Decentralized Periodic Dynamic Event-Triggering Fuzzy Load Frequency Control for Multiarea Nonlinear Power Systems Based on IT2 Fuzzy Model

The article investigates the decentralized periodic dynamic event-based load frequency control problem for a class of multiarea nonlinear power systems with uncertain parameters. For overcoming the limitations on the knowledge of studied power systems, the interval type-2 (IT2) fuzzy model is synthesized by using local linear models relevant to some operation points. Under the IT2 fuzzy framework, the decentralized periodic dynamic event-based fuzzy control law is proposed to reduce the bandwidth burden of communication networks. Based on the Lyapunov stability theory, a sufficient condition is presented such that closed-loop systems are exponentially stable with a given $H_{\infty }$ performance. The existence condition of the controller gains and the triggering scheme's parameters is expressed in terms of matrix inequalities. The obtained results are extended to two situations, i.e., the decentralized periodic static event-based fuzzy control and the decentralized periodic sampling fuzzy control. Compared with the latter two control approaches, the developed decentralized periodic dynamic triggering strategy can provide the lowest communication frequency. Finally, the validity and superiority of the developed method are demonstrated by simulation results.