Systems Science & Control Engineering最新文献

{"title":"Fractional-order SMC controller for mobile robot trajectory tracking under actuator fault","authors":"Minghuang Qin, S. Dian, Bin Guo, Xu Tao, Tao Zhao","doi":"10.1080/21642583.2021.2023683","DOIUrl":"https://doi.org/10.1080/21642583.2021.2023683","url":null,"abstract":"In this paper, aiming at the actuator fault-tolerant trajectory tracking problem of two-wheeled differential-driven mobile robots, a super-twisting fractional-order sliding mode fault-tolerant control method combined with a fault observer is proposed. The method not only ensures the pose tracking of the robot in normal condition but also guarantees the tracking performance while the fault occurs. The proposed method mainly includes: A fractional-order sliding mode surface which improves the transient response is utilized to design the fault-tolerant controller, and the super twisting reaching algorithm is adopted to reduce the chattering; A fault observer is designed to estimate the fault value, ensures system stability and safety through real-time compensation. Finally, the proposed fault-tolerant control method is verified by numerical simulation. The results show that the method proposed in this paper can effectively reduce the impact of actuator fault and ensure trajectory tracking performance. And the advantage of the control strategy over the general sliding mode controller is that compared with the integer-order sliding mode control (IOSMC), the fractional-order sliding mode control (FOSMC) we designed in this paper converges all the error states to zero faster, and the tracking error chattering is smaller.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49207044","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}

{"title":"Bone age assessment method based on fine-grained image classification using multiple regions of interest","authors":"Keji Mao, Wei Lu, Kunxiu Wu, Jiafa Mao, Guanglin Dai","doi":"10.1080/21642583.2021.2018669","DOIUrl":"https://doi.org/10.1080/21642583.2021.2018669","url":null,"abstract":"Bone age assessment is commonly used to determine the growth status and growth potential of children. In this paper, the bone age assessment is regarded as a fine-grained image classification problem as bone age assessment is usually performed on radiographs of the left hand. An end-to-end bone age assessment model was proposed. This model is composed of four parts: feature extractor, Region of Interest (ROI) selection subnet, guidance subnet, and assessment subnet. Feature extractor is implemented based on Convolutional Neural Networks (CNNs), ResNet50 was used to extract image features. ROI selection subnet is used to select multiple informative ROIs that contain representative images features in the radiograph. Guidance subnet can guide the ROI selection subnet to select ROI more appropriately. Assessment subnet is used for bone age assessment by utilizing the extracted image features. The proposed model can extract the most informative ROIs in the radiographs, and use these ROIs to improve the accuracy of bone age assessment. In this paper, the bone age assessment model is tested on a public data set. The experimental results show that the proposed bone age assessment model has the highest accuracy, and the Mean Absolute Error (MAE) reaches 6.65 months.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47407330","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}

{"title":"Frequency performance analysis of proportional integral-type active disturbance rejection generalized predictive control for time delay systems","authors":"Jia Ren, Zengqiang Chen, Mingwei Sun, Qinglin Sun","doi":"10.1080/21642583.2021.2020182","DOIUrl":"https://doi.org/10.1080/21642583.2021.2020182","url":null,"abstract":"To improve the performance of the Active Disturbance Rejection Control (ADRC) in systems which have large time delay, reduce online computation for Proportional Integral-type Generalized Predictive Control (PI-GPC) method, the Proportional Integral-type Active Disturbance Rejection Generalized Predictive Control (PI-ADRGPC) based on Controlled Auto Regression and Moving Average (CARMA) model is designed. The frequency domain analysis method is used to analyse the stability of the PI-ADRGPC based on CARMA model. By using the open-loop transfer function of the PI-GPC discrete form, the influence of parameter changes on the PI-ADRGPC performance is analysed. The performance of the PI-ADRGPC and ADRC algorithm is compared through the application in a second-order time delay system and distillation column system. The research results show that compared with the ADRC algorithm, the PI-ADRGPC method has a shorter rise time and better performance.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49076389","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}

{"title":"Fuzzy fractional-order PID control for two-wheeled self-balancing robots on inclined road surface","authors":"Jiawen Zhang, Tao Zhao, Bin Guo, S. Dian","doi":"10.1080/21642583.2021.2001768","DOIUrl":"https://doi.org/10.1080/21642583.2021.2001768","url":null,"abstract":"Two-wheeled self-balancing robots (TWSBR) is a highly nonlinear and inherently unstable under-driving system. When controlling its movement on an inclined surface, it is more difficult than when it is on a level road. This paper proposes a fuzzy fractional-order PID (FFOPID) controller for the motion control of a TWSBR system in an inclined environment. The control goal of TWSBR is to realize the wheel position control and to stabilize the non-vertical direction of intermediate body (IB). Finally, we compare the control effect of the proposed FFOPID controller with that of the integer-order PID controller, the fuzzy PID (FPID) controller, and the fractional-order PID (FOPID) controller when TWSBR moving on the inclined plane. The simulation results show that the FFOPID controller has better control performance and anti-interference ability.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49656588","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}

