Abstract
A Nonlinear PID (NPID) controller tuning based on the Enhanced Artificial Bee Colony (E-ABC) algorithm is presented. The ABC algorithm uses the foraging behavior of honey bee swarm to find the optimal PID parameters kp, ki and kd. In this proposed E-ABC, the Particle Swarm Optimization (PSO) swarm intelligence behavior is inherited to ABC scout bee to get proper selection of food source. The convergence characteristics of the E-ABC based optimization shows that the proposed method provides better controller settings with minimum iteration. To show the effectiveness of the proposed method, it is presented to the nonlinear Continuous Stirred Tank Reactor (CSTR) process and the results are compared with the conventional Internal Model Control (IMC) tuning method, and heuristic approaches viz., Genetic Algorithm (GA), Simulated Annealing (SA), PSO and other hybrid methods based PID performances. From the results of integral performance criterions viz., ISE, IAE and ITAE, it is evident that the proposed E-ABC provides better tracking and improves closed loop accuracy.
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