Pub Date : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990268
T. Bui, T. Bui, Tuyen Nguyen, Anh Nguyen, Liem Nguyen, Huan Luong
In Vietnam nowadays, smart grids have been built and operated recently in some regions when they enable detecting, reacting and pro-acting to changes in usage and multiple issues of the electricity system, and they may have self-healing capabilities. Therefore, study the correctness of the system design of a smart grid has to be carried out carefully before a grid being implement, especially in developing countries like Vietnam.In this research, we proposed a new approach to represent smart grids using Colored Petri Net (CPN). Our approach allows engineers to configure the net dynamically to verify the capacities of the net. The proposed approach also allows engineers to re-configure the system easily to adapt to any change in the grid without re-modelling the system from the grid topology. Additionally, when the state spaces of the nets constructed by the new approach are smaller than that of the conventional modelling approach, the verification for smart grid properties can overcome its ’inherently intractable’ drawback.
{"title":"Formal Modelling of Smart Grids: Configurability vs. Conventionality","authors":"T. Bui, T. Bui, Tuyen Nguyen, Anh Nguyen, Liem Nguyen, Huan Luong","doi":"10.1109/ICCAIS56082.2022.9990268","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990268","url":null,"abstract":"In Vietnam nowadays, smart grids have been built and operated recently in some regions when they enable detecting, reacting and pro-acting to changes in usage and multiple issues of the electricity system, and they may have self-healing capabilities. Therefore, study the correctness of the system design of a smart grid has to be carried out carefully before a grid being implement, especially in developing countries like Vietnam.In this research, we proposed a new approach to represent smart grids using Colored Petri Net (CPN). Our approach allows engineers to configure the net dynamically to verify the capacities of the net. The proposed approach also allows engineers to re-configure the system easily to adapt to any change in the grid without re-modelling the system from the grid topology. Additionally, when the state spaces of the nets constructed by the new approach are smaller than that of the conventional modelling approach, the verification for smart grid properties can overcome its ’inherently intractable’ drawback.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125862810","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990504
Nhung Nguyen Hong, H. N. Duc, Cuong Dao Manh, Giang Le Hoang Huong
The rapid increase of renewable energy resources such as wind and solar power leads to the development of microgrids, especially stand-alone microgrids that supply remote demand. However, operating these grids still faces many challenges due to wind speed and solar radiation uncertainties. Energy storage systems and demand response programs can be treated as effective solutions to ensure power balancing and reduce the system's operating cost. This paper proposes a stochastic optimization model to determine the optimal scheduling of a microgrid. The uncertainties in wind and solar power are taken into account in this model. The proposed model is implemented on a test system, and the impact of the energy storage system and demand response on the microgrid's scheduling is analyzed. Results indicate that the proposed model can be meaningful in real-world conditions.
{"title":"Optimal Planning of a Microgrid Considering Demand Response and Energy Storage System","authors":"Nhung Nguyen Hong, H. N. Duc, Cuong Dao Manh, Giang Le Hoang Huong","doi":"10.1109/ICCAIS56082.2022.9990504","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990504","url":null,"abstract":"The rapid increase of renewable energy resources such as wind and solar power leads to the development of microgrids, especially stand-alone microgrids that supply remote demand. However, operating these grids still faces many challenges due to wind speed and solar radiation uncertainties. Energy storage systems and demand response programs can be treated as effective solutions to ensure power balancing and reduce the system's operating cost. This paper proposes a stochastic optimization model to determine the optimal scheduling of a microgrid. The uncertainties in wind and solar power are taken into account in this model. The proposed model is implemented on a test system, and the impact of the energy storage system and demand response on the microgrid's scheduling is analyzed. Results indicate that the proposed model can be meaningful in real-world conditions.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128108243","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990429
Chuan Zhu, Jie Deng, Xingyue Long, Wei Zhang, Wei Yi
The multi-frame track-before-detect (MF-TBD) method has excellent detection performance for weak targets. However, the statistical characteristics of the merit function after accumulation of multiple consecutive frames are complex, and the setting of the constant false alarm threshold is difficult, especially when the background statistical characteristics are unknown and nonhomogeneous. This paper considers the robust target detection method for MF-TBD. The weak target detection in the merit function domain plane is modeled as binary classification of pixels on the plane. Due to the motivation of classifying pixel points, the U-Net network is selected. Then we improve U-Net into a novel DBU-Net network structure, and train DBU-Net through different merit function domain sample sets. The DBU- Net can effectively detect target in the merit function domain, although the background statistics are unknown and nonhomogeneous. The simulation results demonstrate the superiority and robustness of the detection performance of the method.
