Dynamic Collaborative Fireworks Algorithm and its applications in robust pole assignment optimization

Pole assignment optimization is important for improving system stability. This paper considers the regional pole assignment optimization based on the swam intelligence optimization algorithm. Regular pole assignment cannot overcome the effect of system disturbance and cannot reach the best control performance. And the firework algorithm (FWA) often ignore valuable local search opportunity and its selection mechanism taken much computation effort. Therefore, a Dynamic Collaborative Fireworks Algorithm (DCFWA) which reserves the advantages of Fireworks Algorithm (FWA) is presented for solve these problems, and a few features of the proposed algorithm as follows. First, a new explosion radius scaling strategy is designed by adjusting the scaling coefficient according to the distribution of optimal value points, which effectively enhances the optimal firework's search capability. Second, a new offspring fireworks selection method is built for avoiding the algorithm falling into local optimum. Third, a new initialization method is embedded into the algorithm for improving global search capability. Some well-known algorithms and our proposed algorithm are applied to several types of pole assignment optimization of control systems. The comparison results indicate that the proposed algorithm does outperform the other ones. (c) 2020 Elsevier B.V. All rights reserved.

Automated summary

This paper introduces a Dynamic Collaborative Fireworks Algorithm (DCFWA) to optimize regional pole assignment, addressing the limitations of conventional methods and offering improvements such as a new explosion radius scaling strategy, offspring fireworks selection method, and initialization method. The comparison results show that the proposed algorithm outperforms other well-known algorithms in pole assignment optimization of control systems.