Approximation of stable systems by laguerre filters
Automatica (Journal of IFAC)
Estimation of parameter bounds from bounded-error data: a survey
Mathematics and Computers in Simulation - Parameter identifications with error bound
On linear programming and robust modelpredictive control using impulse-responses
Systems & Control Letters
On approximation of stable linear dynamical systems using Laguerre and Kautz functions
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Neural networks and genetic algorithms for robust predictive controller
ACMOS'06 Proceedings of the 8th WSEAS international conference on Automatic control, modeling & simulation
Brief Optimal expansions of discrete-time Volterra models using Laguerre functions
Automatica (Journal of IFAC)
| Hi-index | 22.15 |
The present work focuses on robust predictive control (RPC) of uncertain processes and proposes a new approach based on orthonormal series function modeling. In such unstructured modeling, the output signal is described as a weighted sum of orthonormal functions that uses approximative information about the time constant of the process. Due to an efficient uncertainty representation, this kind of modeling is advantageous in the RPC context, even for constrained systems and processes with integral action. The stability of the closed-loop system is guaranteed by the setting of sufficient conditions for the selection of the controller prediction horizon. Simulation results are presented to illustrate the performance of this new RPC algorithm.