Generalized predictive control—Part I. The basic algorithm
Automatica (Journal of IFAC)
Multilayer feedforward networks are universal approximators
Neural Networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Structured neural networks for constrained model predictive control
Automatica (Journal of IFAC)
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Suboptimal Nonlinear Predictive Control with MIMO Neural Hammerstein Models
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Efficient Predictive Control Integrated with Economic Optimisation Based on Neural Models
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Optimising Predictive Control Based on Neural Models
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Suboptimal Nonlinear Predictive Control Based on Neural Wiener Models
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Efficient Nonlinear Predictive Control Based on Structured Neural Models
International Journal of Applied Mathematics and Computer Science
Training of neural models for predictive control
Neurocomputing
Neural models in computationally efficient predictive control cooperating with economic optimisation
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
A predictive control economic optimiser and constraint governor based on neural models
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Computationally efficient nonlinear predictive control based on RBF neural multi-models
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Dynamic matrix control algorithm based on interpolated step response neural models
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Explicit neural network-based nonlinear predictive control with low computational complexity
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Application of fuzzy Wiener models in efficient MPC algorithms
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Computationally efficient nonlinear predictive control based on state-space neural models
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I
Neural dynamic matrix control algorithm with disturbance compensation
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Numerically efficient analytical MPC algorithm based on fuzzy hammerstein models
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
Nonlinear predictive control based on multivariable neural wiener models
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
Predictive control of a distillation column using a control-oriented neural model
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
Precise and computationally efficient nonlinear predictive control based on neural wiener models
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Nonlinear predictive control based on neural multi-models
International Journal of Applied Mathematics and Computer Science - Computational Intelligence in Modern Control Systems
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Hi-index | 0.00 |
This paper details nonlinear Model-based Predictive Control (MPC) algorithms for MIMO processes modelled by means of neural networks of a feedforward structure. Two general MPC techniques are considered: the one with Nonlinear Optimisation (MPC-NO) and the one with Nonlinear Prediction and Linearisation (MPC-NPL). In the first case a nonlinear optimisation problem is solved in real time on-line. In order to reduce the computational burden, in the second case a neural model of the process is used on-line to determine local linearisation and a nonlinear free trajectory. Single-point and multi-point linearisation methods are discussed. The MPC-NPL structure is far more reliable and less computationally demanding in comparison with the MPC-NO one because it solves a quadratic programming problem, which can be done efficiently within a foreseeable time frame. At the same time, closed-loop performance of both algorithm classes is similar. Finally, a hybrid MPC algorithm with Nonlinear Prediction, Linearisation and Nonlinear optimisation (MPC-NPL-NO) is discussed.