Abstract
Proportional Integral Derivative (PID) controllers are extensively used in industry for process instrumentation application. PID controllers have also found widespread application in Power System Control. To achieve effective control optimal tuning of PID gains of the controller is necessary. This controller gain tuning problem is a multimodal non-convex optimization problem. This paper proposes a tuning strategy based on Mine Blast Algorithm (MBA); a population based algorithm for tuning the controller. This algorithm is a newly developed optimization technique. The motivation of this study is to determine if MBA presents a better alternative than traditional soft computing based optimization methods. The algorithm simulates the behavior of exploding mines in a mine field. This algorithm has been used to find optimal values of PID gains. The performance of MBA is compared with results obtained from Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). All the codes have been developed in house in Matlab environment. MBA has demonstrated up to 40% reduction in computational burden while maintaining controllers output characteristics.
Published Version
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