In this paper, 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 . We present an algorithm that leverages a feasible trajectory that completes the task toconstruct 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 . We test the proposed strategy on adiscretized Spring Loaded Inverted Pendulum (SLIP) model with massless legs. Weshow that our methodology is robust to changes in initial conditions anddisturbances acting on the system .

Author(s) : Ugo Rosolia, Aaron D. Ames

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Keywords : control - goal - model - state - system -

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