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- Yunong Zhang, Zhiguo Tan, Ke Chen, Zhi Yang, Xuanjiao Lv
- Robotics and Autonomous Systems
- 2009

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: Keywords: Neural networks Four-link planar robot manipulator Joint physical limits… (More)

- Yunong Zhang, Ning Tan
- 2015

- Yunong Zhang, Zhiguo Tan, Zhi Yang, Xuanjiao Lv, Ke Chen
- 2008 IEEE International Joint Conference on…
- 2008

This paper presents a simplified primal-dual neural network based on linear variational inequalities (LVI) for online repetitive motion planning of PA10 robot manipulator. To do this, a drift-free criterion is exploited in the form of a quadratic function. In addition, the repetitive-motion-planning scheme could incorporate the joint limits and joint… (More)

- Yunong Zhang, Danchi Jiang, Jun Wang
- IEEE Trans. Neural Networks
- 2002

Presents a recurrent neural network for solving the Sylvester equation with time-varying coefficient matrices. The recurrent neural network with implicit dynamics is deliberately developed in the way that its trajectory is guaranteed to converge exponentially to the time-varying solution of a given Sylvester equation. Theoretical results of convergence and… (More)

- Yunong Zhang, Shuzhi Sam Ge
- IEEE Transactions on Neural Networks
- 2005

Following the idea of using first-order time derivatives, this paper presents a general recurrent neural network (RNN) model for online inversion of time-varying matrices. Different kinds of activation functions are investigated to guarantee the global exponential convergence of the neural model to the exact inverse of a given time-varying matrix. The… (More)

- Yunong Zhang, Jun Wang
- 2001

A recurrent neural network called the dual neural network is proposed in this Letter for solving the strictly convex quadratic programming problems. Compared to other recurrent neural networks, the proposed dual network with fewer neurons can solve quadratic programming problems subject to equality, inequality, and bound constraints. The dual neural network… (More)

- Yunong Zhang, Jun Wang, Youshen Xia
- IEEE Trans. Neural Networks
- 2003

In this paper, a recurrent neural network called the dual neural network is proposed for online redundancy resolution of kinematically redundant manipulators. Physical constraints such as joint limits and joint velocity limits, together with the drift-free criterion as a secondary task, are incorporated into the problem formulation of redundancy resolution.… (More)

- Yunong Zhang, Jun Wang
- IEEE transactions on systems, man, and…
- 2004

One important issue in the motion planning and control of kinematically redundant manipulators is the obstacle avoidance. In this paper, a recurrent neural network is developed and applied for kinematic control of redundant manipulators with obstacle avoidance capability. An improved problem formulation is proposed in the sense that the collision-avoidance… (More)

- Yunong Zhang, Shuzhi Sam Ge, Tong Heng Lee
- IEEE Trans. Systems, Man, and Cybernetics, Part B
- 2004

In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints. To solve this QP problem online, a primal-dual dynamical… (More)

- Yunong Zhang, Jun Wang
- IEEE Trans. Neural Networks
- 2002

Global exponential stability is the most desirable stability property of recurrent neural networks. The paper presents new results for recurrent neural networks applied to online computation of feedback gains of linear time-invariant multivariable systems via pole assignment. The theoretical analysis focuses on the global exponential stability, convergence… (More)