Journal ArticleDOI
Adaptive Neural Output Feedback Controller Design With Reduced-Order Observer for a Class of Uncertain Nonlinear SISO Systems
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TLDR
An adaptive output feedback controller is constructively developed for uncertain nonlinear single-input-single-output systems with partial unmeasured states by employing radial basis function neural networks and incorporating the ROO into a new backstepping design.Abstract:
An adaptive output feedback control is studied for uncertain nonlinear single-input-single-output systems with partial unmeasured states. In the scheme, a reduced-order observer (ROO) is designed to estimate those unmeasured states. By employing radial basis function neural networks and incorporating the ROO into a new backstepping design, an adaptive output feedback controller is constructively developed. A prominent advantage is its ability to balance the control action between the state feedback and the output feedback. In addition, the scheme can be still implemented when all the states are not available. The stability of the closed-loop system is guaranteed in the sense that all the signals are semiglobal uniformly ultimately bounded and the system output tracks the reference signal to a bounded compact set. A simulation example is given to validate the effectiveness of the proposed scheme.read more
Citations
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Journal ArticleDOI
Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints
Wei He,Yuhao Chen,Zhao Yin +2 more
TL;DR: Adaptive neural network control for the robotic system with full-state constraints is designed, and the adaptive NNs are adopted to handle system uncertainties and disturbances.
Journal ArticleDOI
Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation
Wei He,Yiting Dong,Changyin Sun +2 more
TL;DR: In this article, an adaptive impedance controller for a robotic manipulator with input saturation was developed by employing neural networks. But the adaptive impedance control was not considered in the tracking control design, and the input saturation is handled by designing an auxiliary system.
Journal ArticleDOI
Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks
TL;DR: It is proved that the proposed adaptive neural network (NN) consensus control method guarantees the convergence on the basis of Lyapunov stability theory.
Journal ArticleDOI
Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems
TL;DR: An observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form.
Journal ArticleDOI
Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints
TL;DR: In order to stabilize a class of uncertain nonlinear strict-feedback systems with full-state constraints, an adaptive neural network control method is investigated and it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded and the output is well driven to follow the desired output.
References
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Universal approximation using radial-basis-function networks
Jooyoung Park,Irwin W. Sandberg +1 more
TL;DR: It is proved thatRBF networks having one hidden layer are capable of universal approximation, and a certain class of RBF networks with the same smoothing factor in each kernel node is broad enough for universal approximation.
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An introduction to observers
TL;DR: In this paper, the identity observer, a reduced-order observer, linear functional observers, stability properties, and dual observers are discussed, along with the special topics of identity observer and reduced order observer.
Journal ArticleDOI
A hierarchical neural-network model for control and learning of voluntary movement
TL;DR: A hierarchical neural network model which accounts for the learning and control capability of the CNS and provides a promising parallel-distributed control scheme for a large-scale complex object whose dynamics are only partially known is proposed.
Journal ArticleDOI
Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form
TL;DR: A backstepping based control design for a class of nonlinear systems in strict-feedback form with arbitrary uncertainty is developed and is able to eliminate the problem of "explosion of complexity" inherent in the existing method.
Journal ArticleDOI
Climbing fibre induced depression of both mossy fibre responsiveness and glutamate sensitivity of cerebellar Purkinje cells
TL;DR: In high decerebrate rabbits, cells were sampled extracellularly from the rostral flocculus and basket cells were identified based on the absence of olivary responses and also on their location in the molecular layer adjacent to identified Purkinje cells.