Neural networks for control
Neurofuzzy adaptive modelling and control
Neurofuzzy adaptive modelling and control
Neural network based control schemes for flexible-link manipulators: simulations and experiments
Neural Networks - Special issue on neural control and robotics: biology and technology
Autonomous of control of complex systems: robotic applications
Applied Mathematics and Computation
Fuzzy and Neural Approaches in Engineering
Fuzzy and Neural Approaches in Engineering
Neuro-Control and Its Applications
Neuro-Control and Its Applications
Journal of Intelligent and Robotic Systems
Neuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators
Fuzzy Sets and Systems - Special issue: Fuzzy set techniques for intelligent robotic systems
Design and tuning of importance-based fuzzy logic controller for a flexible-link manipulator
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Journal of Intelligent and Robotic Systems
A neurofuzzy controller for a single link flexible manipulator
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Constrained motion control of flexible robot manipulators based on recurrent neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
Radial basis function neural network-based adaptive critic control of induction motors
Applied Soft Computing
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The paper describes use of soft computing methods (fuzzy logic and neural network techniques) in the development of a hybrid fuzzy neural control (HFNC) scheme for a multi-link flexible manipulator. A manipulator with multiple flexible links is a multivariable system of considerable complexity due to the inter-link coupling effects that are present in both rigid and flexible motions. Modelling and controlling the dynamics of such manipulators is therefore difficult. The proposed HFNC scheme generates control actions combining contributions form both a fuzzy controller and a neural controller. The primary loop of the proposed HFNC contains a fuzzy controller and a neural network controller in the secondary loop to compensate for the coupling effects due to the rigid and flexible motion along with the inter-link coupling. It has been ascertained from the present investigation that the proposed soft-computing-based controller works effectively in the tracking control of such a multi-link flexible manipulator. The results are extendable to other multivariable systems of similar complexity.