Optimal-horizon model-predictive control with differential dynamic programming

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STACHOWICZ-UNDERGRADUATERESEARCHOPTIONTHESIS-2021.pdf (304.74 KB)
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Stachowicz, Kyle W.
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School of Computer Science
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Undergraduate Scholarship
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http://hdl.handle.net/1853/66266
Abstract
We present an algorithm, based on the Differential Dynamic Programming framework, to handle trajectory optimization problems in which the horizon is determined online rather than fixed a priori. This algorithm exhibits exact one-step convergence for linear, quadratic, time-invariant problems and is fast enough for real-time nonlinear model-predictive control. We show derivations for the nonlinear algorithm in the discrete-time case, and apply this algorithm to a variety of nonlinear problems. Finally, we show the efficacy of the optimal-horizon model-predictive control scheme compared to a standard MPC controller, on an obstacle-avoidance problem with planar robots.
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2021-12
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Undergraduate Thesis
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