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• W3169486517 abstract "In this letter, we present an iterative Model Predictive Control (MPC) design for piecewise nonlinear systems. We consider finite time control tasks where the goal of the controller is to steer the system from a starting configuration to a goal state while minimizing a cost function. First, we present an algorithm that leverages a feasible trajectory that completes the task to construct a control policy which guarantees that state and input constraints are recursively satisfied and that the closed-loop system reaches the goal state in finite time. Utilizing this construction, we present a policy iteration scheme that iteratively generates safe trajectories which have non-decreasing performance. Finally, we test the proposed strategy on a discretized Spring Loaded Inverted Pendulum (SLIP) model with massless legs. We show that our methodology is robust to changes in initial conditions and disturbances acting on the system. Furthermore, we demonstrate the effectiveness of our policy iteration algorithm in a minimum time control task." @default.
• W3169486517 created "2021-06-22" @default.
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• W3169486517 date "2022-01-01" @default.
• W3169486517 modified "2023-09-26" @default.
• W3169486517 title "Iterative Model Predictive Control for Piecewise Systems" @default.
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• W3169486517 doi "https://doi.org/10.1109/lcsys.2021.3086561" @default.
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