H∞ tracking control for a class of asynchronous switched nonlinear systems with uncertain input delay     

S. Pezeshki  M.A. Badamchizadeh  A.R. Ghiasi  S. Ghaemi 《Journal of The Franklin Institute》2019,356(12):5927-5943

This paper studies the problems of stability and H∞ model reference tracking performance for a class of asynchronous switched nonlinear systems with uncertain input delay. First, it is assumed switched controller and corresponding piecewise Lyapunov function are unknown but the derivative of piecewise Lyapunov function has a condition; this condition implies that the nominal system (system without input delay and disturbance) is exponentially stable by any switched controller which satisfies this condition. With this assumption, a proper Lyapunov–Krasovskii functional is constructed. By employing this new functional and average dwell time technique, the delay-dependent input-to-state stability criteria are derived under a certain delay bound; in addition, a mechanism which finds the upper bound of input delay is proposed. Finally, a kind of state feedback control law which fulfils condition of aforesaid piecewise Lyapunov function is introduced to guarantee the input-to-state stability and H∞ model reference tracking performance. Simulation examples are presented to demonstrate the efficacy of results.  相似文献   

Type-2 fuzzy consensus control of nonlinear multi-agent systems: An LMI approach     

Ali Afaghi  Sehraneh Ghaemi  Amir Rikhtehgar Ghiasi  Mohammad Ali Badamchizadeh 《Journal of The Franklin Institute》2021,358(8):4326-4347

This paper considers a class of nonlinear fractional-order multi-agent systems (FOMASs) with time-varying delay and unknown dynamics, and a new robust adaptive control technique is proposed for cooperative control. The unknown nonlinearities of the systems are online approximated by the introduced recurrent general type-2 fuzzy neural network (RGT2FNN). The unknown nonlinear functions are estimated, simultaneously with the control process. In other words, at each sample time the parameters of the proposed RGT2FNNs are updated and then the control signals are generated. In addition to the unknown dynamics, the orders of the fractional systems are also supposed to be unknown. The biogeography-based optimization algorithm (BBO) is extended to estimate the unknown parameters of RGT2FNN and fractional-orders. A LMI based compensator is introduced to guarantee the robustness of the proposed control system. The excellent performance and effectiveness of the suggested method is verified by several simulation examples and it is compared with the other methods. It is confirmed that the introduced cooperative controller results in a desirable performance in the presence of time-varying delay, unknown dynamics, and unknown fractional-orders.  相似文献