{"title":"DBU-Net Based Robust Target Detection for Multi-Frame Track-Before-Detect Method","authors":"Chuan Zhu, Jie Deng, Xingyue Long, Wei Zhang, Wei Yi","doi":"10.1109/ICCAIS56082.2022.9990429","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990429","url":null,"abstract":"The multi-frame track-before-detect (MF-TBD) method has excellent detection performance for weak targets. However, the statistical characteristics of the merit function after accumulation of multiple consecutive frames are complex, and the setting of the constant false alarm threshold is difficult, especially when the background statistical characteristics are unknown and nonhomogeneous. This paper considers the robust target detection method for MF-TBD. The weak target detection in the merit function domain plane is modeled as binary classification of pixels on the plane. Due to the motivation of classifying pixel points, the U-Net network is selected. Then we improve U-Net into a novel DBU-Net network structure, and train DBU-Net through different merit function domain sample sets. The DBU- Net can effectively detect target in the merit function domain, although the background statistics are unknown and nonhomogeneous. The simulation results demonstrate the superiority and robustness of the detection performance of the method.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128491871","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}
This paper presents a multi-UAV coverage strategy using a V-shaped formation with requirements to maximize the sweep coverage rate and minimize flight time. The leader-follower model-based strategy combines a V-shaped formation control at which behavior-based control is used to allow the UAVs to follow virtual points on a virtual V-shaped structure created by the leader UAV, and an optimal coverage path planner to provide a single path in back-and-forth pattern for the formation. We have evaluated our proposed approach in simulations and achieved high performance in both two the stated metrics.
{"title":"Multi-UAV Coverage Strategy with V-shaped Formation for Patrol and Surveillance","authors":"Hung Pham Quang, Truong Nguyen Dam, Vu Nguyen Hoang, Hung Pham Duy","doi":"10.1109/ICCAIS56082.2022.9990236","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990236","url":null,"abstract":"This paper presents a multi-UAV coverage strategy using a V-shaped formation with requirements to maximize the sweep coverage rate and minimize flight time. The leader-follower model-based strategy combines a V-shaped formation control at which behavior-based control is used to allow the UAVs to follow virtual points on a virtual V-shaped structure created by the leader UAV, and an optimal coverage path planner to provide a single path in back-and-forth pattern for the formation. We have evaluated our proposed approach in simulations and achieved high performance in both two the stated metrics.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134183907","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990358
Nguyen Hai Phong, Dang Xuan Ba
In this paper, we develop a new predictive controller for tracking control problems of robotic manipulators. Internal dynamics of the robotic model are first modeled using proper neural networks under support of an output feedback control signal. A new model predictive control signal is next derived to realize the control objective in a robust manner. Novel adaptation laws are then proposed to activate the network learning in an effective way. Effectiveness of the proposed controller has been validated throughout intensive simulation results on two degree of freedom robot.
{"title":"A Robust Neural Predictive Control Approach for Robotic Manipulators with Online Learning Ability","authors":"Nguyen Hai Phong, Dang Xuan Ba","doi":"10.1109/ICCAIS56082.2022.9990358","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990358","url":null,"abstract":"In this paper, we develop a new predictive controller for tracking control problems of robotic manipulators. Internal dynamics of the robotic model are first modeled using proper neural networks under support of an output feedback control signal. A new model predictive control signal is next derived to realize the control objective in a robust manner. Novel adaptation laws are then proposed to activate the network learning in an effective way. Effectiveness of the proposed controller has been validated throughout intensive simulation results on two degree of freedom robot.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134235083","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990100
Khanh-Linh Dang, Bảo-Huy Nguyễn, M. C. Ta, J. Trovão, Thanh Vo-Duy
Induction motors (IMs) are among the most prevalent electrical motors in industry because of their simple structure and low cost. One of the challenges in operating this type of motor by the field oriented control (FOC) method is calculating its continually varying properties such as flux, resistance, and inductance. Despite significant advances in science and technology, there is currently no equipment that can directly measure them, making it difficult to apply traditional model-based control methods. The purpose of this study is to manipulate a sliding mode observer (SMO) for rotor flux. Based on the estimated value, a model free sliding mode controller (MFSMC) is utilized to perform the flux control strategies under different working conditions of the motor. The proposed approach of the IM drive system is modelled using Energetic Macroscopic Representation (EMR) and validated by simulation in Matlab/Simulink®.
