Add to ORKGWe present a method of performing optimal input design on a process controlled by MPC. Given a model structure and a measure of control performance degradation, the method provides an optimal input signal to be used in the identification experiment
Model-based control design plays a key role in today's industrial practice, and industry demands cut...
Abstract: In this paper we briefly review the evolution of the main tools and results for optimal ex...
The problem of designing identification experiments to make them maximally informative with respect ...
Abstract — This paper considers a method for optimal input design in system identification for contr...
Modern control designs are, with few exceptions, in some way model based. In particular, predictive ...
A combined nonlinear model predictive control with extended Kalman filter strategy has been proposed...
In control engineering, system identification is frequently used to create models from inputoutput d...
This paper considers optimal input design when the intended use of the identified model is to constr...
Model predictive control (MPC) makes use of a model of the system, therefore performances are highly...
The model predictive control (MPC) technique has been widely applied in a large number of industrial...
There are many aspects to consider when designing system identification experiments in control appli...
Abstract Presented in this chapter is a tutorial on the design of input signals for system identific...
Abstract — This contribution considers one central aspect of experiment design in system identificat...
It is well known that the quality of the parameters identified during an identification experiment d...
International audienceIt is well known that the quality of the parameters identified during an ident...
Model-based control design plays a key role in today's industrial practice, and industry demands cut...
Abstract: In this paper we briefly review the evolution of the main tools and results for optimal ex...
The problem of designing identification experiments to make them maximally informative with respect ...
Abstract — This paper considers a method for optimal input design in system identification for contr...
Modern control designs are, with few exceptions, in some way model based. In particular, predictive ...
A combined nonlinear model predictive control with extended Kalman filter strategy has been proposed...
In control engineering, system identification is frequently used to create models from inputoutput d...
This paper considers optimal input design when the intended use of the identified model is to constr...
Model predictive control (MPC) makes use of a model of the system, therefore performances are highly...
The model predictive control (MPC) technique has been widely applied in a large number of industrial...
There are many aspects to consider when designing system identification experiments in control appli...
Abstract Presented in this chapter is a tutorial on the design of input signals for system identific...
Abstract — This contribution considers one central aspect of experiment design in system identificat...
It is well known that the quality of the parameters identified during an identification experiment d...
International audienceIt is well known that the quality of the parameters identified during an ident...
Model-based control design plays a key role in today's industrial practice, and industry demands cut...
Abstract: In this paper we briefly review the evolution of the main tools and results for optimal ex...
The problem of designing identification experiments to make them maximally informative with respect ...