Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053924
Shi Liu, Tehuan Chen, Chao Xu
Continuous stirred tank reactor (CSTR) is one of the most common industrial equipment in petroleum and chemical industry, and is widely used in regrouping, fermentation engineering and additive preparation. In general, CSTR is used to prepare a fixed concentration of the output product. Accurate and fast monitoring of the changes in the state quantities of the CSTR chemical reaction process becomes the most important aspect before implementing excellent control. This paper presents a neural network observer with a residual network as the core component. In addition, the operations of the neural network are also matrixed to isolate the nonlinearities as much as possible. Finally we conduct numerical experiments in MATLAB R2018b based on SIMULINK framework to verify the feasibility of our strategy.
{"title":"A CSTR State Observer Based on Residual Neural Network","authors":"Shi Liu, Tehuan Chen, Chao Xu","doi":"10.1109/ICCR55715.2022.10053924","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053924","url":null,"abstract":"Continuous stirred tank reactor (CSTR) is one of the most common industrial equipment in petroleum and chemical industry, and is widely used in regrouping, fermentation engineering and additive preparation. In general, CSTR is used to prepare a fixed concentration of the output product. Accurate and fast monitoring of the changes in the state quantities of the CSTR chemical reaction process becomes the most important aspect before implementing excellent control. This paper presents a neural network observer with a residual network as the core component. In addition, the operations of the neural network are also matrixed to isolate the nonlinearities as much as possible. Finally we conduct numerical experiments in MATLAB R2018b based on SIMULINK framework to verify the feasibility of our strategy.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"122 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123575239","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053864
Yansui Song, Shuai Liang, Erzhuo Niu, Bin Xu
This paper investigates the trajectory optimization and tracking control for the perch maneuver of a fixed-wing unmanned aerial vehicle (UAV). An important aspect of the perch maneuver is that it provides a fast landing for UAVs on fixed points, which could be useful to solve the problem of landing dornes on warship or in tight areas. Optimal trajectory optimization is one of the main concerns of the technology, which is optimised for the shortest trajectory length and minimal energy consumption of the actuator in this paper. In addition, high-precision trajectory tracking control is required, but it is difficult due to the contradiction between variable model parameters and high-precision trajectory tracking control at high angles of attack flight. Toward this end, we developed a cascade incremental nonlinear dynamic inverse (INDI) controller which has a great robustness to the model uncertainties. As a result of simulation, it is verified that the INDI controller can maintain high trajectory tracking accuracy even at a large model deviation, and that it has a better control performance than a linear quadratic controller.
{"title":"A Perched Landing Control Method Based on Incremental Nonlinear Dynamic Inverse","authors":"Yansui Song, Shuai Liang, Erzhuo Niu, Bin Xu","doi":"10.1109/ICCR55715.2022.10053864","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053864","url":null,"abstract":"This paper investigates the trajectory optimization and tracking control for the perch maneuver of a fixed-wing unmanned aerial vehicle (UAV). An important aspect of the perch maneuver is that it provides a fast landing for UAVs on fixed points, which could be useful to solve the problem of landing dornes on warship or in tight areas. Optimal trajectory optimization is one of the main concerns of the technology, which is optimised for the shortest trajectory length and minimal energy consumption of the actuator in this paper. In addition, high-precision trajectory tracking control is required, but it is difficult due to the contradiction between variable model parameters and high-precision trajectory tracking control at high angles of attack flight. Toward this end, we developed a cascade incremental nonlinear dynamic inverse (INDI) controller which has a great robustness to the model uncertainties. As a result of simulation, it is verified that the INDI controller can maintain high trajectory tracking accuracy even at a large model deviation, and that it has a better control performance than a linear quadratic controller.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121611975","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053853
Qingyun Wang, Li Yan, Zhenfeng Cui
The main technical challenges in the operation of automated warehouses with two-end access platforms are related to low operational efficiency and racks instability. This paper proposed a modified mathematical model with the optimization objectives of improving the handling efficiency of the stacker crane, reducing the center of gravity of the goods and approaching the quality of the goods in the same aisle. Meanwhile, an improved genetic algorithm based on cosine adaptive is used to optimize the objective function. The findings demonstrate that the developed mathematical model can successfully optimize the warehouse level and that the improved genetic algorithm is more effective than the conventional adaptive algorithm at resolving the allocation issue in the double-access automated warehouse.
