Yun Zhang

GuangDong University of Technology, Shengcheng, Guangdong, China

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Publications (48)35.44 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, a robust adaptive fuzzy control approach is proposed for a class of nonlinear systems in strict-feedback form with the unknown time-varying saturation input. To deal with the time-varying saturation problem, a novel controller separation approach is proposed in the literature to separate the desired control signal from the practical constrained control input. Furthermore, an optimized adaptation method is applied to the dynamic surface control design to reduce the number of adaptive parameters. By utilizing the Lyapunov synthesis, the fuzzy logic system technique and the Nussbaum function technique, an adaptive fuzzy control algorithm is constructed to guarantee that all the signals in the closed-loop control system remain semiglobally uniformly ultimately bounded, and the tracking error is driven to an adjustable neighborhood of the origin. Finally, some numerical examples are provided to validate the effectiveness of the proposed control scheme in the literature.
    Asian Journal of Control 08/2014; · 1.41 Impact Factor
  • Zhi Liu, Ci Chen, Yun Zhang, C L P Chen
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    ABSTRACT: To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with the nonlinearities existing in the system dynamics. The literatures so far on the humanoid robot control have a common assumption that the problem of output hysteresis could be ignored. However, in the practical applications, the output hysteresis is widely spread; and its existing limits the motion/force performances of the robotic system. In this paper, an adaptive neural control scheme, which takes the unknown output hysteresis and computational efficiency into account, is presented and investigated. In the controller design, the prior knowledge of system dynamics is assumed to be unknown. The motion error is guaranteed to converge to a small neighborhood of the origin by Lyapunov's stability theory. Simultaneously, the internal force is kept bounded and its error can be made arbitrarily small.
    IEEE transactions on cybernetics. 06/2014;
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    ABSTRACT: An interval type-2 fuzzy weighted support vector machine (IT2FW-SVM) is proposed to address the problem of high energy consumption for biped walking robots. Different from the traditional machine learning method of ‘copy learning’, the proposed IT2FW-SVM obtains lower energy cost and larger zero moment point (ZMP) stability margin using a novel strategy of ‘selective learning’, which is similar to human selections based on experience. To handle the uncertainty of the experience, the learning weights in the IT2FW-SVM are deduced using an interval type-2 fuzzy logic system (IT2FLS), which is an extension of the previous weighted SVM. Simulation studies show that the existing biped walking which generates the original walking samples is improved remarkably in terms of both energy efficiency and biped dynamic balance using the proposed IT2FW-SVM.
    Applied Intelligence 04/2014; 40(3). · 1.85 Impact Factor
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    ABSTRACT: This paper proposed an Interval Type-2 Fuzzy Kernel based Support Vector Machine (IT2FK-SVM) for scene classification of humanoid robot. Type-2 fuzzy sets have been shown to be a more promising method to manifest the uncertainties. Kernel design is a key component for many kernel-based methods. By integrating the kernel design with type-2 fuzzy sets, a systematic design methodology of IT2FK-SVM classification for scene images is presented to improve robustness and selectivity in the humanoid robot vision, which involves feature extraction, dimensionality reduction and classifier learning. Firstly, scene images are represented as high dimensional vector extracted from intensity, edge and orientation feature maps by biological-vision feature extraction method. Furthermore, a novel three-domain Fuzzy Kernel-based Principal Component Analysis (3DFK-PCA) method is proposed to select the prominent variables from the high-dimensional scene image representation. Finally, an IT2FM SVM classifier is developed for the comprehensive learning of scene images in complex environment. Different noisy, different view angle, and variations in lighting condition can be taken as the uncertainties in scene images. Compare to the traditional SVM classifier with RBF kernel, MLP kernel, and the Weighted Kernel (WK), respectively, the proposed method performs much better than conventional WK method due to its integration of IT2FK, and WK method performs better than the single kernel methods (SVM classifier with RBF kernel or MLP kernel). IT2FK-SVM is able to deal with uncertainties when scene images are corrupted by various noises and captured by different view angles. The proposed IT2FK-SVM method yields over $92~\% $ 92 % classification rates for all cases. Moreover, it even achieves $98~\% $ 98 % classification rate on the newly built dataset with common light case.
