Abstract This paper presents the State Partition based Mixed Logical Dynamical (SPMLD) formalism as a new modeling technique for a class of discrete-time hybrid systems, where the system is defined by different modes with continuous and logical control inputs and state variables, each model subject to linear constraints. The reformulation of the predictive strategy for hybrid systems under the SPMLD approach is then developed. This technique enables to considerably reduce the computation time (with respect to the classical MPC approaches for PWA and MLD models), as a positive feature for real time implementation. This strategy is applied in simulation to the control of a three tanks benchmark.
ii Hybrid systems combine the continuous behavior evolution specified by differential equations with...
Hybrid systems are dynamical systems whose behavior is determined by the interaction of continuous a...
Abstract This paper proposes an approach for reducing the computational com-plexity of a model-predi...
This paper deals with Mixed LogicalDynamical (MLD) approach. It allows to model the hybridsystems in...
Mixed Logical Dynamical (MLD) systems are introduced as a new system type. The MLD form is capable t...
Mixed Logical Dynamical (MLD) systems are introduced as a new system type. The MLD form is capable ...
This paper proposes a framework for modeling and controlling systems described by interdependent phy...
The paper discusses a framework for modeling, analyzing and controlling systems whose behavior is go...
This paper proposes a framework for modeling and controlling systems described by interdependent phy...
In this paper, to reduce the computation time for solving the finite-time optimal control problem (i...
ABSTRACT: The Mixed Logical Dynamical (MLD) formalism has proved to be an efficient modelling framew...
The paper discusses a framework for modeling, analyzing and controlling systems whose behavior is go...
In this paper, we propose a new modeling method to express discrete-time hybrid systems with paramet...
In many applications, the control objectives and constraints can be assigned a hierarchy of levels o...
In this paper we investigate the use of model predictive control (MPC) as a means for controlling a ...
ii Hybrid systems combine the continuous behavior evolution specified by differential equations with...
Hybrid systems are dynamical systems whose behavior is determined by the interaction of continuous a...
Abstract This paper proposes an approach for reducing the computational com-plexity of a model-predi...
This paper deals with Mixed LogicalDynamical (MLD) approach. It allows to model the hybridsystems in...
Mixed Logical Dynamical (MLD) systems are introduced as a new system type. The MLD form is capable t...
Mixed Logical Dynamical (MLD) systems are introduced as a new system type. The MLD form is capable ...
This paper proposes a framework for modeling and controlling systems described by interdependent phy...
The paper discusses a framework for modeling, analyzing and controlling systems whose behavior is go...
This paper proposes a framework for modeling and controlling systems described by interdependent phy...
In this paper, to reduce the computation time for solving the finite-time optimal control problem (i...
ABSTRACT: The Mixed Logical Dynamical (MLD) formalism has proved to be an efficient modelling framew...
The paper discusses a framework for modeling, analyzing and controlling systems whose behavior is go...
In this paper, we propose a new modeling method to express discrete-time hybrid systems with paramet...
In many applications, the control objectives and constraints can be assigned a hierarchy of levels o...
In this paper we investigate the use of model predictive control (MPC) as a means for controlling a ...
ii Hybrid systems combine the continuous behavior evolution specified by differential equations with...
Hybrid systems are dynamical systems whose behavior is determined by the interaction of continuous a...
Abstract This paper proposes an approach for reducing the computational com-plexity of a model-predi...