Adaptive Iterative Learning Control of Nonlinearly Parameterized Pure Feedback Nonlinear Systems

This paper is devoted to the generalized projective synchronization problem of fractional-order systems subject to the unknown local Lipschitz conditions. Based on the definition of the fractional integral, a suitable variable is defined, thereby the generalized projective synchronization problem between leader and follower is transformed into the stabilization problem of the system consisting of the newly defined variable. An adaptive iterative learning controller is proposed to control the fractional-order systems. Based on the composite energy function method, the convergence of learning process is analysed. Consequently, the sufficient conditions are derived to guarantee that the leader-following FOSs can achieve the generalized projective synchronization in the finite time interval as the iteration step goes to infinity. Finally, a numerical simulation example is presented to demonstrate the effectiveness of the proposed method.

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Adaptive Iterative Learning Control of Nonlinearly Parameterized Pure Feedback Nonlinear Systems

Cited by 6 publications

References 20 publications

Performance Enhancement of Electrohydraulic Servo System Using Teaching Learning-Based Optimization and CDM-Backstepping with Disturbance Observer

Performance Enhancement of Electrohydraulic Servo System Using Teaching Learning-Based Optimization and CDM-Backstepping with Disturbance Observer

Adaptive Iterative Learning Control for Nonlinearly Parameterized Non-Strict Feedback Nonlinear Systems with Full-State Constraints

Iterative Learning Control for Generalized Projective Synchronization of Fractional-order System with Unknown Local Lipschitz Function

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