Abstract: The performance of a predictive controller is typically poor when the true plant evolution deviates significantly from that predicted by the model. A robust control approach that considers model uncertainty explicitly is then needed. However, it is often difficult to find a single input profile that works well for the range of uncertainty considered. Thus, multiple input profiles, i.e. one for each realization of the uncertainty, need to be determined. Unfortunately, this is computationally extremely expensive. This paper proposes an alternative approach that is based on neighboring extremals, where the multiple input profiles are computed using a simple feedback law, thereby reducing considerably the computational burden. The ide...
Current applications of nonlinear model predictive control algorithms are restricted to small-scale ...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time...
The performance of a predictive controller is typically poor when the true plant evolution deviates ...
A powerful approach for dynamic optimization in the presence of uncertainty is to incorporate measur...
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...
A new method of designing predictive controllers for SISO systems is presented. The controller selec...
Concerning the robust model predictive control (MPC) for constrained systems with polytopic model ch...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
In this paper, we present a new technique to address constrained robust model predictive control. Th...
A model-based robust controller is designed for a packed bed methanation reactor. To accomplish thi...
In this paper a new robust Modelbased Predictive Control (MPC) algorithm for linear models with poly...
For the first time, a textbook that brings together classical predictive control with treatment of u...
This thesis introduces a new interpretation of the problems arising in robust model predictive contr...
Current applications of nonlinear model predictive control algorithms are restricted to small-scale ...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time...
The performance of a predictive controller is typically poor when the true plant evolution deviates ...
A powerful approach for dynamic optimization in the presence of uncertainty is to incorporate measur...
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...
A new method of designing predictive controllers for SISO systems is presented. The controller selec...
Concerning the robust model predictive control (MPC) for constrained systems with polytopic model ch...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
In this paper, we present a new technique to address constrained robust model predictive control. Th...
A model-based robust controller is designed for a packed bed methanation reactor. To accomplish thi...
In this paper a new robust Modelbased Predictive Control (MPC) algorithm for linear models with poly...
For the first time, a textbook that brings together classical predictive control with treatment of u...
This thesis introduces a new interpretation of the problems arising in robust model predictive contr...
Current applications of nonlinear model predictive control algorithms are restricted to small-scale ...
Model Predictive Control (MPC) has become one of the dominant methods of chemical process control in...
This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time...