Model-free iterative learning control for LTI systems with actuator constraints
نویسندگان
چکیده
This paper presents a model-free iterative learning control algorithm for linear time-invariant systems. At every trial, a finite impulse response filter to update the system input is calculated by solving a convex optimization problem that minimizes the next trial’s tracking error taking into account actuator constraints. Simulation results show the ability of the proposed model-free method to deal with actuator constraints and to fully compensate for trial-invariant disturbances such as actuator cogging.
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