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For the point-to-point (P2P) iterative learning control (ILC), the tracked-points are usually known. However, in many cases, time allocation can be regarded as an optimization variable to achieve optimal control energy. Also, in some situations, only information on certain dimensions in the output is needed to be tracked. Based on the combination of the above two aspects, this paper studies energy-optimal time allocation in P2P ILC with specified output tracking. An algorithm based on a two-stage optimization framework that integrates the norm-optimal ILC and the gradient method is proposed. The proposed algorithm is further extended to a system with input constraints, and its robustness is analyzed. Finally, simulation tests on a gantry robot are performed to validate the performance of the proposed algorithm.

Energy-Optimal Time Allocation in Point-to-Point ILC With Specified Output Tracking