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Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
In this paper, we present control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint. To prevent constraint violation, we employ a… Expand
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
The potential field method is widely used for autonomous mobile robot path planning due to its elegant mathematical analysis and simplicity. However, most researches have been focused on solving the… Expand
Adaptive Neural Network Control of Robotic Manipulators
There has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of… Expand
Direct adaptive NN control of a class of nonlinear systems
In this paper, direct adaptive neural-network (NN) control is presented for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. By utilizing a special… Expand
Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form
In this paper, adaptive dynamic surface control (DSC) is developed for a class of pure-feedback nonlinear systems with unknown dead zone and perturbed uncertainties using neural networks. The… Expand
Adaptive neural control of uncertain MIMO nonlinear systems
In this paper, adaptive neural control schemes are proposed for two classes of uncertain multi-input/multi-output (MIMO) nonlinear systems in block-triangular forms. The MIMO systems consist of… Expand
Stable Adaptive Neural Network Control
- S. Ge, C. Hang, T. Lee, T. Zhang
- Engineering
- The Springer International Series on Asian…
- 30 November 2001
While neural network control has been successfully applied in various practical applications, many important issues, such as stability, robustness, and performance, have not been extensively… Expand
Adaptive neural network control for strict-feedback nonlinear systems using backstepping design
This paper focuses on adaptive control of strict-feedback nonlinear systems using multilayer neural networks (MNNs). By introducing a modified Lyapunov function, a smooth and singularity-free… Expand
An ISS-modular approach for adaptive neural control of pure-feedback systems
Controlling non-affine non-linear systems is a challenging problem in control theory. In this paper, we consider adaptive neural control of a completely non-affine pure-feedback system using radial… Expand
Adaptive neural control of MIMO nonlinear state time-varying delay systems with unknown dead-zones and gain signs
In this paper, adaptive neural control is proposed for a class of uncertain multi-input multi-output (MIMO) nonlinear state time-varying delay systems in a triangular control structure with unknown… Expand