    Soft Computing 03/2014; · 1.30 Impact Factor
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    ABSTRACT: A three-domain fuzzy wavelet network filter (3DFWNF) is proposed to filter the physiological tremor in robotic assisted microsurgical procedures, which bases on the three-domain fuzzy wavelet neural network (3DFWN) for estimating the modulated signals with multiple frequency components. The fuzzy domain is added in the 3DFWN to handle the fuzzy uncertainties of the tremor signals. The adaptive parameters of the network are adjusted by using a novel particle swarm optimization (PSO) algorithm in the training process, namely fuzzy PSO (FPSO). FPSO adopts fuzzy sets described by Gaussian membership function to define the position and velocity of particles, thus all arithmetic operators in the position and velocity updating rules used in the original PSO are replaced by the operators and procedures defined on fuzzy sets. Without the necessity for gradients, the FPSO coordinates the exploration and exploitation capabilities of particles, ensures quick convergence and a preferable global search. The proposed filter is compared with the existing RBF neural network and fuzzy wavelet neural networks. Experiments are carried in different situations, experimental results show superiority on tremor suppression of the newly filter. The effectiveness and accuracy of the FPSO algorithm are also verified.
    Knowledge-Based Systems. 01/2014;
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    ABSTRACT: A novel three-domain fuzzy support vector regression (3DFSVR) is proposed, where the three-domain fuzzy kernel function (3DFKF) provides a solution to process uncertainties and input--output data information simultaneously. When compared with traditional two-domain SVR (2DSVR), the major advantage of 3DFSVR is able to use the prior knowledge via the novel fuzzy domain to analyze uncertain data and signals, which will enhance the potentials of 2DSVR. The 3DFKF is presented to integrate the kernel and fuzzy membership functions into a three-domain function. Definition and solution of the fuzzy convex optimization problem are presented to construct the whole theoretical framework. Experiments and simulation results show the effectiveness of 3DFSVR for the uncertain image denoising.
    IEEE transactions on cybernetics. 05/2013;
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    ABSTRACT: One of the amazing abilities of fuzzy logic systems or neural networks is their ability to approximate unknown certainties. When nonlinear systems possess multiple variables, however, the process of the adaptive fuzzy or neural network online control becomes difficult. In this paper, we will introduce the extended partition of unity (EPU), composed of scalars and saturators, to address this problem. The merit of the suggested design scheme is that the construction of the partition of unity and the design of adaptive laws are separate. This means the proposed design method only adjusts the outputs of EPU and one update law, even in nonlinear systems with multiple variables. Therefore, this new method of EPU leads to easier selection of basis functions, reduces the number of adaptive laws, has greater robustness, and is suitable for different kinds of universal approximators. Finally, a numerical example is given to illustrate the effectiveness of the approach.
    Asian Journal of Control 05/2013; 15(3). · 1.41 Impact Factor
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    ABSTRACT: The synchronization for a class of complex dynamical network with similar nodes and coupling time-delay is investigated. The dimensions of the dynamical nodes in the complex network are different. Moreover, the coupling time-delays of the dynamical nodes are also different, and the decentralized control strategies are designed in term of the information of the similar parameters in dynamical complex networks by using the method of linear matrix inequality. The definition of the synchronization manifold is constructed, and the time delay independent criterion of the synchronization of the complex dynamical networks is derived. Finally, a numerical example is presented to demonstrate the application of the theoretical results.
    Applied Mathematics and Computation 02/2013; 219(12):6719–6728. · 1.35 Impact Factor
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    ABSTRACT: To learn biped walking dynamics accurately, and then compensate time-varying external disturbances timely, a time-sequence-based fuzzy SVM (TSF-SVM) learning control system considering time properties of biped walking samples is proposed. For the first time, time-sequence-based triangular and Gaussian fuzzy membership functions have been proposed for the single support phase (SSP) and the double support phase (DSP), respectively, according to time properties of different biped phases, which provides an effective way to formulate time properties of biped walking samples in the context of time-varying external disturbances. In addition, a time-sequence-based moving learning window (TS-MLW) is proposed for online training of the proposed TSF-SVM. The performance of the proposed TSF-SVM is compared with other typical intelligent methods; simulation results demonstrate that the proposed method is more sensitive to occasional external disturbances, which increases the stability margin and prevents the robot from falling down.
