Artificial Intelligence
Heuristically enhanced feedback control of constrained discrete-time linear systems
Automatica (Journal of IFAC)
Piecewise-linear LQ control for systems with input constraints
Automatica (Journal of IFAC)
On constrained infinite-time linear quadratic optimal control
Systems & Control Letters
The explicit linear quadratic regulator for constrained systems
Automatica (Journal of IFAC)
Convexity recognition of the union of polyhedra
Computational Geometry: Theory and Applications
Set Membership approximation theory for fast implementation of Model Predictive Control laws
Automatica (Journal of IFAC)
Analytical expression of explicit MPC solution via lattice piecewise-affine function
Automatica (Journal of IFAC)
The expression of control law for zone constraints predictive control
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Survey of explicit approaches to constrained optimal control
Switching and Learning in Feedback Systems
Brief An algorithm for multi-parametric quadratic programming and explicit MPC solutions
Automatica (Journal of IFAC)
Technical Communique: Evaluation of piecewise affine control via binary search tree
Automatica (Journal of IFAC)
Predictive switching supervisory control of persistently disturbed input-saturated plants
Automatica (Journal of IFAC)
Optimal control of sampled-data piecewise affine systems
Automatica (Journal of IFAC)
Hi-index | 22.16 |
Optimal feedback solutions to the infinite horizon LQR problem with state and input constraints based on receding horizon real-time quadratic programming are well known. In this paper we develop an explicit solution to the same problem, eliminating the need for real-time optimization. It is shown that the resulting feedback controller is piecewise linear. This explicit functional structure is exploited for efficient real-time implementation. A suboptimal strategy, based on a suboptimal choice of a finite horizon and imposing additional limitations on the allowed switching between active constraint sets on the horizon, is suggested in order to address the computer memory and processing capacity requirements of the explicit solution.