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New mixed broadcast scheduling approach using neural networks and graph coloring in wireless sensor network

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Journal of Systems Engineering and Electronics 2009年第1期20卷 185-191页

作者： Zhang Xizheng wang yaonan Dept. of Computer Science Hunan Inst. of Engineering Xiangtan 411104 P. R. China School of Electrical and Information Engineering Hunan Univ. Changsha 410082 P. R. China

Due to the mutual interference and sharing of wireless links in TDMA wireless sensor networks, conflicts will occur when data messages are transmitting between nodes. The broadcast scheduling problem （BSP） is aimed to schedule each node in different slot of fixed length frame at least once, and the objective of BSP is to seek for the optimal feasible solution, which has the shortest length of frame slots, as well as the maximum node transmission. A two-stage mixed algorithm based on a fuzzy Hopfield neural network is proposed to solve this BSP in wireless sensor network. In the first stage, a modified sequential vertex coloring algorithm is adopted to obtain a minimal TDMA frame length. In the second stage, the fuzzy Hopfleld network is utilized to maximize the channel utilization ratio. Experimental results, obtained from the running on three benchmark graphs, show that the algorithm can achieve better performance with shorter frame length and higher channel utilizing ratio than other exiting BSP solutions.

关键词： wireless sensor network broadcast scheduling fuzzy Hopfield network graph coloring.

Robust dynamic surface control of flexible joint robots using recurrent neural networks

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控制理论与应用（英文版） 2013年第2期11卷 222-229页

作者： Zhiqiang MIAO yaonan wang College of Electrical and Information Engineering Hunan University

A robust neuro-adaptive controller for uncertain flexible joint robots is presented. This control scheme integrates H^infinity disturbance attenuation design and recurrent neural network adaptive control technique into the dy- namic surface control framework. Two recurrent neural networks are used to adaptively learn the uncertain functions in a flexible joint robot. Then, the effects of approximation error and filter error on the tracking performance are attenuated to a prescribed level by the embedded H-infinity controller, so that the desired H-infinity tracking performance can be achieved. Finally. simulation results verifv the effectiveness of the nronosed control scheme.

关键词： Dynamic surface control Flexible joint robots Robust H-infinity control Recurrent neural network

Effective method for tracking multiple objects in real-time visual surveillance systems

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Journal of Systems Engineering and Electronics 2009年第6期20卷 1167-1178页

作者： wang yaonan Wan Qin Yu Hongshan Coll. of Electrical and Information Engineering Hunan Univ. Changsha 410082 P. R. China

An object model-based tracking method is useful for tracking multiple objects, but the main difficulties are modeling objects reliably and tracking objects via models in successive frames. An effective tracking method using the object models is proposed to track multiple objects in a real-time visual surveillance system. Firstly, for detecting objects, an adaptive kernel density estimation method is utilized, which uses an adaptive bandwidth and features combining colour and gradient. Secondly, some models of objects are built for describing motion, shape and colour features. Then, a matching matrix is formed to analyze tracking situations. If objects are tracked under occlusions, the optimal ＂visual＂ object is found to represent the occluded object, and the posterior probability of pixel is used to determine which pixel is utilized for updating object models. Extensive experiments show that this method improves the accuracy and validity of tracking objects even under occlusions and is used in real-time visual surveillance systems.

关键词： visual surveillance multiple object tracking object model matching matrix.

High-Order Control Barrier Function-Based Safety Control of Constrained Robotic Systems:An Augmented Dynamics Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2487-2496页

作者： Haijing wang Jinzhu Peng Fangfang Zhang yaonan wang the School of Electrical and Information Engineering Zhengzhou University the National Engineering Laboratory for Robot Visual Perception and Control Hunan University the College of Electrical and Information Engineering Hunan University

Although constraint satisfaction approaches have achieved fruitful results, system states may lose their smoothness and there may be undesired chattering of control inputs due to switching characteristics. Furthermore, it remains a challenge when there are additional constraints on control torques of robotic systems. In this article, we propose a novel high-order control barrier function(HoCBF)-based safety control method for robotic systems subject to input-output constraints, which can maintain the desired smoothness of system states and reduce undesired chattering vibration in the control torque. In our design, augmented dynamics are introduced into the HoCBF by constructing its output as the control input of the robotic system,so that the constraint satisfaction is facilitated by HoCBFs and the smoothness of system states is maintained by the augmented dynamics. This proposed scheme leads to the quadratic program(QP), which is more user-friendly in implementation since the constraint satisfaction control design is implemented as an add-on to an existing tracking control law. The proposed closed-loop control system not only achieves the requirements of real-time capability, stability, safety and compliance, but also reduces undesired chattering of control inputs. Finally, the effectiveness of the proposed control scheme is verified by simulations and experiments on robotic manipulators.