    Engineering Applications of Artificial Intelligence 02/2013; 26(2):757–765. · 1.96 Impact Factor
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    ABSTRACT: Traditional wavelet system is a two-domain (time and frequency domains) wavelet system (2DWS), which works only in time and frequency domains. The 2DWS is not able to treat time-frequency information and fuzziness simultaneously. For this reason, a three-domain (fuzzy, time, and frequency domains) fuzzy wavelet system (3DFWS) is proposed, where the three-domain mechanism provides a solution to handle fuzzy uncertainties and time-frequency information together. The major advantage of 3DFWS is able to use the prior knowledge via the novel fuzzy domain to analyze uncertain data and signals, which will enhance the potentials of 2DWS. Experimental and simulation studies show that the performance of the proposed 3DFWS is superior to the traditional one for simultaneous processing of time-frequency and fuzziness.
    IEEE Transactions on Fuzzy Systems 01/2013; 21(1):176-183. · 5.48 Impact Factor
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    ABSTRACT: An energy-efficient support vector machine (EE-SVM) learning control system considering the energy cost of each training sample of biped dynamic is proposed to realize energy-efficient biped walking. Energy costs of the biped walking samples are calculated. Then the samples are weighed with the inverses of the energy costs. An EE-SVM objective function with energy-related slack variables is proposed, which follows the principle that the sample with the lowest energy consumption is treated as the most important one in the training. That means the samples with lower energy consumption contribute more to the EE-SVM regression function learning, which highly increases the energy efficiency of the biped walking. Simulation results demonstrate the effectiveness of the proposed method.
    IEEE transactions on neural networks and learning systems 01/2013; 24(5):831-837. · 3.77 Impact Factor
  • Qijie Zeng, Yun Zhang, Bin Tang
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    ABSTRACT: This paper deals with the robust stability analysis for uncertain systems with time-varying delay. A novel augmented Lyapunov-Krasovskii functional is constructed by decomposing the delay interval [0, d (t)] into some variable sub-intervals and line integral technology. Using the novel augmented functional, the new delay-dependent stability criteria are proposed for linear systems with time-varying delay. All the stability criteria are formulated in the form of linear matrix inequality (LMI). Some numerical examples are given to show the less conservatism and applicability of the obtained results.
    Control and Decision Conference (CCDC), 2013 25th Chinese; 01/2013
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    ABSTRACT: An unscented Kalman filter (UKF)-based predictable support vector regression (SVR) learning controller is proposed to improve the flexibility of biped walking robots. After estimating the biped states of the next moment using a UKF, an SVR learning controller with the predicted biped states is implemented to ensure the zero moment point (ZMP) stability. Using the predicted biped states, the SVR learning controller can predictably adjust the posture of the trunk timely and properly to adapt to the dynamic posture of the whole body. The flexibility of biped robots is enhanced by the proposed method, which is promising for realizing the stable biped walking in unstructured environments. Simulation and experimental results demonstrate the superiority of the proposed methods.
    Systems, Man, and Cybernetics: Systems, IEEE Transactions on. 01/2013; 43(6):1440-1450.
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    ABSTRACT: This paper investigates the synchronisation of nonlinear coupled complex dynamical networks with different nonlinear nodes and different orders by using decentralised dynamical compensation controllers. We propose a dynamical network mathematical model with similar nonlinear nodes, whose dimensions are different. For this kind of network model, the decentralised dynamical compensation controllers are designed for the state synchronisation of the coupled nodes. In addition, the synchronisation manifold is defined as an invariant manifold, which is regarded as the generalised case of dynamical networks with the same nodes’ dynamics. Furthermore, some stability criteria for the synchronisation are derived by means of rigorous theoretical analysis. Finally, numerical examples are presented to verify the effectiveness of the obtained theoretical results.
