Spiritual Search: a Novel Metaheuristic Algorithm for Control Engineering Optimization

Abstract

Control synthesis is now considered as one of the optimization problems, which can be successfully and completely solved by efficient metaheuristic optimization techniques called “metaheuristics”. This article proposes a novel spiritual search (SS) metaheuristic algorithm-based approach for control engineering optimization. The proposed SS is conceptualized by the spiritual concentration according to the Buddhist principles. In the SS algorithm, single solution-based (trajectory-based) and population-based approaches are combined to balance the advantages of exploration and exploitation properties. To perform its effectiveness, the SS is tested against eight standard test functions and compared with the tabu search (TS) as one of the most powerful solution-based metaheuristics and the cuckoo search (CS) as one of the most efficient population-based metaheuristics. As results, the SS can provide better solutions with higher solution-found rates and shorter search-time consumed than TS and CS, respectively. Various control engineering problems, including model identification of DC motor, PID controller design and PIDA controller design, are optimized in order to demonstrate the effectiveness and robustness of the SS algorithm. Obtained results indicate that the proposed SS algorithm is a powerful optimization technique that can provide very satisfactory solutions within very short search-time consumed.