Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8405799
Junjie Fu, G. Wen
In this paper, we consider the sampled-data consensus of a class of nonlinear multi-agent systems under general directed communication graphs. A distributed consensus controller which uses only sampled-data relative state measurements is first proposed. Then, by input delay approach, the closed-loop system is reformulated as continuous systems with time-varying input delay. Based on novel Lyapunov functions, sufficient conditions on the controller parameters, the sampling interval upper bound and the communication graphs to achieve consensus are derived. Then, simple LMI conditions are given to design the controller. A simulation example is given to illustrate the obtained results.
{"title":"Sampled-data consensus of Lipschitz nonlinear multi-agent systems under directed communication graphs","authors":"Junjie Fu, G. Wen","doi":"10.1109/YAC.2018.8405799","DOIUrl":"https://doi.org/10.1109/YAC.2018.8405799","url":null,"abstract":"In this paper, we consider the sampled-data consensus of a class of nonlinear multi-agent systems under general directed communication graphs. A distributed consensus controller which uses only sampled-data relative state measurements is first proposed. Then, by input delay approach, the closed-loop system is reformulated as continuous systems with time-varying input delay. Based on novel Lyapunov functions, sufficient conditions on the controller parameters, the sampling interval upper bound and the communication graphs to achieve consensus are derived. Then, simple LMI conditions are given to design the controller. A simulation example is given to illustrate the obtained results.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128093882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406343
Yu Cao, Yahui Gan, X. Dai, Jun-Feng Cao
To solve the inverse kinematics of 7-DOF redundant manipulators with arbitrary offsets. A numerical method that is based on augmented Jacobian is proposed. Firstly, the end-effector Jacobian is given to reflect the relationship between joint angle rates and end-effector rates. To solve the redundancy of 7-DOF manipulator, an arm angle parameter is defined to parameterize the redundancy of manipulator. From the geometric features of the manipulator, the Jacobian matrix of arm angle is built to solve the redundancy of the manipulator. Furthermore, singularities of Jacobian are discussed mainly by analyzing the rank of Jacobian. In the end, the method is verified with Yaskawa VA1400II manipulator. The results of simulations and experiment strongly prove the validity and efficiency of this method.
{"title":"Inverse kinematics of 7-DOF redundant manipulators with arbitrary offsets based on augmented Jacobian","authors":"Yu Cao, Yahui Gan, X. Dai, Jun-Feng Cao","doi":"10.1109/YAC.2018.8406343","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406343","url":null,"abstract":"To solve the inverse kinematics of 7-DOF redundant manipulators with arbitrary offsets. A numerical method that is based on augmented Jacobian is proposed. Firstly, the end-effector Jacobian is given to reflect the relationship between joint angle rates and end-effector rates. To solve the redundancy of 7-DOF manipulator, an arm angle parameter is defined to parameterize the redundancy of manipulator. From the geometric features of the manipulator, the Jacobian matrix of arm angle is built to solve the redundancy of the manipulator. Furthermore, singularities of Jacobian are discussed mainly by analyzing the rank of Jacobian. In the end, the method is verified with Yaskawa VA1400II manipulator. The results of simulations and experiment strongly prove the validity and efficiency of this method.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114007350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406476
Zheng Zhang, X. Ren, Hengxing Lv
A deep learning method for fault diagnosis is proposed in this paper. The stacked sparse auto encoder(SSAE) model with the theory of deep learning extracts deep feature representation from original fault data. Compared with traditional methods, SSAE is more efficient because of its deep architecture. The feature representation is used by a softmax classifier for fault detection and classification. The proposed method is experimented on Tennessee Eastman Process(TEP), a chemical industrial process benchmark, to demonstrate its practicality and effectiveness.