    International Journal of Control 01/2013; 86(10). · 1.01 Impact Factor
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    ABSTRACT: For a sampled-data control system with nonuniform sampling, the sampling interval sequence, which is continuously distributed in a given interval, is described as a multiple independent and identically distributed (i.i.d.) process. With this process, the closed-loop system is transformed into an asynchronous dynamical impulsive model with input delays. Sufficient conditions for the closed-loop mean-square exponential stability are presented in terms of linear matrix inequalities (LMIs), in which the relation between the nonuniform sampling and the mean-square exponential stability of the closed-loop system is explicitly established. Based on the stability conditions, the controller design method is given, which is further formulated as a convex optimization problem with LMI constraints. Numerical examples and experiment results are given to show the effectiveness and the advantages of the theoretical results.
    International Journal of Automation and Computing 10/2012; 9(5).
  • Xiaolong Chen, Yun Zhang, Zhi Liu
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    ABSTRACT: We investigate the global stability of the nonlinear Fast active queue management scalable Transmission Control Protocol (FAST TCP) system with time-varying time-delay. By considering that the time-delay variation is proportional to the sending window variation of the TCP source and the nonlinear function is strictly monotonically decreasing, we present improved iterative formulas for calculating the trajectory bounds and determining the trajectory bounds of the Fast TCP system in each oscillating period. For the Fast TCP system, we develop a global stability condition which is less conservative than the existing one. The effectiveness of this improved global stability condition is validated by the network simulator 2 (NS-2) simulation results.
    Kongzhi Lilun Yu Yinyong/Control Theory and Applications 01/2012; 29(4).
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    ABSTRACT: By employing the partition of unity subordinated to an open covering of the system state domain, firstly, several local fuzzy logic systems are synthesized to product a function approximator. Compared with the existing results, this approximator possesses not only the property of universal approximation but also the language interpretability due to the local fuzzy logic systems with fewer rules. Then, a time-varying parameter is introduced into the approximator to design adaptive controllers for a class of nonlinear systems with uncertainties. Finally, simulations show the effectiveness of the proposed method.
    Control and Decision. 01/2012; 27(12).
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    ABSTRACT: Many practical engineering applications require various types of fuzzy logic systems (FLSs) to design adaptive controllers for nonlinear systems with uncertainties. In this article, we will consider a fundamental theoretical question: is it possible to find a unified adaptive control design method suited to various types of FLSs? In order to solve this problem, we will introduce scalers and saturators at the input and output terminals of FLSs to form the extended FLSs (EFLS). The scalers and saturators have adjustable parameters. By designing the updated laws of these parameters and the estimate values of the fuzzy approximate accuracies, stable adaptive fuzzy controllers can be realised for a class of nonlinear systems with unknown homogeneous drift functions and gains. The proposed design method is only dependent on the outputs of EFLS and the above updated laws, thus increasing its adaptability. The fuzzy control scheme introduced in this article is suitable for all fuzzy systems with or without fuzzy rules. Simulations will also be used to show the validity of the method proposed in this article.
    International Journal of Systems Science 01/2012; · 1.31 Impact Factor
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    ABSTRACT: Regional pole assignment is studied for a class of linear systems via static output feedback. The shortage of the optimization problem subject to a set of bilinear matrix inequalities(BMIs) is analyzed. Then the algorithm of static output feedback pole assignment based on the regional attractors is proposed. A set of attractors in the satisfactory region is determined firstly. After that, the optimization direction of the output feedback matrix can be obtained via the one-dimensional searching method of variable polling. And a feasible solution can be attained by iterative computation. Computational results are presented demonstrating the effectiveness of the provided algorithm.
    Intelligent Control and Automation (WCICA), 2012 10th World Congress on; 01/2012
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    ABSTRACT: This paper presents a motion planning and control method for determining the joint velocities of a single-legged robot based on the desired Centre of Pressure (COP) motion, the Centre of Mass (COM) dynamics and the ground reaction forces. A closed-loop inverse kinematics algorithm is implemented using the Centre of Gravity (COG) Jacobian, while the control system relies on the reaction force data to estimate the real COP. The main idea is to manipulate the dynamics of the COM such as the COP shows a desired behavior. The implementation of the COP-based controller is described to demonstrate the possibility of keeping a single-legged robot in balance, while adapting to unexpected changes in a slope surface or during execution of a specified motion task. Simulation results are illustrated throughout the paper to validate the proposed controller.
    Robotics and Biomimetics (ROBIO), 2012 IEEE International Conference on; 01/2012