
The authors present an efficient algorithm for solving the infinite-horizon constrained linear quadratic regulator (CLQR) problem. The algorithm is based on multi-parametric quadratic programming and reachability analysis. This combination outperforms all comparable mp-QP approaches in terms off-line computation speed. Moreover, the authors show that, when compared to on-linke computation procedures, the time necessary to obtain the optimal input was significantly decreased, making CLQR an attractive solution even for fast processes. Furthermore, a worst-case run-time can be guaranteed.
invariant set, Design techniques (robust design, computer-aided design, etc.), model predictive control, Optimal stochastic control, constrained infinite horizon control, linear quadratic regulator
invariant set, Design techniques (robust design, computer-aided design, etc.), model predictive control, Optimal stochastic control, constrained infinite horizon control, linear quadratic regulator
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