Abstract — In this paper, an enhanced event-based scheme for model predictive control (MPC) of constrained discrete-time systems with additive disturbances is investigated. The re/calculation of the MPC control law is triggered whenever an event depending on the error of the measured state with respect to the nominal state of the system occurs. Between the controller updates, the last computed control trajectory is applied to the system, in conjunction with a correction term. This term consists of a perturbation solution of the nominal system which itself depends on the aforementioned error. The overall framework yields less conservative results with respect to our previous work. The results are illustrated through a simulated example. I
A robust model predictive control (MPC) method is presented for linear, time-invariant systems affec...
We propose a robust event-triggered model predictive control (MPC) scheme for linear time-invariant ...
Abstract — This paper presents an approach to event-triggered model predictive control for discrete-...
In this master thesis we propose an aperiodic formulation of Model Predictive Control for distribute...
Abstract: In this paper, novel event-triggered strategies for the design of model predictive (MPC) c...
This paper proposes a new control parametrization under the Model Predictive Control frame-work for ...
This paper proposes a feedback model predictive control (MPC) strategy for linear time invariant dis...
Abstract A quasi‐differential type event‐triggered model predictive control (ET‐MPC) framework for c...
This paper considers the problem of event-triggered decentralized model predictive control (MPC) for...
Adaptive control for constrained, linear systems is addressed and a solution based on Model Predicti...
Abstract — This paper proposes novel event-triggered strate-gies for the control of uncertain nonlin...
This paper proposes a robust self-triggered modelpredictive control (MPC) with an adaptive predictio...
We propose a robust event-triggered model predictive control (MPC) scheme for linear time-invariant ...
In this paper, we propose an event-based sampling policy to implement a constraint-tightening, robus...
A new real time stability constraint for model predictive control is developed in this paper. Motiva...
A robust model predictive control (MPC) method is presented for linear, time-invariant systems affec...
We propose a robust event-triggered model predictive control (MPC) scheme for linear time-invariant ...
Abstract — This paper presents an approach to event-triggered model predictive control for discrete-...
In this master thesis we propose an aperiodic formulation of Model Predictive Control for distribute...
Abstract: In this paper, novel event-triggered strategies for the design of model predictive (MPC) c...
This paper proposes a new control parametrization under the Model Predictive Control frame-work for ...
This paper proposes a feedback model predictive control (MPC) strategy for linear time invariant dis...
Abstract A quasi‐differential type event‐triggered model predictive control (ET‐MPC) framework for c...
This paper considers the problem of event-triggered decentralized model predictive control (MPC) for...
Adaptive control for constrained, linear systems is addressed and a solution based on Model Predicti...
Abstract — This paper proposes novel event-triggered strate-gies for the control of uncertain nonlin...
This paper proposes a robust self-triggered modelpredictive control (MPC) with an adaptive predictio...
We propose a robust event-triggered model predictive control (MPC) scheme for linear time-invariant ...
In this paper, we propose an event-based sampling policy to implement a constraint-tightening, robus...
A new real time stability constraint for model predictive control is developed in this paper. Motiva...
A robust model predictive control (MPC) method is presented for linear, time-invariant systems affec...
We propose a robust event-triggered model predictive control (MPC) scheme for linear time-invariant ...
Abstract — This paper presents an approach to event-triggered model predictive control for discrete-...