Hybrid compensation control for affine TSK fuzzy control systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An improved stability criterion for T-S fuzzy discrete systems via vertex expression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy model-based control of complex plants
IEEE Transactions on Fuzzy Systems
Robustness design of nonlinear dynamic systems via fuzzy linear control
IEEE Transactions on Fuzzy Systems
Analysis and synthesis of nonlinear time-delay systems via fuzzy control approach
IEEE Transactions on Fuzzy Systems
Mixed H2/H∞ fuzzy output feedback control design for nonlinear dynamic systems: an LMI approach
IEEE Transactions on Fuzzy Systems
Robust H∞ disturbance attenuation for a class of uncertain discrete-time fuzzy systems
IEEE Transactions on Fuzzy Systems
Output feedback robust H∞ control of uncertain fuzzy dynamic systems with time-varying delay
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A multiple Lyapunov function approach to stabilization of fuzzy control systems
IEEE Transactions on Fuzzy Systems
Hybrid fuzzy control of robotics systems
IEEE Transactions on Fuzzy Systems
LMI-based Integral fuzzy control of DC-DC converters
IEEE Transactions on Fuzzy Systems
Evolution of a Negative-Rule Fuzzy Obstacle Avoidance Controller for an Autonomous Vehicle
IEEE Transactions on Fuzzy Systems
Quick Design of Fuzzy Controllers With Good Interpretability in Mobile Robotics
IEEE Transactions on Fuzzy Systems
Averaging of nonsmooth systems using dither
Automatica (Journal of IFAC)
Neural network-based control design: an LMI approach
IEEE Transactions on Neural Networks
Tuning the structure and parameters of a neural network by using hybrid Taguchi-genetic algorithm
IEEE Transactions on Neural Networks
Design of Asymptotic Estimators: An Approach Based on Neural Networks and Nonlinear Programming
IEEE Transactions on Neural Networks
Multifeedback-Layer Neural Network
IEEE Transactions on Neural Networks
Hi-index | 0.21 |
This study presents a robustness design of fuzzy control for nonlinear systems with multiple time delays. First, the neural-network (NN) model is employed to approximate the nonlinear multiple time-delay (NMTD) plant. Then, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. According to the LDI state-space representation, a robustness design of fuzzy control is proposed to overcome the effect of modeling errors between the NMTD plant and the NN model. If the designed fuzzy controller cannot stabilize the NMTD system, a dither, as an auxiliary of the fuzzy controller, is simultaneously introduced to stabilize the NMTD system. Based on the relaxed method, the NMTD system can be stabilized by regulating appropriately the parameters of dither. If the frequency of dither is high enough, the trajectory of the dithered system and that of its corresponding mathematical model-the relaxed system can be made as close as desired. This fact enables us to get a rigorous prediction of stability of the dithered system by establishing the stability of the relaxed system.