关键词： Augmented dynamics high-order control barrier function (HoCBF) input-output constraints quadratic program (QP) robotic systems

Boundary Gap Based Reactive Navigation in Unknown Environments

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 468-477页

作者： Zhao Gao Jiahu Qin Shuai wang yaonan wang the Department of Automation University of Science and Technology of ChinaHefei 230027China the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the National Engineering Laboratory for Robot Visual Perception and Control Technology Changsha 410082China

Due to the requirements for mobile robots to search or rescue in unknown environments,reactive navigation which plays an essential role in these applications has attracted increasing ***,most existing reactive methods are vulnerable to local minima in the absence of prior knowledge about the *** paper aims to address the local minimum problem by employing the proposed boundary gap(BG)based reactive navigation ***,the narrowest gap extraction algorithm(NGEA)is proposed to eliminate the improper ***,we present a new concept called boundary gap which enables the robot to follow the obstacle boundary and then get rid of local ***,in order to enhance the smoothness of generated trajectories,we take the robot dynamics into consideration by using the modified dynamic window approach(DWA).Simulation and experimental results show the superiority of our method in avoiding local minima and improving the smoothness.

关键词： Boundary gap local minima reactive navigation unknown environments

Robust fuzzy control of Takagi-Sugeno fuzzy neural networks with discontinuous activation functions and time delays

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Journal of Systems Engineering and Electronics 2011年第3期22卷 473-481页

作者： yaonan wang Xiru Wu Yi Zuo College of Electrical and Information Engineering Hunan UniversityChangsha 410082P.R.China School of Energy and Power Engineering Changsha University of Science and TechnologyChangsha 410004P.R.China

The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks（TSFNN） with discontinuous activation functions and time delays is investigated by using Lyapunov stability *** on linear matrix inequalities（LMIs）,we originally propose robust fuzzy control to guarantee the global robust asymptotical stability of *** with the existing literature,this paper removes the assumptions on the neuron activations such as Lipschitz conditions,bounded,monotonic increasing property or the right-limit value is bigger than the left one at the discontinuous ***,the results are more general and ***,two numerical examples are given to show the effectiveness of the proposed stability results.

关键词： delayed neural network global robust asymptotical stability discontinuous neuron activation linear matrix inequality(LMI) Takagi-sugeno(T-S) fuzzy model.

Adaptive-backstepping force/motion control for mobile-manipulator robot based on fuzzy CMAC neural networks

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Control Theory and Technology 2014年第4期12卷 368-382页

作者： Thang-Long MAI yaonan wang College of Electrical and Information Engineering Hunan University Faculty of Electronics Engineering Industrial University of Hochiminh City

In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control （ABFCNC） system for motion/force control of the mobile-manipulator robot （MMR） is proposed. By applying the ABFCNC in the tracking-position controller, the unknown dynamics and parameter variation problems of the MMR control system are relaxed. In addition, an adaptive robust compensator is proposed to eliminate uncertainties that consist of approximation errors, uncertain disturbances. Based on the tracking position-ABFCNC design, an adaptive robust control strategy is also developed for the nonholonomicconstraint force of the MMR. The design of adaptive-online learning algorithms is obtained by using the Lyapunov stability theorem. Therefore, the proposed method proves that it not only can guarantee the stability and robustness but also the tracking performances of the MMR control system. The effectiveness and robustness of the proposed control system are verified by comparative simulation results.

关键词： Backstepping control Fuzzy CMAC (cerebellar model articulation controller) neural networks Adaptive robustcontrol Mobile-manipulator robot

A new ensemble feature selection and its application to pattern classification

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控制理论与应用（英文版） 2009年第4期7卷 419-426页

作者： Dongbo ZHANG yaonan wang Institute of Information Engineering Xiangtan University Xiangtan Hunan 411105 China College of Electrical and Information Engineering Hunan University Changsha Hunan 410082 China

Neural network ensemble based on rough sets reduct is proposed to decrease the computational complexity of conventional ensemble feature selection algorithm. First, a dynamic reduction technology combining genetic algorithm with resampling method is adopted to obtain reducts with good generalization ability. Second, Multiple BP neural networks based on different reducts are built as base classifiers. According to the idea of selective ensemble, the neural network ensemble with best generalization ability can be found by search strategies. Finally, classification based on neural network ensemble is implemented by combining the predictions of component networks with voting. The method has been verified in the experiment of remote sensing image and five UCI datasets classification. Compared with conventional ensemble feature selection algorithms, it costs less time and lower computing complexity, and the classification accuracy is satisfactory.

关键词： Rough sets reduction Ensemble feature selection Neural network ensemble Remote sensing image classification

Design of PID controller with incomplete derivation based on differential evolution algorithm

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Journal of Systems Engineering and Electronics 2008年第3期19卷 578-583页

作者： Wu Lianghong wang yaonan Zhou Shaowu Tan Wen School of Information and Electric Engineering Hunan Univ. of Science and Technology Xiangtan 411201 P. R. China Coll. of Electric and Information Engineering Hunan Univ. Changsha 410082 P. R. China

To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.

关键词： PID controller incomplete derivation differential evolution parameter tuning.