Fast Algorithm for Estimating Control Horizon of Input Constrained Linear Quadratic Regulation

Abstract:

A fast algorithm for estimating the control horizon of the input constrained linear quadratic regulation (LQR) problem is presented. It is known that there exists a finite horizon such that the infinite horizon constrained LQR problem can be solved as a finite horizon constrained LQR problem. An efficient algorithm to estimate the upper bound of the horizon is presented based on the linear programming. It only needs to solve a linear programming problem for on line application. Finally, the comparison among some methods is shown by an example. The proposed algorithm has less conservative than those of other algorithms.

• Periodical: Advanced Materials Research (Volumes 546-547)
• Pages: 1056-1062
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.546-547.1056
• Online since: July 2012
• Authors: Wei Wei Zhang, Yong Sun
• Keywords: Control Horizon, Linear Quadratic Regulator, Model Predictive Control (MPC), Null-Controllable Region

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