{"title":"Fault diagnosis with feature representation based on stacked sparse auto encoder","authors":"Zheng Zhang, X. Ren, Hengxing Lv","doi":"10.1109/YAC.2018.8406476","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406476","url":null,"abstract":"A deep learning method for fault diagnosis is proposed in this paper. The stacked sparse auto encoder(SSAE) model with the theory of deep learning extracts deep feature representation from original fault data. Compared with traditional methods, SSAE is more efficient because of its deep architecture. The feature representation is used by a softmax classifier for fault detection and classification. The proposed method is experimented on Tennessee Eastman Process(TEP), a chemical industrial process benchmark, to demonstrate its practicality and effectiveness.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126080531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406506
Xiaofeng Chai, Qing Wang, Yao Yu
In this study, output formation control problems for high-order time-invariant swarm systems with unknown nonlinear uncertainties and directed interaction topologies are studied using a robust controller. First, the dimensions of the observation matrix are extended to be non-singular. Then the output formation problem is transformed into consensus problem. Based on observability decomposition, the consensus problem is transformed into stability problem. Further more, A robust controller which consists of a nominal controller and a robust compensator is applied to achieve formation control. The nominal controller based on the output feedback is designed to achieve desired output formation properties for the nominal system and the robust compensator based on the robust signal compensator technology is to restrain the nonlinear uncertainties. The proposed controller is linear, time invariant and easy to implement. Based on partial stability theory, sufficient and necessary conditions for output formation feasibility are given and the formation errors can be made as small as desired with expected convergence rate.
{"title":"Robust output formation control for swarm systems with nonlinear uncertainties in directed networks","authors":"Xiaofeng Chai, Qing Wang, Yao Yu","doi":"10.1109/YAC.2018.8406506","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406506","url":null,"abstract":"In this study, output formation control problems for high-order time-invariant swarm systems with unknown nonlinear uncertainties and directed interaction topologies are studied using a robust controller. First, the dimensions of the observation matrix are extended to be non-singular. Then the output formation problem is transformed into consensus problem. Based on observability decomposition, the consensus problem is transformed into stability problem. Further more, A robust controller which consists of a nominal controller and a robust compensator is applied to achieve formation control. The nominal controller based on the output feedback is designed to achieve desired output formation properties for the nominal system and the robust compensator based on the robust signal compensator technology is to restrain the nonlinear uncertainties. The proposed controller is linear, time invariant and easy to implement. Based on partial stability theory, sufficient and necessary conditions for output formation feasibility are given and the formation errors can be made as small as desired with expected convergence rate.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123059625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406514
Wu Di, Liu Bei, Niu Chengbo, Yi Yang
This paper addresses the anti-disturbance tracking control problem of robotic systems with exogenous disturbances. In order to obtain the favourable tracking performance, the disturbance-observer-based-control (DOBC) method is established to monitor the value of unknown disturbances in real time and the PID controller is designed to implement dynamical tracing for the displacement of typical second-order robotic systems. By using the Lyapunov analytical method, the controller gain and the observer gain can be computed so that the dynamical tracking error of the displacement tend to zero. Finally, the second-order model of robotic system is built to simulate. The satisfactory stability and the attitude tracking of the robotic system can be obtained via the designed algorithm.
{"title":"Anti-disturbance PID attitude tracking control for robotic manipulators via DOBC approach","authors":"Wu Di, Liu Bei, Niu Chengbo, Yi Yang","doi":"10.1109/YAC.2018.8406514","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406514","url":null,"abstract":"This paper addresses the anti-disturbance tracking control problem of robotic systems with exogenous disturbances. In order to obtain the favourable tracking performance, the disturbance-observer-based-control (DOBC) method is established to monitor the value of unknown disturbances in real time and the PID controller is designed to implement dynamical tracing for the displacement of typical second-order robotic systems. By using the Lyapunov analytical method, the controller gain and the observer gain can be computed so that the dynamical tracking error of the displacement tend to zero. Finally, the second-order model of robotic system is built to simulate. The satisfactory stability and the attitude tracking of the robotic system can be obtained via the designed algorithm.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128216650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406409
Lingxia Mu, Xiang Yu, Ban Wang, Youmin Zhang, Xinmin Wang, P. Li
A sliding mode guidance strategy is developed for an unpowered reusable launch vehicle (RLV) during the terminal area energy management (TAEM) phase. The 3-DOF guidance model of a RLV in the domain of altitude is firstly provided, based on which a new sliding surface is constructed to account for multiple constraints on terminal conditions and dynamic pressure profile during flight. A second-order sliding mode guidance law is then developed to ensure the reaching of the sliding surface at a specific altitude. The simulation results confirm the effectiveness of the proposed method.