{"title":"Optimization of Two-end Access Platform Automated Warehouse Storage Allocation","authors":"Qingyun Wang, Li Yan, Zhenfeng Cui","doi":"10.1109/ICCR55715.2022.10053853","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053853","url":null,"abstract":"The main technical challenges in the operation of automated warehouses with two-end access platforms are related to low operational efficiency and racks instability. This paper proposed a modified mathematical model with the optimization objectives of improving the handling efficiency of the stacker crane, reducing the center of gravity of the goods and approaching the quality of the goods in the same aisle. Meanwhile, an improved genetic algorithm based on cosine adaptive is used to optimize the objective function. The findings demonstrate that the developed mathematical model can successfully optimize the warehouse level and that the improved genetic algorithm is more effective than the conventional adaptive algorithm at resolving the allocation issue in the double-access automated warehouse.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114140441","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053888
H. Huang, Ding Wang, Junlong Wu, Lingzhi Hu
This paper develops a novel value iteration (VI) scheme and an online VI algorithm, to address the discounted optimal control problems of affine discrete-time nonlinear systems. First, we provide the derivation of the novel VI. Second, we analyze the convergence and monotonicity of the iterative value function sequence, as well as the admissibility of the iterative control. Third, based on the theory of the attraction domain and the novel VI scheme, an online VI algorithm is proposed to implement the stability analysis of the controlled system. It is worth noting that the current control during the online control stage is determined by the location of the current state. Finally, a simulation example is involved to demonstrate the performance of the developed algorithms.
{"title":"Innovative Discounted Optimal Control Design via Offline and Online Formulations for Affine Systems","authors":"H. Huang, Ding Wang, Junlong Wu, Lingzhi Hu","doi":"10.1109/ICCR55715.2022.10053888","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053888","url":null,"abstract":"This paper develops a novel value iteration (VI) scheme and an online VI algorithm, to address the discounted optimal control problems of affine discrete-time nonlinear systems. First, we provide the derivation of the novel VI. Second, we analyze the convergence and monotonicity of the iterative value function sequence, as well as the admissibility of the iterative control. Third, based on the theory of the attraction domain and the novel VI scheme, an online VI algorithm is proposed to implement the stability analysis of the controlled system. It is worth noting that the current control during the online control stage is determined by the location of the current state. Finally, a simulation example is involved to demonstrate the performance of the developed algorithms.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117064615","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053932
Jiawei Zhuang, Shiguo Peng, Yonghua Wang
This article addresses the secure leader-following consensus (SLFC) problem of nonlinear stochastic multi-agent systems, which suffer from randomly occurring uncertainties, stochastic disturbances and deception attacks. As a typical type of deception attacks, randomly occurring stealthy false data-injection (FDI) attacks imply that sensor-to-controller channels are probably injected with false signals by adversaries intending to damage consensus. The malicious attacker's behavior can be measured by the Bernoulli distribution variable. By jointly employing the Lyapunov function, the linear matrix inequality method and the definition of average impulsive interval, several sufficient conditions with less conservative are derived, which means that impulsive control scheme can ensure the achievement of SLFC within a given error bound. Finally, one simple simulation example is reported to verify the reliability and effectiveness of our developed results.
