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Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
TLDR
In this paper, we present control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint. Expand
  • 1,057
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Dynamic Motion Planning for Mobile Robots Using Potential Field Method
  • S. Ge, Y. Cui
  • Computer Science
  • Auton. Robots
  • 1 November 2002
TLDR
This paper proposes a new potential field method for motion planning of mobile robots in a dynamic environment where the target and the obstacles are moving. Expand
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Adaptive Neural Network Control of Robotic Manipulators
TLDR
Adaptive neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Expand
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Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form
TLDR
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. Expand
  • 586
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Direct adaptive NN control of a class of nonlinear systems
  • S. Ge, C. Wang
  • Mathematics, Computer Science
  • IEEE Trans. Neural Networks
  • 2002
TLDR
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. Expand
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Adaptive neural control of uncertain MIMO nonlinear systems
  • S. Ge, C. Wang
  • Mathematics, Medicine
  • IEEE Transactions on Neural Networks
  • 1 May 2004
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 ofExpand
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Stable Adaptive Neural Network Control
While neural network control has been successfully applied in various practical applications, many important issues, such as stability, robustness, and performance, have not been extensivelyExpand
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An ISS-modular approach for adaptive neural control of pure-feedback systems
TLDR
In this paper, we consider adaptive neural control of a completely non-affine pure-feedback system using radial basis function (RBF) neural networks (NN). Expand
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Adaptive neural network control for strict-feedback nonlinear systems using backstepping design
TLDR
This paper focuses on adaptive control of strict-feedback nonlinear systems using multilayer neural networks (MNNs) using a modified Lyapunov function. Expand
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Adaptive neural control of MIMO nonlinear state time-varying delay systems with unknown dead-zones and gain signs
TLDR
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 nonlinear dead-zones and gain signs. Expand
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