of control methods which are able to handle physical con-straints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global asymptotic stability can be obtained. A globally stabilizing finite-horizon MPC has lately been suggested for the neutrally stable systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. In this paper, an input-to-state-stabilizing MPC is proposed for the discrete-time input-constrained neutrally stable system using a non-quadratic terminal cost which is similar to that used in the global stabilizing MPC, provide...
The objective of this paper is, on the base of existing results, to provide a general framework for ...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
Research on sub-optimal Model Predictive Control (MPC) has led to a variety of optimization methods ...
MPC(Model Predictive Control) is representative of control methods which are able to handle physical...
MPC or model predictive control is representative of control methods which are able to handle inequa...
It is well known that exponentially unstable linear systems can not be globally stabilized in the pr...
This paper proposes a framework for dealing with certain classes of nonlinear model predictive contr...
In this paper, a robust MPC for constrained discrete-time nonlinear system with additive uncertainti...
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with...
International audienceThis paper is concerned with stability and recur-sive feasibility of constrain...
We present a method to increase feasibility in MPC algorithms that use ellipsoidal terminal state co...
invariant sets, asymptotic stability. This paper is concerned with the design of stabilizing MPC con...
This paper proposes a parallelizable algorithm for linear-quadratic model predictive control (MPC) p...
In the problem of input-to-state stabilization of nonlinear systems, synthesis of input-to-state sta...
The aim of this paper is to provide new techniques for computing a terminal cost and a local state-f...
The objective of this paper is, on the base of existing results, to provide a general framework for ...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
Research on sub-optimal Model Predictive Control (MPC) has led to a variety of optimization methods ...
MPC(Model Predictive Control) is representative of control methods which are able to handle physical...
MPC or model predictive control is representative of control methods which are able to handle inequa...
It is well known that exponentially unstable linear systems can not be globally stabilized in the pr...
This paper proposes a framework for dealing with certain classes of nonlinear model predictive contr...
In this paper, a robust MPC for constrained discrete-time nonlinear system with additive uncertainti...
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with...
International audienceThis paper is concerned with stability and recur-sive feasibility of constrain...
We present a method to increase feasibility in MPC algorithms that use ellipsoidal terminal state co...
invariant sets, asymptotic stability. This paper is concerned with the design of stabilizing MPC con...
This paper proposes a parallelizable algorithm for linear-quadratic model predictive control (MPC) p...
In the problem of input-to-state stabilization of nonlinear systems, synthesis of input-to-state sta...
The aim of this paper is to provide new techniques for computing a terminal cost and a local state-f...
The objective of this paper is, on the base of existing results, to provide a general framework for ...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
Research on sub-optimal Model Predictive Control (MPC) has led to a variety of optimization methods ...