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Taylor O(h³) Discretization of ZNN Models for Dynamic Equality-Constrained Quadratic Programming With Application to Manipulators

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING systems 2016年第2期27卷 225-237页

作者： Liao, Bolin Zhang, Yunong Jin, Long Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China Jishou Univ Coll Informat Sci & Engn Jishou 416000 Peoples R China SYSU CMU Shunde Int Joint Res Inst Shunde 528300 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China

In this paper, a new Taylor-type numerical differentiation formula is first presented to discretize the continuous-time Zhang neural network (ZNN), and obtain higher computational accuracy. Based on the Taylor-type formula, two Taylor-type discrete-time ZNN models (termed Taylor-type discrete-time ZNNK and Taylor-type discrete-time ZNNU models) are then proposed and discussed to perform online dynamic equality-constrained quadratic programming. For comparison, Euler-type discrete-time ZNN models (called Euler-type discrete-time ZNNK and Euler-type discrete-time ZNNU models) and Newton iteration, with interesting links being found, are also presented. It is proved herein that the steady-state residual errors of the proposed Taylor-type discrete-time ZNN models, Euler-type discrete-time ZNN models, and Newton iteration have the patterns of O(h(3)), O(h(2)), and O(h), respectively, with h denoting the sampling gap. Numerical experiments, including the application examples, are carried out, of which the results further substantiate the theoretical findings and the efficacy of Taylor-type discrete-time ZNN models. Finally, the comparisons with Taylor-type discrete-time derivative model and other Lagrange-type discrete-time ZNN models for dynamic equality-constrained quadratic programming substantiate the superiority of the proposed Taylor-type discrete-time ZNN models once again.

关键词： Computational accuracy discrete-time Zhang neural network (ZNN) equality constraint numerical differentiation online dynamic quadratic programming

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Tracking control of modified Lorenz nonlinear system using ZG neural dynamics with additive input or mixed inputs

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NEUROCOMPUTING 2016年 196卷 82-94页

作者： Jin, Long Zhang, Yunong Qiao, Tianjian Tan, Manchun Zhang, Yinyan Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Shunde 528300 Foshan Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Jinan Univ Dept Math Guangzhou 510632 Guangdong Peoples R China

The tracking-control problem of a special nonlinear system (i.e., the extension of a modified Lorenz chaotic system) with additive input or the mixture of additive and multiplicative inputs is considered in this paper. It is worth pointing out that, with the parameters fixed at some particular values, the modified Lorenz nonlinear system degrades to the modified Lorenz chaotic system. Note that, due to the existence of singularities at which the nonlinear system fails to have a well-defined relative degree, the inputoutput linearization method and the backstepping design technique cannot solve the tracking-control problem. By combining Zhang neural dynamics and gradient neural dynamics, a new effective controller design method, termed Zhang-gradient (ZG) neural dynamics, is proposed for the tracking control of the modified Lorenz nonlinear system. With singularities conquered, this ZG neural dynamics is able to solve the tracking-control problem of the modified Lorenz nonlinear system via additive input or mixed inputs (i.e., the mixture of additive and multiplicative inputs). Both theoretical analyses and simulative verifications substantiate that the tracking controllers based on the ZG neural dynamics with additive input or mixed inputs not only achieve satisfactory tracking accuracy but also successfully conquer the singularities encountered during the tracking-control process. Moreover, the applications to the synchronization, stabilization and tracking control of other nonlinear systems further illustrate the effectiveness and advantages of the ZG neural dynamics. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Tracking control Chaotic system Singularity conquering Zhang neural dynamics Gradient neural dynamics

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Development of a TouchX based Teleoperation Approach using Wave Variable Technique

Development of a TouchX based Teleoperation Approach using W...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Wang, Xingjian Yang, Chenguang Li, Zhijun South China Univ Technol Key Lab Autonomous Syst & Networked Control Coll Automat Sci & Engn Guangzhou 510640 Guangdong Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SA1 8EN W Glam Wales

ISBN: (纸本)9781509033645

In this paper, a teleoperation approach is developed for TouchX device using wave variable technique. The control system employs the 6-DOF (degrees of freedom) Geomagic (R) TouchX as a master device, and a 2-DOF simulated robot manipulator as slave. The master device provides user haptic feedback such that the bilateral opreation can be achieved for the teleoperation system. To avoid singularity pose during operation, we first defined a constrained workspace for the master device based on its kinematics. In the teleopration system, the CLIK (closed-loop inverse kinematics) method is used to achieve position control in the Cartesian space. The developed method integrates a corrective wave proportional to the difference between the desired and the fictitious position when in the time-varying delay communication. The system in this control strategy is proven to be stable and the positions of the master and the slave to coincide. And when static contact is made, the reflecting force tracks the reaction force well.