{"title":"3D gliding guidance for an unpowered RLV in the TAEM phase","authors":"Lingxia Mu, Xiang Yu, Ban Wang, Youmin Zhang, Xinmin Wang, P. Li","doi":"10.1109/YAC.2018.8406409","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406409","url":null,"abstract":"A sliding mode guidance strategy is developed for an unpowered reusable launch vehicle (RLV) during the terminal area energy management (TAEM) phase. The 3-DOF guidance model of a RLV in the domain of altitude is firstly provided, based on which a new sliding surface is constructed to account for multiple constraints on terminal conditions and dynamic pressure profile during flight. A second-order sliding mode guidance law is then developed to ensure the reaching of the sliding surface at a specific altitude. The simulation results confirm the effectiveness of the proposed method.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134053499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406448
Liao Kaiju, Xuefeng Li, Chaoxu Mu, Wang Dan
Due to the meteorological factors, such as weather conditions, irradiance, ambient temperature and wind speed, as well as the non-meteorological factors, such as the temperature and installation location of components and parts, the output power of photovoltaic power generation system is characterized by strong intermittency, volatility and uncertainty, and low forecast accuracy of photovoltaic power generation. Based on the historical power generation data and the actual meteorological data of the photovoltaic system, the short-term prediction of the photovoltaic power generation is carried out by using the T-S fuzzy neural network prediction model. Finally, the prediction results of T-S neural network and traditional BP neural network are compared. The results show that the prediction accuracy of PV output power is improved by using the T-S fuzzy neural network prediction method. The average error percentage between the predicted result and the measured value is controlled within 8%. The algorithm can be effectively used for short-term power forecasting of photovoltaic systems.
{"title":"Short-term photovoltaic power prediction based on T-S fuzzy neural network","authors":"Liao Kaiju, Xuefeng Li, Chaoxu Mu, Wang Dan","doi":"10.1109/YAC.2018.8406448","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406448","url":null,"abstract":"Due to the meteorological factors, such as weather conditions, irradiance, ambient temperature and wind speed, as well as the non-meteorological factors, such as the temperature and installation location of components and parts, the output power of photovoltaic power generation system is characterized by strong intermittency, volatility and uncertainty, and low forecast accuracy of photovoltaic power generation. Based on the historical power generation data and the actual meteorological data of the photovoltaic system, the short-term prediction of the photovoltaic power generation is carried out by using the T-S fuzzy neural network prediction model. Finally, the prediction results of T-S neural network and traditional BP neural network are compared. The results show that the prediction accuracy of PV output power is improved by using the T-S fuzzy neural network prediction method. The average error percentage between the predicted result and the measured value is controlled within 8%. The algorithm can be effectively used for short-term power forecasting of photovoltaic systems.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115011240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406484
Jiadong Li, Xueqi Li, Lijuan Yu
In the environment where the topography of the plateau and mountainous terrain fluctuates, it is necessary to develop an optimal inspection plan when using a group drone to carry out detection and reconnaissance missions in this area. The overall inspection program is divided into two phases: the global optimal route planning, which is based on the parallel search strategy, establishes a nonlinear programming model with the minimum and maximum detection width as the objective function. Then it finds the track and duration of the entire area with a single drone in the least number of turns;In the local planning stage, the search area is divided according to the initial position and endurance of the group drone. An integer programming model is established and the minimum number of drones required is obtained by using a genetic algorithm. A patrol scheme is formulated to complete the continuous inspection task. The final simulation results show that this method of trajectory planning is effective and efficient.