{"title":"Secure Consensus of Stochastic Multi-agent Systems Subject to Deception Attacks via Impulsive Control","authors":"Jiawei Zhuang, Shiguo Peng, Yonghua Wang","doi":"10.1109/ICCR55715.2022.10053932","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053932","url":null,"abstract":"This article addresses the secure leader-following consensus (SLFC) problem of nonlinear stochastic multi-agent systems, which suffer from randomly occurring uncertainties, stochastic disturbances and deception attacks. As a typical type of deception attacks, randomly occurring stealthy false data-injection (FDI) attacks imply that sensor-to-controller channels are probably injected with false signals by adversaries intending to damage consensus. The malicious attacker's behavior can be measured by the Bernoulli distribution variable. By jointly employing the Lyapunov function, the linear matrix inequality method and the definition of average impulsive interval, several sufficient conditions with less conservative are derived, which means that impulsive control scheme can ensure the achievement of SLFC within a given error bound. Finally, one simple simulation example is reported to verify the reliability and effectiveness of our developed results.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116394762","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053881
Yuge Xu, Zixing Guo, Xie Zhang, Chuanlong Lv
Aluminum profiles are widely used in many industries with good characteristics. Surface defects of aluminum profiles will affect the quality, reliability and safety of products. In recent years, deep learning has been applied in aluminum profile surface defect detection. However, there are still some problems unsolved. The tiny and narrow defects are easily ignored in feature extraction. The length-width ratio of different aluminum surface defects varies widely, but the fixed anchor boxes in traditional deep learning algorithms will easily miss defects. Due to the lack of training on background images, some backgrounds are easily misidentified as defects. To address these problems, a novel Cascade R-CNN network with deformable convolution, guided anchoring and sample augmentation (GAE-Cascade R-CNN model) is proposed. The deformable convolution enhances the feature extraction ability of the network. The guided anchoring reduces the missed detection by automatically generating anchors to match narrow defects. The sample augmentation effectively reduces missed defect detection by training a large number of background images. The experimental results show that the proposed GAE-Cascade R-CNN model can achieve accuracy of 98.85% for identification and mean average precision (mAP) of 80.55% for surface defect detection of aluminum profiles. The performance of the proposed network outperforms other deep learning methods in terms of both missed detection rate and false detection rate.
{"title":"Research on Surface Defect Detection of Aluminum Based on Improved Cascade R-CNN","authors":"Yuge Xu, Zixing Guo, Xie Zhang, Chuanlong Lv","doi":"10.1109/ICCR55715.2022.10053881","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053881","url":null,"abstract":"Aluminum profiles are widely used in many industries with good characteristics. Surface defects of aluminum profiles will affect the quality, reliability and safety of products. In recent years, deep learning has been applied in aluminum profile surface defect detection. However, there are still some problems unsolved. The tiny and narrow defects are easily ignored in feature extraction. The length-width ratio of different aluminum surface defects varies widely, but the fixed anchor boxes in traditional deep learning algorithms will easily miss defects. Due to the lack of training on background images, some backgrounds are easily misidentified as defects. To address these problems, a novel Cascade R-CNN network with deformable convolution, guided anchoring and sample augmentation (GAE-Cascade R-CNN model) is proposed. The deformable convolution enhances the feature extraction ability of the network. The guided anchoring reduces the missed detection by automatically generating anchors to match narrow defects. The sample augmentation effectively reduces missed defect detection by training a large number of background images. The experimental results show that the proposed GAE-Cascade R-CNN model can achieve accuracy of 98.85% for identification and mean average precision (mAP) of 80.55% for surface defect detection of aluminum profiles. The performance of the proposed network outperforms other deep learning methods in terms of both missed detection rate and false detection rate.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127624495","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053849
Xiaoxiao Li, Yinhe Wang, Shengping Li
In this research, the model following adaptive control problem for the complex dynamical networks with adaptive coupling is investigated. Firstly, from the large-scale system perspective, the complex dynamical networks studied in this paper is composed of many nodes coupled with each other, where each node is a dynamic basic unit with detailed content, which is modeled by the vector differential equation. Next, based on the Lyapunov stability theory, an appropriate adaptive control scheme and the adaptive coupling are designed for the controller plant, so that the controlled plant can asymptotically track its model following target. Furthermore, each node has a different model following target, which is actually achieve multi-target tracking control. Finally, numerical simulation is given to verify the effectiveness and correctness of the control scheme proposed in this paper.
{"title":"Model Following Adaptive Control of Complex Dynamical Networks with the Adaptive Coupling","authors":"Xiaoxiao Li, Yinhe Wang, Shengping Li","doi":"10.1109/ICCR55715.2022.10053849","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053849","url":null,"abstract":"In this research, the model following adaptive control problem for the complex dynamical networks with adaptive coupling is investigated. Firstly, from the large-scale system perspective, the complex dynamical networks studied in this paper is composed of many nodes coupled with each other, where each node is a dynamic basic unit with detailed content, which is modeled by the vector differential equation. Next, based on the Lyapunov stability theory, an appropriate adaptive control scheme and the adaptive coupling are designed for the controller plant, so that the controlled plant can asymptotically track its model following target. Furthermore, each node has a different model following target, which is actually achieve multi-target tracking control. Finally, numerical simulation is given to verify the effectiveness and correctness of the control scheme proposed in this paper.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"212 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122454726","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053859
Hanjun Xie, Qin-ruo Wang
Aiming at the dynamic coupling problem of the dual-drive motors caused by the position change of heavy-load working head on gantry stage, this paper establishes an accurate electromechanical mathematical model for rigid-flexible coupling characteristics of the platform based on first principles. The model includes the crossbeam's linear motion and rotational motion of the non-constant moment of inertia ${J}$, and the cross-coupling force between the dual drive motors is quantified by defining the virtual centroid of the crossbeam. Finally, the effectiveness of the model is verified by the frequency response experiment of a actual system.
