H∞ tracking of uncertain SISO nonlinear systems: an observer-based adaptive fuzzy approach
International Journal of Systems Science
Backstepping Control of Uncertain Time Delay Systems Based on Neural Network
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Adaptive Control for a Class of Nonlinear Time-Delay Systems Using RBF Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Robust Adaptive Neural Network Control for a Class of Nonlinear Systems with Uncertainties
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Preventing bursting in approximate-adaptive control when using local basis functions
Fuzzy Sets and Systems
Fuzzy adaptive backstepping robust control for SISO nonlinear system with dynamic uncertainties
Information Sciences: an International Journal
Brief paper: Hybrid-based adaptive NN backstepping control of strict-feedback systems
Automatica (Journal of IFAC)
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
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Multiobjective algebraic synthesis of neural control systems by implicit model following
IEEE Transactions on Neural Networks
Adaptive neural control for strict-feedback nonlinear systems without backstepping
IEEE Transactions on Neural Networks
An observer-based neural networks control scheme for nonlinear systems
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Adaptive backstepping sliding mode control for nonlinear systems with neural networks
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
IEEE Transactions on Neural Networks
A new robust weight update for multilayer-perceptron adaptive control
Control and Intelligent Systems
Analysis of mixed inflammable gases based on single sensor and RBF neural network
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Improved Output Tracking of a Flexible-Joint Arm using Neural Networks
Neural Processing Letters
Fast forward RBF network construction based on particle swarm optimization
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part II
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Radial basis function neural network based approach to test oracle
ACM SIGSOFT Software Engineering Notes
Adaptive dynamic RBF neural controller design for a class of nonlinear systems
Applied Soft Computing
Implementable adaptive backstepping neural control of uncertain strict-feedback nonlinear systems
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Robust and adaptive backstepping control for nonlinear systems using fuzzy logic systems
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
A novel training algorithm for RBF neural network using a hybrid fuzzy clustering approach
Fuzzy Sets and Systems
Robust adaptive control scheme using hopfield dynamic neural network for nonlinear nonaffine systems
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Sliding mode control for uncertain nonlinear systems using RBF neural networks
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Decentralized discrete-time neural control for a Quanser 2-DOF helicopter
Applied Soft Computing
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
| Hi-index | 0.01 |
In this paper, two different backstepping neural network (NN) control approaches are presented for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. By a special design scheme, the controller singularity problem is avoided perfectly in both approaches. Furthermore, the closed loop signals are guaranteed to be semiglobally uniformly ultimately bounded and the outputs of the system are proved to converge to a small neighborhood of the desired trajectory. The control performances of the closed-loop systems can be shaped as desired by suitably choosing the design parameters. Simulation results obtained demonstrate the effectiveness of the approaches proposed. The differences observed between the inputs of the two controllers are analyzed briefly.