Adapting Self-Adaptive Parameters in Evolutionary Algorithms
Applied Intelligence
A Knowledge Discovery System with Support for Model Selection and Visualization
Applied Intelligence
A Fuzzy Integral Based Query Dispatching Model in Collaborative Case-Based Reasoning
Applied Intelligence
A Prioritized Information Fusion Method for Handling Fuzzy Decision-Making Problems
Applied Intelligence
A QoS-Tunable Scheme for ATM Cell Scheduling Using Evolutionary Fuzzy System
Applied Intelligence
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Adaptive Multi-Model CMAC-Based Supervisory Control for Uncertain MIMO Systems
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
A novel fuzzy compensation multi-class support vector machine
Applied Intelligence
Fuzzy multiple modeling and fuzzy predictive control of a tubular heat exchanger system
AEE'08 Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering
Multiple modeling and fuzzy predictive control of a tubular heat exchanger system
WSEAS Transactions on Systems and Control
Non Linear Process Identification Using a Neural Network Based Multiple Models Generator
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
Data driven multiple neural network models generator based on a tree-like scheduler
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Model predictive control using fuzzy decision functions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Predictive functional control based on fuzzy model for heat-exchanger pilot plant
IEEE Transactions on Fuzzy Systems
Fuzzy predictive control of a solar power plant
IEEE Transactions on Fuzzy Systems
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This work deals with the problem of controlling the outlet temperature of a tubular heat exchanger system by means of flow pressure. The usual industrial case is to try to control the outlet temperature by either the temperature or the flow of the fluid, which flows through the shell tube. But, in some situations, this is not possible, due to the fact that the whole of system coefficients variation cannot quite be covered by control action. In this case, the system behavior must precisely be modeled and appropriate control action needs to be obtained based on novel techniques. A new multiple models control strategy using the well-known linear generalized predictive control (LGPC) scheme has been proposed, in this paper. The main idea of the proposed control strategy is to represent the operating environments of the system, which have a wide range of variation with respect to time by multiple explicit linear models. In this strategy, the best model of the system is accurately identified, at each instant of time, by an intelligent decision mechanism (IDM), which is organized based on both new recursive weight generator and fuzzy adaptive Kalman filter approaches. After that, the adaptive algorithm is implemented on the chosen model. Finally, for having a good tracking performance, the generalized predictive control is instantly updated and its control action is also applied to the system. For demonstrating the effectiveness of the proposed approach, simulations are all done and the results are also compared with those obtained using a nonlinear GPC (NLGPC) approach that is realized based on the Wiener model of the system. The results can verify the validity of the proposed control scheme.