{"title":"Coupling Modeling Analysis of Synchronous Direct-Drive Gantry Laser Cutting Stage with Heavy-Load","authors":"Hanjun Xie, Qin-ruo Wang","doi":"10.1109/ICCR55715.2022.10053859","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053859","url":null,"abstract":"Aiming at the dynamic coupling problem of the dual-drive motors caused by the position change of heavy-load working head on gantry stage, this paper establishes an accurate electromechanical mathematical model for rigid-flexible coupling characteristics of the platform based on first principles. The model includes the crossbeam's linear motion and rotational motion of the non-constant moment of inertia ${J}$, and the cross-coupling force between the dual drive motors is quantified by defining the virtual centroid of the crossbeam. Finally, the effectiveness of the model is verified by the frequency response experiment of a actual system.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124966912","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053897
Zhaofeng Chen
Animals control is an important task for the safe operation of substations. Aiming at the problems existing in the control of small animals, with the superior prediction ability of machine learning, a prediction model of small animals hazard grade is proposed, which combines gradient boosting decision (GBDT) and logistic regression (LR) algorithm. The model combined substation operation and maintenance data with local meteorological data, performs features screening by calculating the variance value, and achieves classes balance by using sampling technology. And finally the model achieves the prediction of small animals hazard grade in substation. By using different data sets and not using GBDT algorithm to train the model, the prediction results are compared and analyzed. The proposed model is better in all prediction performance indicators, which verifies the validity of the method.
{"title":"Application of Small Animals Control in Substation Based on GBDT and LR Fusion Algorithm","authors":"Zhaofeng Chen","doi":"10.1109/ICCR55715.2022.10053897","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053897","url":null,"abstract":"Animals control is an important task for the safe operation of substations. Aiming at the problems existing in the control of small animals, with the superior prediction ability of machine learning, a prediction model of small animals hazard grade is proposed, which combines gradient boosting decision (GBDT) and logistic regression (LR) algorithm. The model combined substation operation and maintenance data with local meteorological data, performs features screening by calculating the variance value, and achieves classes balance by using sampling technology. And finally the model achieves the prediction of small animals hazard grade in substation. By using different data sets and not using GBDT algorithm to train the model, the prediction results are compared and analyzed. The proposed model is better in all prediction performance indicators, which verifies the validity of the method.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127962202","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 : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053887
Shibo Na, Ruizhuo Song
In this paper, we proposed an adaptive dynamic programming (ADP) algorithm for discrete time stochastic linear quadratic game without system dynamics. Firstly, we described the problem and converted it into a deterministic form. Then, we solved the Bellman equation to obtain the control gain matrix and disturbance gain matrix when the system dynamics were known. After that, we implemented the ADP algorithm with unknown system through neural networks. Model network, action network, disturbance network and critic network were used to approximate the system model, control gain matrix, disturbance gain matrix and value function respectively. Finally, a simulation example was given to verify the effectiveness of the algorithm.
{"title":"Stochastic Linear Quadratic Game for Discrete-time Systems Based-on Adaptive Dynamic Programming","authors":"Shibo Na, Ruizhuo Song","doi":"10.1109/ICCR55715.2022.10053887","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053887","url":null,"abstract":"In this paper, we proposed an adaptive dynamic programming (ADP) algorithm for discrete time stochastic linear quadratic game without system dynamics. Firstly, we described the problem and converted it into a deterministic form. Then, we solved the Bellman equation to obtain the control gain matrix and disturbance gain matrix when the system dynamics were known. After that, we implemented the ADP algorithm with unknown system through neural networks. Model network, action network, disturbance network and critic network were used to approximate the system model, control gain matrix, disturbance gain matrix and value function respectively. Finally, a simulation example was given to verify the effectiveness of the algorithm.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128009250","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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