{"title":"Multi-UAV cooperative coverage path planning in plateau and mountain environment","authors":"Jiadong Li, Xueqi Li, Lijuan Yu","doi":"10.1109/YAC.2018.8406484","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406484","url":null,"abstract":"In the environment where the topography of the plateau and mountainous terrain fluctuates, it is necessary to develop an optimal inspection plan when using a group drone to carry out detection and reconnaissance missions in this area. The overall inspection program is divided into two phases: the global optimal route planning, which is based on the parallel search strategy, establishes a nonlinear programming model with the minimum and maximum detection width as the objective function. Then it finds the track and duration of the entire area with a single drone in the least number of turns;In the local planning stage, the search area is divided according to the initial position and endurance of the group drone. An integer programming model is established and the minimum number of drones required is obtained by using a genetic algorithm. A patrol scheme is formulated to complete the continuous inspection task. The final simulation results show that this method of trajectory planning is effective and efficient.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130312357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406356
Zhenyu Lu, Yunan Qiu, You Fu, Bingjian Lu
Fuzzy C-Means (FCM) algorithm is one of the most commonly used image segmentation algorithms. It has the advantages of unsupervised, easy calculation, soft segmentation and so on. However, for the image containing noise, it will be more obviously disturbed. At the same time, it is sensitive to the initial value and easy to fall into the local minimum. Aiming at solving above problems, a new FCM algorithm is proposed, which combines wavelet transform and improved FCM algorithm. Firstly, the high frequency and low frequency coefficients of different scales are obtained by using the wavelet transform to decompose the image. The Anisotropic Diffusion is used to denoise the decomposed high frequency coefficients. Then, the processed coefficients are reconstructed by wavelet to get the processed images. Finally, the particle swarm optimization algorithm is used to update the FCM cluster centers to get the global optimal value. The experimental results show that the proposed algorithm can better suppress the influence of noise and has better robustness.
{"title":"An improved FCM method for image segmentation based on wavelet transform and particle swarm","authors":"Zhenyu Lu, Yunan Qiu, You Fu, Bingjian Lu","doi":"10.1109/YAC.2018.8406356","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406356","url":null,"abstract":"Fuzzy C-Means (FCM) algorithm is one of the most commonly used image segmentation algorithms. It has the advantages of unsupervised, easy calculation, soft segmentation and so on. However, for the image containing noise, it will be more obviously disturbed. At the same time, it is sensitive to the initial value and easy to fall into the local minimum. Aiming at solving above problems, a new FCM algorithm is proposed, which combines wavelet transform and improved FCM algorithm. Firstly, the high frequency and low frequency coefficients of different scales are obtained by using the wavelet transform to decompose the image. The Anisotropic Diffusion is used to denoise the decomposed high frequency coefficients. Then, the processed coefficients are reconstructed by wavelet to get the processed images. Finally, the particle swarm optimization algorithm is used to update the FCM cluster centers to get the global optimal value. The experimental results show that the proposed algorithm can better suppress the influence of noise and has better robustness.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127132867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-18DOI: 10.1109/YAC.2018.8406353
Di Cui, Ben Niu, Huan Li
This paper studies the issue of observer-based adaptive fuzzy control issue for a class of switched time-delay nonlinear systems in nonstrict-feedback form. Firstly, an adaptive output feedback fuzzy backstepping-based control approach is proposed for the switched nonstrict-feedback system. Furthermore, fuzzy logic systems (FLSs) are utilized to model the unknown nonlinear system functions, and backstepping and adaptive technique are applied to construct output feedback controllers for all switched subsystems. The proposed controllers insure that all of the switched signals in the whole closed-loop system are semi-globally uniformly ultimately bounded. In the end, simulation results are given to show the effectiveness of the obtained method.
{"title":"Observer-based adaptive control for nonlinear switched nonstrict-feedback systems","authors":"Di Cui, Ben Niu, Huan Li","doi":"10.1109/YAC.2018.8406353","DOIUrl":"https://doi.org/10.1109/YAC.2018.8406353","url":null,"abstract":"This paper studies the issue of observer-based adaptive fuzzy control issue for a class of switched time-delay nonlinear systems in nonstrict-feedback form. Firstly, an adaptive output feedback fuzzy backstepping-based control approach is proposed for the switched nonstrict-feedback system. Furthermore, fuzzy logic systems (FLSs) are utilized to model the unknown nonlinear system functions, and backstepping and adaptive technique are applied to construct output feedback controllers for all switched subsystems. The proposed controllers insure that all of the switched signals in the whole closed-loop system are semi-globally uniformly ultimately bounded. In the end, simulation results are given to show the effectiveness of the obtained method.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129531397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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