关键词： Remote control

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Active Disturbance Rejection Based Iterative Learning control

Active Disturbance Rejection Based Iterative Learning Contro...

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第28届中国控制与决策会议

作者： Xiangyang Li Senping Tian Wei Ai IEEE Key Laboratory of Autonomous Systems and Networked Control Ministry of EducationSchool of Automation Science and EngineeringSouth China University of Technology

ISBN: (纸本)9781467397155

The traditional iterative learning control(ILC) algorithm improves the control performance by updating the control input to implicitly compensate the periodic *** order to enhance the convergence rate of ILC,a new concept,iterative extended state observer(IESO),is presented which can estimate explicitly the periodic uncertainties during the process of iterations and be used to update the control input *** explicit estimation of the uncertainty by the linear IESO in the iteration domain is used to construct a new ILC algorithm based on active disturbance rejection(ADR).The ADR-based ILC algorithm and its corresponding theorem are given in detail and proven by using Lyapunov-like *** results verify the effectiveness of the proposed ILC algorithm,and the iterative learning efficiency is improved greatly by using ADR-based ILC algorithm.

关键词： Iterative Learning control(ILC) Extended State Observer(ESO) Iterative Extended State Observer(IESO) Active Disturbance Rejection Based Iterative Learning control(ADR-based ILC) Lyapunov-like Approach

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Z-type control of populations for Lotka-Volterra model with exponential convergence

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MATHEMATICAL BIOSCIENCES 2016年 272卷 15-23页

作者： Zhang, Yunong Yan, Xiaogang Liao, Bolin Zhang, Yinyan Ding, Yaqiong Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan 528300 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Jishou Univ Coll Informat Sci & Engn Jishou 416000 Peoples R China

The population control of the Lotka-Volterra model is one of the most important and widely investigated issues in mathematical ecology. In this study, assuming that birth rate is controllable and using the Z-type dynamic method, we develop Z-type control laws to drive the prey population and/or predator population to a desired state to keep species away from extinction and to improve ecosystem stability. A direct controller group is initially designed to control the prey and predator populations simultaneously. Two indirect controllers are then proposed for prey population control and predator population control by exerting exogenous measure on another species. All three control laws possess exponential convergence performances. Finally, the corresponding numerical simulations are performed. Results substantiate the theoretical analysis and effectiveness of such Z-type control laws for the population control of the Lotka-Volterra model. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Lotka-Volterra model Z-type controller Population control Exponential convergence Numerical simulation

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Sigmoid Function Array Based ZG control for Bounded Input, Energy Saving and Output Tracking of Time-Invariant Linear System 12

Sigmoid Function Array Based ZG Control for Bounded Input, E...

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12th World Congress on Intelligent control and Automation (WCICA)

作者： Zhang, Yunong Wang, Jinjin Zhang, Deyang Qiu, Binbin Zhang, Yinyan SYSU Sch Elect & Informat Technol Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan 528300 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781467384148

The Zhang-gradient (ZG) method has been proved to be powerful for control problems solving. In view of the boundedness and safety of practical actuators through limiting the input, the sigmoid function array (SFA) based ZG (SFABZG) controller, designed by the combination of the SFA and the ZG method, is proposed and investigated for output tracking of the time-invariant linear (TIL) system in this paper. Simulation results substantiate the efficacy and superiority of the proposed novel controller for output tracking of the TIL system with the input bounded and energy saved.

关键词： Linear systems

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Discontinuous Signum-Activated ZD controllers Handling Agitator Tank as An Attempt 3

Discontinuous Signum-Activated ZD Controllers Handling Agita...

