Hierarchical gradient based control optimized by shuffled frog leaping algorithm for large-scale systems

Abstract

In this paper, a new hybrid approach based on hierarchical gradient based control and Shuffled Frog Leaping optimization algorithm (SFLA) is presented for optimal control of large-scale systems. In this approach, the large-scale system is decomposed into smaller subsystems and then solved separately at the first level. Afterward at the second level, a coordinator coordinate the subsystems to achieve overall optimal solution. For this, the discrete-time linear quadratic regulators (DLQR) with prescribed degree of stability are used to control each subsystem in the first level in which the SFL optimization algorithm is employed for optimizing the cost function of the DLQR. In the second level, the solutions obtained from the first level are coordinated using gradient-type strategy, which is updated by the error of the coordination vector. The proposed method is simulated on the aircraft system and the obtained results are compared with the centralized optimal control.