{"title":"Sliding Mode Solution for Rotor Flux Control and Estimation of Induction Motors Using Energetic Macroscopic Representation","authors":"Khanh-Linh Dang, Bảo-Huy Nguyễn, M. C. Ta, J. Trovão, Thanh Vo-Duy","doi":"10.1109/ICCAIS56082.2022.9990100","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990100","url":null,"abstract":"Induction motors (IMs) are among the most prevalent electrical motors in industry because of their simple structure and low cost. One of the challenges in operating this type of motor by the field oriented control (FOC) method is calculating its continually varying properties such as flux, resistance, and inductance. Despite significant advances in science and technology, there is currently no equipment that can directly measure them, making it difficult to apply traditional model-based control methods. The purpose of this study is to manipulate a sliding mode observer (SMO) for rotor flux. Based on the estimated value, a model free sliding mode controller (MFSMC) is utilized to perform the flux control strategies under different working conditions of the motor. The proposed approach of the IM drive system is modelled using Energetic Macroscopic Representation (EMR) and validated by simulation in Matlab/Simulink®.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122220977","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990364
Aidan Blair, Amirali Khodadadian Gostar, Ruwan Tennakoon, A. Bab-Hadiashar, Xiaodong Li, Jennifer Palmer, R. Hoseinnezhad
This paper proposes a new sensor control algorithm for multi-target tracking applications within distributed sensor networks. In multi-target tracking applications, most sensor control algorithms are designed for centralized sensor networks, where there is a central processing node that is computationally inefficient. This paper first provides a conceptual and mathematical overview of the multi-sensor multi-target tracking framework, using random finite set (RFS) filters and sensor fusion. We will also provide an overview of the existing sensor control methods. We then explore coordinate descent-based sensor control and introduce a fully distributed algorithm utilizing coordinate descent and an information-theoretic objective function. This method is tested on synthetic data and compared to alternative methods. The results show that the proposed method outperforms equivalent independent multi-sensor control methods.
{"title":"Distributed Multi-Sensor Control for Multi-Target Tracking","authors":"Aidan Blair, Amirali Khodadadian Gostar, Ruwan Tennakoon, A. Bab-Hadiashar, Xiaodong Li, Jennifer Palmer, R. Hoseinnezhad","doi":"10.1109/ICCAIS56082.2022.9990364","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990364","url":null,"abstract":"This paper proposes a new sensor control algorithm for multi-target tracking applications within distributed sensor networks. In multi-target tracking applications, most sensor control algorithms are designed for centralized sensor networks, where there is a central processing node that is computationally inefficient. This paper first provides a conceptual and mathematical overview of the multi-sensor multi-target tracking framework, using random finite set (RFS) filters and sensor fusion. We will also provide an overview of the existing sensor control methods. We then explore coordinate descent-based sensor control and introduce a fully distributed algorithm utilizing coordinate descent and an information-theoretic objective function. This method is tested on synthetic data and compared to alternative methods. The results show that the proposed method outperforms equivalent independent multi-sensor control methods.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123792455","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990164
Nga Bui Thi Thuy, D. N. Bui, Manh Duong Phung, Hung Pham Duy
This study proposes an approach for establishing an optimal multihop ad-hoc network using multiple unmanned aerial vehicles (UAVs) to provide emergency communication in disaster areas. The approach includes two stages, one uses particle swarm optimization (PSO) to find optimal positions to deploy UAVs, and the other uses a behavior-based controller to navigate the UAVs to their assigned positions without colliding with obstacles in an unknown environment. Several constraints related to the UAVs’ sensing and communication ranges have been imposed to ensure the applicability of the proposed approach in real-world scenarios. A number of simulation experiments with data loaded from real environments have been conducted. The results show that our proposed approach is not only successful in establishing multihop ad-hoc routes but also meets the requirements for real-time deployment of UAVs.
