Pub Date : 2024-07-24DOI: 10.1177/01423312241263673
H. Ghadiri, Hamed Khodadadi
This study introduces a Constrained Predictive Functional Controller (CPFC) designed for regulating chamber pressure in a coke furnace. While the traditional controllers face challenges posed by the system’s complex multi-input multi-output (MIMO) structure, cross-coupling, time delays, physical constraints, and uncertainties, this article’s approach realized set-point tracking and disturbance rejection, addressing model mismatches while considering constraints on system inputs, input variations, and outputs. To tackle the constrained Model Predictive Control (MPC) optimization problem and minimize the cost function, the Quantum Simultaneous Whale Optimization Algorithm (QSWOA) is employed. This meta-heuristic optimization method integrates quantum coding and simultaneous search with the whale optimization algorithm, enhancing convergence speed and precision. Furthermore, the performance of the proposed CPFC-QSWOA controller is assessed through simulations of the chamber pressure control of a Coke furnace. Results demonstrate the superiority of the CPFC-QSWOA approach, showcasing high precision and robustness, particularly in the face of uncertainties and disturbances.
{"title":"Predictive functional control for chamber pressure: A quantum simultaneous whale optimization approach","authors":"H. Ghadiri, Hamed Khodadadi","doi":"10.1177/01423312241263673","DOIUrl":"https://doi.org/10.1177/01423312241263673","url":null,"abstract":"This study introduces a Constrained Predictive Functional Controller (CPFC) designed for regulating chamber pressure in a coke furnace. While the traditional controllers face challenges posed by the system’s complex multi-input multi-output (MIMO) structure, cross-coupling, time delays, physical constraints, and uncertainties, this article’s approach realized set-point tracking and disturbance rejection, addressing model mismatches while considering constraints on system inputs, input variations, and outputs. To tackle the constrained Model Predictive Control (MPC) optimization problem and minimize the cost function, the Quantum Simultaneous Whale Optimization Algorithm (QSWOA) is employed. This meta-heuristic optimization method integrates quantum coding and simultaneous search with the whale optimization algorithm, enhancing convergence speed and precision. Furthermore, the performance of the proposed CPFC-QSWOA controller is assessed through simulations of the chamber pressure control of a Coke furnace. Results demonstrate the superiority of the CPFC-QSWOA approach, showcasing high precision and robustness, particularly in the face of uncertainties and disturbances.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1177/01423312241261747
Weijia Zheng, Xiaorong Li, Yangquan Chen, Ze-Hao Wu, Xiaohong Wang
Time-delay characteristics of various industrial processes may degrade the stability and dynamic performance of the control systems. Aiming at the problems of the existing methods in dealing with the time delay plant, a modified fractional-order proportional–integral–derivative (FOPID) controller for the first-order plus time-delay (FOPTD) system is developed. Assisted by a modified active disturbance rejection control (ADRC) scheme with increased observer bandwidth, the proposed FOPID controller inherently obtains good robustness to time-delay uncertainties and external disturbances. In addition, taking advantage of the fractional-order operator, the proposed controller can provide larger stability margin over the proportional–integral–derivative (PID) controller. By suitably establishing the relation between ADRC and FOPID controller parameters, the proposed controller can be analytically tuned based on the common design indices. A practical tuning guideline is developed according to frequency-domain characteristic analysis, making the proposed controller more acceptable to industrial application. The performance of the ADRC-based FOPID controller is tested by the control simulation of some typical FOPTD systems and a diesel engine speed regulation system. The efficiency of the ADRC-based FOPID controller is demonstrated by the comparisons with some existing controllers.
