© IFAC. In this paper we propose a novel quadratic model predictive control technique that constrains the number of active inputs at each control horizon instant. This problem is known as sparse control. We use an iterative convex optimization procedure to solve the corresponding optimization problem subject to sparsity constraints defined by means of the ℓ0-norm. We also derive a sufficient condition on the minimum number of active of inputs that guarantees the exponential stability of the closed-loop system. A simulation example illustrates the benefits of the control design method proposed in the paper
We study stability of Model Predictive Control (MPC) with a quadratic cost function for LTI systems ...
A key component in enabling the application of model predictive control (MPC) in fields such as auto...
The flexibility and simplicity of recently published first-order methods (often first proposed for i...
In this paper we propose a novel quadratic model predictive control technique that constrains the nu...
© 2017 IEEE. This note addresses the problem of feedback control with a constrained number of active...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
International audienceA technique is presented to solve the linear quadraticoptimal control problem ...
We consider the problem of constructing optimal sparse controllers. It is known that a property call...
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with...
We propose an algorithm for the effective solution of quadratic programming (QP) problems arising fr...
Simulations for the quadratically-constrained model predictive control (qc-MPC) with power system li...
An active set algorithm tailored to quadratically constrained quadratic programming in model predict...
This paper deals with direct data-driven design of model-reference controllers whose number of param...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
This article is concerned with the approximation of constrained continuous-time linear quadratic reg...
We study stability of Model Predictive Control (MPC) with a quadratic cost function for LTI systems ...
A key component in enabling the application of model predictive control (MPC) in fields such as auto...
The flexibility and simplicity of recently published first-order methods (often first proposed for i...
In this paper we propose a novel quadratic model predictive control technique that constrains the nu...
© 2017 IEEE. This note addresses the problem of feedback control with a constrained number of active...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
International audienceA technique is presented to solve the linear quadraticoptimal control problem ...
We consider the problem of constructing optimal sparse controllers. It is known that a property call...
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with...
We propose an algorithm for the effective solution of quadratic programming (QP) problems arising fr...
Simulations for the quadratically-constrained model predictive control (qc-MPC) with power system li...
An active set algorithm tailored to quadratically constrained quadratic programming in model predict...
This paper deals with direct data-driven design of model-reference controllers whose number of param...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
This article is concerned with the approximation of constrained continuous-time linear quadratic reg...
We study stability of Model Predictive Control (MPC) with a quadratic cost function for LTI systems ...
A key component in enabling the application of model predictive control (MPC) in fields such as auto...
The flexibility and simplicity of recently published first-order methods (often first proposed for i...