Terminal constraints in predictive control provide a guarantee stability, but result in deadbeat predicted responses and can violate physical constraints. Two recent algorithms (Rossiter et al, 1996a; Scokaert and Rawlings, 1996) removed this restriction, but of these the former lacks the guarantee of l2-optimality whereas the latter lacks the guarantee of feasibility. Here we develop algorithms which overcome both these difficulties and illustrate their advantages by means of numerical examples. © 1998 Elsevier Science Ltd. All rights reserved
Disturbances in the presence of constraints can drive predictive control into infeasibility and inst...
This paper copes with the problem of satisfying input and/or state hard constraints in set-point tra...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
Terminal constraints in predictive control provide a guarantee stability, but result in deadbeat pre...
Terminal constraints provide for stable predicted trajectories and thus form the basis of predictive...
Predictive controllers allow for systematic inclusion of constraints. However, the associated quadra...
Input constraints present a major difficulty in the design of stable predictive controllers. A conve...
A predictive control algorithm is presented that uses a weighted sum of Linear quadaratic (LQ) optim...
This article is concerned with the approximation of constrained continuous-time linear quadratic reg...
Multi parametric quadratic programming solutions to predictive control can require large numbers of ...
The connections between optimization and control theory have been explored by many researchers and o...
In this paper we review a dual fast gradient-projection approach to solving quadratic programming (Q...
International audienceThis article addresses the fast on-line solution of a sequence of quadratic pr...
A receding horizon predictive control algorithm for systems with model uncertainty and input constra...
In this paper, it is shown how a performance tuple can be obtained in model predictive control if th...
Disturbances in the presence of constraints can drive predictive control into infeasibility and inst...
This paper copes with the problem of satisfying input and/or state hard constraints in set-point tra...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
Terminal constraints in predictive control provide a guarantee stability, but result in deadbeat pre...
Terminal constraints provide for stable predicted trajectories and thus form the basis of predictive...
Predictive controllers allow for systematic inclusion of constraints. However, the associated quadra...
Input constraints present a major difficulty in the design of stable predictive controllers. A conve...
A predictive control algorithm is presented that uses a weighted sum of Linear quadaratic (LQ) optim...
This article is concerned with the approximation of constrained continuous-time linear quadratic reg...
Multi parametric quadratic programming solutions to predictive control can require large numbers of ...
The connections between optimization and control theory have been explored by many researchers and o...
In this paper we review a dual fast gradient-projection approach to solving quadratic programming (Q...
International audienceThis article addresses the fast on-line solution of a sequence of quadratic pr...
A receding horizon predictive control algorithm for systems with model uncertainty and input constra...
In this paper, it is shown how a performance tuple can be obtained in model predictive control if th...
Disturbances in the presence of constraints can drive predictive control into infeasibility and inst...
This paper copes with the problem of satisfying input and/or state hard constraints in set-point tra...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...