{"title":"Shared control of ship autopilots and human pilots for maritime autonomous surface ship in the presence of actuator anomalies","authors":"Minghao Ruan, Anqing Wang, Dan Wang","doi":"10.1080/21642583.2021.2010618","DOIUrl":"https://doi.org/10.1080/21642583.2021.2010618","url":null,"abstract":"This paper investigates the heading control problem of maritime autonomous surface ships (MASSs) in the presence of actuator anomalies. A shared control framework that includes a ship autopilot and a human pilot, is constructed to realize the accurate tracking of the time-varying command signals. Specifically, the human pilot is responsible for high-level decision making such as anomaly estimation, anomaly correction and monitoring analysis, and the ship autopilot is responsible for a low-level task of command following. With the proposed shared control framework, the ability of the ship autopilot can be significantly enhanced compared to entirely automated tracking. Through Lyapunov stability analysis, it is proven that the tracking error is ultimately bounded, while all the signals of the closed-loop system remain bounded. Finally, a simulation example is presented to prove the effectiveness of the proposed shared control architecture for MASSs under actuator anomalies.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45386435","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}

{"title":"Observer-based event-triggered control and application in active suspension vehicle systems","authors":"Wei Zhang, XiaoDan Fan","doi":"10.1080/21642583.2021.1998933","DOIUrl":"https://doi.org/10.1080/21642583.2021.1998933","url":null,"abstract":"This paper focuses on event-trigger control of automotive suspension systems. Firstly, fuzzy T-S systems which suitable for automobile suspension systems are studied. Parameter uncertainties and disturbances are included in the fuzzy T-S systems. Secondly, based on linear matrix inequalities (LMIs) and Lyapunov function, the conditions for the stability of fuzzy T-S systems are given. In the meantime, the controller and observer of the fuzzy T-S systems are designed. Finally, the theory is applied to the automotive suspension systems in the simulation.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48099314","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}

{"title":"Robust fuzzy dynamic surface formation control for underactuated ships using MLP and LFG","authors":"Shang Liu, Guoqing Zhang, Wenjun Zhang, Xianku Zhang","doi":"10.1080/21642583.2021.1997669","DOIUrl":"https://doi.org/10.1080/21642583.2021.1997669","url":null,"abstract":"This note deals with the leader-following formation problem for multiple underactuated ships in the presence of structure uncertainties and the time-varying parameterized disturbances. Following this ideology, a novel robust fuzzy dynamic surface formation control algorithm is proposed by fusing of the dynamic surface control (DSC), minimal learning parameter (MLP) and low frequency gain-learning (LFG). In the control algorithm, the intermediate virtual control laws do not appear in the finally actual control effort, and only two fuzzy type approximators are introduced to compensate the model uncertainties and the external disturbances, which can effectively overcome the constraints of ‘explosion of complexity’ and ‘curse of dimensionality’ in the traditional approximation-based algorithm. Unlike the current DSC technique, no filter errors are required to be stabilized in the Lyapunov function by virtue of the filter compensation signal, which could optimize the calculation of stabilization analysis. Furthermore, benefiting from the LFG technique, the robustness and applicability of the proposed control algorithm can be improved. Based on the Lyapunov theory analysis, all signals of the closed-loop control system can be guaranteed to be semi-global uniformly ultimately bounded (SGUUB). Finally, the simulated experiment is provided to verify the effectiveness and superiority of the proposed control scheme.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46237291","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}

{"title":"Ship target detection of unmanned surface vehicle base on EfficientDet","authors":"Ronghui Li, Jinshan Wu, Liang Cao","doi":"10.1080/21642583.2021.1990159","DOIUrl":"https://doi.org/10.1080/21642583.2021.1990159","url":null,"abstract":"The autonomous navigation of unmanned surface vehicles (USV) depends mainly on effective ship target detection to the nearby water area. The difficulty of target detection for USV derives from the complexity of the external environment, such as the light reflection and the cloud or mist shield. Accordingly, this paper proposes a target detection technology for USV on the basis of the EfficientDet algorithm. The ship features fusion is performed by Bi-directional Feature Pyra-mid Network (BiFPN), in which the pre-trained EfficientNet via ImageNet is taken as the backbone network, then the detection speed is increased by group normalization. Compared with the Faster-RCNN and Yolo V3, the ship target detection accuracy is greatly improved to 87.5% in complex environments. The algorithm can be applied to the identification of dynamic targets on the sea, which provides a key reference for the autonomous navigation of USV and the military threats assessment on the sea surface.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48501637","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}

