Approximation capabilities of multilayer feedforward networks
Neural Networks
Adaptive nonlinear control without overparametrization
Systems & Control Letters
A robust adaptive nonlinear control design
Automatica (Journal of IFAC)
Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form
Automatica (Journal of IFAC)
Adaptive neural network control for strict-feedback nonlinear systems using backstepping design
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Robust neural-network control of rigid-link electrically driven robots
IEEE Transactions on Neural Networks
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An adaptive neural control approach based on backstepping is presented. Unmodelled dynamics or external disturbances are considered in the nonlinear models. Approximating nonlinear dynamic is one of the performances of multi-layer feedforward neural networks. By the Lyapunov's stability theory, the NN weights are turned on-line with no prior training needed. An important feature of the presented approach is that by modifying a novel quasi-weighted Lyapunov function, the possible control singularity in the design of NN adaptive controller is avoided effectively. Finally, the approach is applied in CSTR system. The simulation result is given to demonstrate the feasibility and effectiveness of the proposed method.