On constrained infinite-time linear quadratic optimal control
Systems & Control Letters
Multidimensional binary search trees used for associative searching
Communications of the ACM
Linear Optimal Control Systems
Linear Optimal Control Systems
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Explicit sub-optimal linear quadratic regulation with state and input constraints
Automatica (Journal of IFAC)
The explicit linear quadratic regulator for constrained systems
Automatica (Journal of IFAC)
Brief An algorithm for multi-parametric quadratic programming and explicit MPC solutions
Automatica (Journal of IFAC)
Design of robust model-based controllers via parametric programming
Automatica (Journal of IFAC)
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This chapter presents a review of the explicit approaches to optimal control. It is organized as follows. Section 1 gives a summary of the main results of the optimal control theory. Section 2 presents briefly the methods for unconstrained optimal state feedback control of linear systems. Sections 3, 4 and 5 consider in details the explicit methods for constrained linear quadratic regulation (LQR) together with several examples. The main motivation behind the explicit solution is that it avoids the need for real-time optimization, and thus allows implementation at high sampling frequencies in real-time systems with high reliability and low software complexity. These sections include formulation of the constrained LQR problem, summary of the implicit approaches, basics of the model predictive control (MPC), description of the exact and the approximate approaches to explicit solution of MPC problems and the experimental evaluation of explicit MPC controller performance for laboratory gas-liquid separation plant.