{"title":"A method for unmanned vessel autonomous collision avoidance based on model predictive control","authors":"Shengwei Xing, Hongwei Xie, Wenjun Zhang","doi":"10.1080/21642583.2021.1986752","DOIUrl":"https://doi.org/10.1080/21642583.2021.1986752","url":null,"abstract":"Aiming at the problem of autonomous collision avoidance of unmanned vessels in the case of multiple vessels encountering at sea, this paper proposes a method for collision avoidance of vessels in open water based on the Mathematical Model Group (MMG) vessel motion mathematical model. This method uses Model Predictive Control (MPC) model algorithm, and considers vessel maneuverability and the International Regulations for Preventing Collision at Sea, 1972 (COLREGs), and uses fuzzy mathematics to analyze the collision risk of vessels during navigation, and then constructs the evaluation function of the collision avoidance algorithm. The vessel's autonomous collision avoidance is realized. The simulation results show that the algorithm can solve the problem of autonomous vessel collision avoidance in the case of multi-vessel encounters in open water, which verifies the effectiveness of the algorithm.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48629486","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}

{"title":"Heart rate control using first- and second-order models during treadmill exercise.","authors":"Hanjie Wang,&nbsp;Kenneth J Hunt","doi":"10.1080/21642583.2021.1976304","DOIUrl":"https://doi.org/10.1080/21642583.2021.1976304","url":null,"abstract":"<p><p>Heart rate control using first- and second-order models was compared using a novel control design strategy which shapes the input sensitivity function. Ten participants performed two feedback control test series on a treadmill with square wave and constant references. Using a repeated measures, counterbalanced study design, each series compared controllers C1 and C2 based on first- and second-order models, respectively. In the first series, tracking accuracy root-mean-square tracking error (RMSE) was not significantly lower for C2: 2.59 bpm vs. 2.69 bpm (mean, C1 vs. C2), <i>p</i> = 0.79. But average control signal power was significantly higher for C2: <math><mn>11.29</mn> <mo>×</mo> <msup><mn>10</mn> <mrow><mo>-</mo> <mn>4</mn></mrow> </msup> <mspace></mspace> <msup><mrow><mi>m</mi></mrow> <mn>2</mn></msup> <mrow><mo>/</mo></mrow> <msup><mrow><mi>s</mi></mrow> <mn>2</mn></msup> </math> vs. <math><mn>27.91</mn> <mo>×</mo> <msup><mn>10</mn> <mrow><mo>-</mo> <mn>4</mn></mrow> </msup> <mspace></mspace> <msup><mrow><mi>m</mi></mrow> <mn>2</mn></msup> <mrow><mo>/</mo></mrow> <msup><mrow><mi>s</mi></mrow> <mn>2</mn></msup> </math> , <math><mi>p</mi> <mo>=</mo> <mn>3.1</mn> <mo>×</mo> <msup><mn>10</mn> <mrow><mo>-</mo> <mn>10</mn></mrow> </msup> </math> . In the second series, RMSE was also not significantly lower for C2: 1.99 bpm vs. 1.94 bpm, <i>p</i> = 0.39; but average control signal power was again significantly higher for C2: <math><mn>2.20</mn> <mo>×</mo> <msup><mn>10</mn> <mrow><mo>-</mo> <mn>4</mn></mrow> </msup> <mspace></mspace> <msup><mrow><mi>m</mi></mrow> <mn>2</mn></msup> <mrow><mo>/</mo></mrow> <msup><mrow><mi>s</mi></mrow> <mn>2</mn></msup> </math> vs. <math><mn>2.78</mn> <mo>×</mo> <msup><mn>10</mn> <mrow><mo>-</mo> <mn>4</mn></mrow> </msup> <mspace></mspace> <msup><mrow><mi>m</mi></mrow> <mn>2</mn></msup> <mrow><mo>/</mo></mrow> <msup><mrow><mi>s</mi></mrow> <mn>2</mn></msup> </math> , <i>p</i> = 0.045. The results provide no evidence that controllers based on second-order models lead to better tracking accuracy, despite the finding that they are significantly more dynamic. Further investigation using a substantially larger sample size is warranted.</p>","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/95/34/TSSC_9_1976304.PMC8494276.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39505633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}