This paper addresses the 5 stability of soft-constrained model predictive control (MPC). It is shown that the infinite horizon soft-constrained MPC problem can be solved as a finite horizon soft-constrained MPC problem if the prediction horizon is greater than an upper bound. The contribution of this paper is a procedure to compute the prediction horizon upper bound, which guarantees the stability. The proposed technique is verified using two simulation examples. The second example (inverted pendulum) is verified through practical implementation
The presence of constraints in the on-line optimization problem solved by Model Predictive Control a...
This paper will demonstrate how the convexity and quadratic nature of the soft constrained model pre...
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with...
This article addresses the stability of soft-constrained model predictive control. It is shown that ...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
Soft constrained model predictive control (MPC) is frequently applied in practice in order to ensure...
Soft constrained model predictive control (MPC) is frequently applied in practice in order to ensure...
Abstract—Soft constrained MPC is frequently applied in prac-tice in order to ensure feasibility of t...
In this paper a new robust Modelbased Predictive Control (MPC) algorithm for linear models with poly...
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is d...
receding horizon control. Abstract: A typical bottleneck of model predictive control algorithms is t...
MPC or model predictive control is representative of control methods which are able to handle inequa...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
The presence of constraints in the on-line optimization problem solved by Model Predictive Control a...
This paper will demonstrate how the convexity and quadratic nature of the soft constrained model pre...
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with...
This article addresses the stability of soft-constrained model predictive control. It is shown that ...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
Soft constrained model predictive control (MPC) is frequently applied in practice in order to ensure...
Soft constrained model predictive control (MPC) is frequently applied in practice in order to ensure...
Abstract—Soft constrained MPC is frequently applied in prac-tice in order to ensure feasibility of t...
In this paper a new robust Modelbased Predictive Control (MPC) algorithm for linear models with poly...
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is d...
receding horizon control. Abstract: A typical bottleneck of model predictive control algorithms is t...
MPC or model predictive control is representative of control methods which are able to handle inequa...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
We derive stability conditions for Model Predictive Control (MPC) with hard constraints on the input...
The presence of constraints in the on-line optimization problem solved by Model Predictive Control a...
This paper will demonstrate how the convexity and quadratic nature of the soft constrained model pre...
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with...