{"title":"Deployment of UAVs for Optimal Multihop Ad-hoc Networks Using Particle Swarm Optimization and Behavior-based Control","authors":"Nga Bui Thi Thuy, D. N. Bui, Manh Duong Phung, Hung Pham Duy","doi":"10.1109/ICCAIS56082.2022.9990164","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990164","url":null,"abstract":"This study proposes an approach for establishing an optimal multihop ad-hoc network using multiple unmanned aerial vehicles (UAVs) to provide emergency communication in disaster areas. The approach includes two stages, one uses particle swarm optimization (PSO) to find optimal positions to deploy UAVs, and the other uses a behavior-based controller to navigate the UAVs to their assigned positions without colliding with obstacles in an unknown environment. Several constraints related to the UAVs’ sensing and communication ranges have been imposed to ensure the applicability of the proposed approach in real-world scenarios. A number of simulation experiments with data loaded from real environments have been conducted. The results show that our proposed approach is not only successful in establishing multihop ad-hoc routes but also meets the requirements for real-time deployment of UAVs.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114816346","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990185
P. Quan, Dang Xuan Ba, Cong-Doan Truong, Nguyen Phong Luu, Vuong Quang Huy, Nguyen Tu Duc
Unmanned aerial vehicles (UAVs, drones) have become one of the key machines/tools of the modern world in which they are widely employed to effectively enhance working performances in many fields of daily social life and manufacturing such as delivery, protecting wildlife, agricultural activities, academy, searching, rescue missions and military applications. To accomplish the given mission, the systems are required precise controllers with strong ability of adaptation and robustness. In this article, we present an adaptive robust nonlinear controller for position tracking control problems of a quadcopter system. The controller is structured with two control loops. In the inner loop, the attitude of the system is adjusted following desired signals using a proper combination of sliding-mode-backstepping control framework under nonlinear disturbance observers. The position control mission is realized by another nonlinear altitude control method. A new gain-learning mechanism is then proposed to improve both transient and steady-state control performances. Stability of the closed-loop system under time-varying disturbances is governed by Lyapunov theories. Effectiveness and feasibility of the proposed control approach were verified by comparative simulations.
{"title":"An Adaptive Robust Nonlinear Control Approach of a Quadcopter with Disturbance Observer","authors":"P. Quan, Dang Xuan Ba, Cong-Doan Truong, Nguyen Phong Luu, Vuong Quang Huy, Nguyen Tu Duc","doi":"10.1109/ICCAIS56082.2022.9990185","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990185","url":null,"abstract":"Unmanned aerial vehicles (UAVs, drones) have become one of the key machines/tools of the modern world in which they are widely employed to effectively enhance working performances in many fields of daily social life and manufacturing such as delivery, protecting wildlife, agricultural activities, academy, searching, rescue missions and military applications. To accomplish the given mission, the systems are required precise controllers with strong ability of adaptation and robustness. In this article, we present an adaptive robust nonlinear controller for position tracking control problems of a quadcopter system. The controller is structured with two control loops. In the inner loop, the attitude of the system is adjusted following desired signals using a proper combination of sliding-mode-backstepping control framework under nonlinear disturbance observers. The position control mission is realized by another nonlinear altitude control method. A new gain-learning mechanism is then proposed to improve both transient and steady-state control performances. Stability of the closed-loop system under time-varying disturbances is governed by Lyapunov theories. Effectiveness and feasibility of the proposed control approach were verified by comparative simulations.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116244596","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990560
Dung Manh Do, D. Hoang, NamHoai Nguyen, P. D. Nguyen
This article proposes a data-driven method for tracking control of the autonomous underwater vehicle (AUV) with matched disturbances and time-varying model’s uncertain parameters. The method is established by combining the conventional model reference control principle with a corresponding procedure for step-wise updating controller parameters so that the model error between the AUV and an appropriately chosen linear stable model converges to zero. The update procedure of controller parameters is created based on Lagrange interpolation technique, hence it acts entirely on the experimentally collected data from the AUV. The expected tracking performance by using this proposed data-driven controller has been theoretically authenticated and through numerical simulation.
{"title":"Data-Driven Output Regulation of Uncertain 6 DOF AUV via Lagrange Interpolation","authors":"Dung Manh Do, D. Hoang, NamHoai Nguyen, P. D. Nguyen","doi":"10.1109/ICCAIS56082.2022.9990560","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990560","url":null,"abstract":"This article proposes a data-driven method for tracking control of the autonomous underwater vehicle (AUV) with matched disturbances and time-varying model’s uncertain parameters. The method is established by combining the conventional model reference control principle with a corresponding procedure for step-wise updating controller parameters so that the model error between the AUV and an appropriately chosen linear stable model converges to zero. The update procedure of controller parameters is created based on Lagrange interpolation technique, hence it acts entirely on the experimentally collected data from the AUV. The expected tracking performance by using this proposed data-driven controller has been theoretically authenticated and through numerical simulation.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116988579","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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