Fuzzy system modeling by fuzzy partition and GA hybrid schemes
Fuzzy Sets and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Fuzzy systems with defuzzification are universal approximators
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid clustering and gradient descent approach for fuzzymodeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Design of fuzzy systems using neurofuzzy networks
IEEE Transactions on Neural Networks
Adaptive fuzzy systems for backing up a truck-and-trailer
IEEE Transactions on Neural Networks
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
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Truck backer-upper problem is a typical benchmark for many control methods in nonlinear system identification. In this paper, first, the traditional fuzzy control system is studied for the truck backer-upper problem, and then the fuzzy control system based on a hybrid clustering method and neural network is presented. The clustering method is proposed to construct an initial fuzzy model to determine the number of fuzzy rules from the intuitionistic-desired trajectories. Neural network is used to train the parameters of the constructed fuzzy model (neural-fuzzy system). Compared with traditional fuzzy system, this neural-fuzzy controller demonstrates advantages not only on the control performance but also on its convenience and feasibility.