A parameter estimation perspective of continuous time model reference adaptive control
Automatica (Journal of IFAC)
Convergent activation dynamics in continuous time networks
Neural Networks
Approximation capabilities of multilayer feedforward networks
Neural Networks
Universal approximation using radial-basis-function networks
Neural Computation
Neural networks for control systems: a survey
Automatica (Journal of IFAC)
Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form
Automatica (Journal of IFAC)
CMAC neural networks for control of nonlinear dynamical systems: structure, stability and passivity
Automatica (Journal of IFAC)
Adaptive robust control of MIMO nonlinear systems in semi-strict feedback forms
Automatica (Journal of IFAC)
Gaussian networks for direct adaptive control
IEEE Transactions on Neural Networks
Neural net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
International Journal of Systems Science
Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Adaptive neural control for strict-feedback nonlinear systems without backstepping
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Indirect sliding mode neural-network control for holonomic constrained robot manipulators
International Journal of Intelligent Systems Technologies and Applications
Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints
Automatica (Journal of IFAC)
Adaptive neural compensation control for input-delay nonlinear systems by passive approach
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Engineering Applications of Artificial Intelligence
Hi-index | 22.15 |
Neural network adaptive robust control (ARC) design is generalized to synthesize performance oriented control laws for a class of nonlinear systems in semi-strict feedback forms through the incorporation of backstepping design techniques.