic Algorithms (GAs) which is a stochastic global search method used for optimization.. In missile control systems Proportional Integral Derivative (PID) control is widely used, but due to empirically selected parameters Kp, Ki, Kd it is difficult to achieve parameter optimization. Genetic algorithm is a search algorithm that is based on natural selection and genetics principles.GA is a computational algorithm which deals with genetics of the human body. It evolves with the number of iterations. After ever iteration a better result is expected. These results are checked for the error. The fittest roots or solution are considered for the next generation based on the selection criterion. GA randomly generates the initial population of the PID control parameters according to the calculation of selection (Normalized Geometric Selection), crossover (Arithmetic Crossover) and mutation (Uniform Mutation), thus optimizing the control parameters. Mean Square Error (MSE) value is chosen as the performance assessment index. For a missile altitude control Proportional Integral Derivative (PID) controller using genetic algorithm is implemented & compared with the classical method Zeigler-Nichols (Z-N) in the paper. Z-N method is classical method which tunes the parameters of PID. The parameters of PID are difficult to tune. Tuned parameters give the optimum solution. Optimum solution generally converges to a solution having minimum error. Minimum error gives a response of the system in terms of maximum over shoot, Settling time, Rise time & Steady State Error. The designed PID with the Genetic Algorithm has much faster response than th