Two approaches to control system design for constrained systems are studied. The first involves theoretical investigations of constrained model predictive control algorithms. The second involves extensions of robust linear control theory to handle the nonlinear control schemes commonly used in practice for constrained systems. A novel model predictive control algorithm, with attractive functional and numerical characteristics is developed. This algorithm minimizes peak excursions in the controlled outputs and is particularly suited to regulatory control problems common in continuous process systems. Model predictive control concepts are extended to uncertain linear systems. An on-line optimizing control scheme (RMPC) is developed whic...
Current applications of nonlinear model predictive control algorithms are restricted to small-scale ...
A robust model predictive control scheme for a class of constrained norm-bounded uncertain discrete-...
This thesis presents a novel approach to robust controller design. It describes how linear constrain...
Most practical control problems are dominated by constraints. Although a rich theory has been develo...
Most practical control problems are dominated by constraints. Although a rich theory has been develo...
Abstract: A new method for the design of predictive controllers for SISO systems is presented. The p...
A new method for the design of predictive controllers for SISO systems is presented. The proposed te...
Abstract: Problem statement: More advanced control techniques have been developed in recent decades ...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
The primary disadvantage of current design techniques for model predictive control (MPC) is their in...
Controlling a system and state constraints is one of the most important problems in control theory, ...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
Research Doctorate - Electrical EngineeringThis thesis studies the use of model predictive control (...
An approach to design feedback controllers for discrete-time, uncertain, linear time-varying systems...
A significant number of Model Predictive Control algorithms solve on-line an appropriate optimizatio...
Current applications of nonlinear model predictive control algorithms are restricted to small-scale ...
A robust model predictive control scheme for a class of constrained norm-bounded uncertain discrete-...
This thesis presents a novel approach to robust controller design. It describes how linear constrain...
Most practical control problems are dominated by constraints. Although a rich theory has been develo...
Most practical control problems are dominated by constraints. Although a rich theory has been develo...
Abstract: A new method for the design of predictive controllers for SISO systems is presented. The p...
A new method for the design of predictive controllers for SISO systems is presented. The proposed te...
Abstract: Problem statement: More advanced control techniques have been developed in recent decades ...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
The primary disadvantage of current design techniques for model predictive control (MPC) is their in...
Controlling a system and state constraints is one of the most important problems in control theory, ...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
Research Doctorate - Electrical EngineeringThis thesis studies the use of model predictive control (...
An approach to design feedback controllers for discrete-time, uncertain, linear time-varying systems...
A significant number of Model Predictive Control algorithms solve on-line an appropriate optimizatio...
Current applications of nonlinear model predictive control algorithms are restricted to small-scale ...
A robust model predictive control scheme for a class of constrained norm-bounded uncertain discrete-...
This thesis presents a novel approach to robust controller design. It describes how linear constrain...