It is well known that exponentially unstable linear systems can not be globally stabilized in the presence of input constraints. In the case where the linear system is neutrally stable, one can achieve global asymptotic stability using a particular Control Lyapunov Function (CLF)-based controller. Using this particular CLF as terminal cost in a receding horizon scheme, we obtain a receding horizon controller which globally stabilizes such systems. Contrary to previous results, the horizon length is fixed, and can be chosen arbitrarily. The resulting controller also outperforms the CLF controller, since it provides a lower cost as measured by a quadratic performance index.
This paper proposes a static (LQR) plus a dynamic compensation scheme for input magnitude and rate c...
MPC or model predictive control is representative of control methods which are able to handle inequa...
Abstract: The problem of stabilizing constrained nonlinear systems meanwhile optimizing some perform...
It is well known that exponentially unstable linear systems can not be globally stabilized in the pr...
It is well known that unconstrained infinite-horizon optimal control may be used to construct a stab...
This paper addresses the issue of region of attraction of stabilizing receding horizon control stra...
This paper focus on the stability of receding horizon control of general nonlinear systems. We emplo...
Abstract: Recent results on receding horizon control of linear systems with state and input constrai...
This paper deals with unconstrained receding horizon control of nonlinear systems with a general, no...
Almost all proposed approaches to nonlinear receding horizon control with guaranteed stability are b...
It is well known that unconstrained infinite-horizon optimal control may be used to construct a stab...
Feedback stabilization of systems subject to constraints has been a long-standing problem in control...
In this technical note, we present a Receding Horizon Control (RHC) design method for linear paramet...
Receding horizon control has recently been used for regulating discrete-time Piecewise Affine (PWA) ...
This paper focus on the stabilizing properties of stationary feedback controls for general nonlinear...
This paper proposes a static (LQR) plus a dynamic compensation scheme for input magnitude and rate c...
MPC or model predictive control is representative of control methods which are able to handle inequa...
Abstract: The problem of stabilizing constrained nonlinear systems meanwhile optimizing some perform...
It is well known that exponentially unstable linear systems can not be globally stabilized in the pr...
It is well known that unconstrained infinite-horizon optimal control may be used to construct a stab...
This paper addresses the issue of region of attraction of stabilizing receding horizon control stra...
This paper focus on the stability of receding horizon control of general nonlinear systems. We emplo...
Abstract: Recent results on receding horizon control of linear systems with state and input constrai...
This paper deals with unconstrained receding horizon control of nonlinear systems with a general, no...
Almost all proposed approaches to nonlinear receding horizon control with guaranteed stability are b...
It is well known that unconstrained infinite-horizon optimal control may be used to construct a stab...
Feedback stabilization of systems subject to constraints has been a long-standing problem in control...
In this technical note, we present a Receding Horizon Control (RHC) design method for linear paramet...
Receding horizon control has recently been used for regulating discrete-time Piecewise Affine (PWA) ...
This paper focus on the stabilizing properties of stationary feedback controls for general nonlinear...
This paper proposes a static (LQR) plus a dynamic compensation scheme for input magnitude and rate c...
MPC or model predictive control is representative of control methods which are able to handle inequa...
Abstract: The problem of stabilizing constrained nonlinear systems meanwhile optimizing some perform...