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3rd International Conference on systems and Informatics (ICSAI)

作者： Ding, Yaqiong Li, Xiaodong Zhang, Deyang Tan, Hongzhou Zhang, Yunong SYSU Sch Data & Comp Sci Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan 528300 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781509055210

In this paper, discontinuous signum-activated ZD (Zhang dynamics) controllers are proposed as an attempt firstly to handle the agitator tank. For the agitator tank, there are two control variables, which are accurate concentration and moderate liquid level. In other words, the proposed discontinuous signum-activated ZD controllers are designed to make the two variables of the agitator tank converge to desired trajectories. Moreover, signum function, as a kind of discontinuous activated function, has easier circuit implementation and thus is introduced as an activation function for handling agitator tank as an attempt. Besides, different tracking trajectories are used, and corresponding simulation results are shown in this paper. The simulation results, compared with the ZD controllers using the linear activation function, further verify the relative effectiveness of the discontinuous signum-activated ZD controllers. In addition, the simulation results also simultaneously show that the discontinuous signum-activated ZD controllers of the agitator tank may oscillate under certain frequencies.

关键词： signum activation function ZD controllers agitator tank tracking control

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The Second-Order ZD, GD and Hybrid systems Solving Nonlinear Equations Compared with Other Dynamics 28

The Second-Order ZD, GD and Hybrid Systems Solving Nonlinear...

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28th Chinese control and Decision Conference

作者： Zhang, Yunong Wang, Jinjin Qiao, Tianjian Xiao, Zhengli Mao, Mingzhi SYSU Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan 528300 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781467397148

Solving nonlinear equations has become increasingly significant and indispensable in many disciplines. In the recent decade, two powerful methods, the Zhang dynamics (ZD) method and the gradient dynamics (GD) method have been extensively investigated and implemented in solving nonlinear equations. In addition, some conventional methods, such as the dynamic relaxation method (DRM), redundant manipulators dynamics (RMD), and Langevin dynamics (LD), can also be applied to solve nonlinear equations. In this paper, we propose four novel types of systems based on the ZD method, the GD method and the hybrid dynamics methods to solve nonlinear equations in time-invariant and time-variant situations, respectively. In addition, it is worth pointing out that, by comparison, the four proposed systems depicted in the second-order dynamics are evidently quite different from and more general than some other conventional systems/dynamics for solving nonlinear equations, which all constitute the unified second-order methodology for nonlinear equations solving.

关键词： Zhang Dynamics Gradient Dynamics Time-Invariant Nonlinear Equations Time-Variant Nonlinear Equations Comparison

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GZ-type complex dynamic system solving online for time-varying complex matrix inverse

GZ-type complex dynamic system solving online for time-varyi...

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IEEE International Conference on Information and Automation (ICIA)

作者： Zhang, Deyang He, Penghao Wang, Nanhao Liao, Bolin Zhang, Yunong SYSU Sch Data & Comp Sci Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan 528300 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781509041022

A novel complex dynamic system, termed GZ-type (gradient-Zhang type) complex dynamic system, is proposed and investigated for solving online the time-varying complex matrix inverse problem, which is based on the ingenious combination of the conventional gradient dynamic system and the recently-proposed Zhang dynamic system. Theoretical results and simulation results both show the efficacy of the proposed complex model for time-varying complex matrix inversion.

关键词： Gradient dynamics Zhang dynamics time-varying complex matrix inverse

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Enhanced discrete-time Zhang neural network for time-variant matrix inversion in the presence of bias noises

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NEUROCOMPUTING 2016年 207卷 220-230页

作者： Mao, Mingzhi Li, Jian Jin, Long Li, Shuai Zhang, Yunong Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Shunde 528300 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Hong Kong Polytech Univ Dept Chem Kowloon Hong Kong Peoples R China

Inevitable noises and limited computational time are major issues for time-variant matrix inversion in practice. When designing a time-variant matrix inversion algorithm, it is highly demanded to suppress noises without violating the performance of real-time computation. However, most existing algorithms only consider a nominal system in the absence of noises, and may suffer from a great computational error when noises are taken into account. Some other algorithms assume that denoising has been conducted before computation, which may consume extra time and may not be suitable in practice. By considering the above situation, in this paper, an enhanced discrete-time Zhang neural network (EDTZNN) model is proposed, analyzed and investigated for time-variant matrix inversion. For comparison, an original discrete-time Zhang neural network (ODTZNN) model is presented. Note that the EDTZNN model is superior to ODTZNN model in suppressing various kinds of bias noises. Moreover, theoretical analyses show the convergence of the proposed EDTZNN model in the presence of various kinds of bias noises. In addition, numerical experiments including an application to robot motion planning are provided to substantiate the efficacy and superiority of the proposed EDTZNN model for time-variant matrix inversion. (C) 2016 Elsevier BAT. All rights reserved.

关键词： Enhanced discrete-time Zhang neural network model Time-variant matrix inversion Bias noises Convergence Residual error

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