{"title":"Robust fractional-order PID controller assisted by active disturbance rejection control for the first-order plus time-delay systems","authors":"Weijia Zheng, Xiaorong Li, Yangquan Chen, Ze-Hao Wu, Xiaohong Wang","doi":"10.1177/01423312241261747","DOIUrl":"https://doi.org/10.1177/01423312241261747","url":null,"abstract":"Time-delay characteristics of various industrial processes may degrade the stability and dynamic performance of the control systems. Aiming at the problems of the existing methods in dealing with the time delay plant, a modified fractional-order proportional–integral–derivative (FOPID) controller for the first-order plus time-delay (FOPTD) system is developed. Assisted by a modified active disturbance rejection control (ADRC) scheme with increased observer bandwidth, the proposed FOPID controller inherently obtains good robustness to time-delay uncertainties and external disturbances. In addition, taking advantage of the fractional-order operator, the proposed controller can provide larger stability margin over the proportional–integral–derivative (PID) controller. By suitably establishing the relation between ADRC and FOPID controller parameters, the proposed controller can be analytically tuned based on the common design indices. A practical tuning guideline is developed according to frequency-domain characteristic analysis, making the proposed controller more acceptable to industrial application. The performance of the ADRC-based FOPID controller is tested by the control simulation of some typical FOPTD systems and a diesel engine speed regulation system. The efficiency of the ADRC-based FOPID controller is demonstrated by the comparisons with some existing controllers.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1177/01423312241257298
Yan-Ping Bu
This paper presents Krylov subspace model order reduction of linear dynamical systems with quadratic output. To reach this goal, the quadratic transfer function with two variables is taken into consideration. The Krylov subspaces are established at the finite and the infinite frequency points where both the one-sided and the two-sided projection cases are discussed. The moment matching is accordingly studied and the quadratic transfer function of the reduced system resulting from the two-sided projection case can match more moments. Finally, numerical results illustrate the performance of the proposed Krylov model order reduction methodology.
{"title":"Krylov subspace model order reduction of linear dynamical systems with quadratic output","authors":"Yan-Ping Bu","doi":"10.1177/01423312241257298","DOIUrl":"https://doi.org/10.1177/01423312241257298","url":null,"abstract":"This paper presents Krylov subspace model order reduction of linear dynamical systems with quadratic output. To reach this goal, the quadratic transfer function with two variables is taken into consideration. The Krylov subspaces are established at the finite and the infinite frequency points where both the one-sided and the two-sided projection cases are discussed. The moment matching is accordingly studied and the quadratic transfer function of the reduced system resulting from the two-sided projection case can match more moments. Finally, numerical results illustrate the performance of the proposed Krylov model order reduction methodology.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tower cranes are the main tool of the horizontal and vertical transportation for construction, which are always driven by operators slowly to prevent payloads from large swing, such that efficiency is low. To deal with the problem, a finite-time tracking control method based on fast command filters is proposed, which can eliminate the tracking error in finite time and restrain the swing at the same time. The asymptotic stability is proved by Lyapunov technique. Finally, the hardware experiment is carried out and compared with the existing methods on the self-built tower crane experimental platform, and the pole placement method is used to select control parameters. The effectiveness and superiority are verified by the experimental results.
{"title":"A tracking control method with the fast finite-time command filter for four degrees of freedom tower cranes","authors":"Cungen Liu, Shuo Meng, Xiaoping Liu, Yajing Zhao, Huanqing Wang, Chengdong Li","doi":"10.1177/01423312241259066","DOIUrl":"https://doi.org/10.1177/01423312241259066","url":null,"abstract":"Tower cranes are the main tool of the horizontal and vertical transportation for construction, which are always driven by operators slowly to prevent payloads from large swing, such that efficiency is low. To deal with the problem, a finite-time tracking control method based on fast command filters is proposed, which can eliminate the tracking error in finite time and restrain the swing at the same time. The asymptotic stability is proved by Lyapunov technique. Finally, the hardware experiment is carried out and compared with the existing methods on the self-built tower crane experimental platform, and the pole placement method is used to select control parameters. The effectiveness and superiority are verified by the experimental results.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1177/01423312241260916
Wangming Lu, Zhiyong Yu, Xuening Xu, Haijun Jiang
This paper discusses the prescribed-time leader-follower consensus and containment control problems for a class of nonlinear multi-agent systems with external disturbances. First, an event-triggered control protocol with sign function is proposed, which can ensure that all agents achieve consensus within a prescribed time. Second, as the sliding mode control has the advantage of good robustness to external disturbances, an improved event-triggered control protocol is designed by using the integral sliding mode control method and some sufficient conditions are derived for achieving the prescribed-time leader-follower consensus. Moreover, the prescribed-time containment control problem for multi-agent systems with multiple leaders is investigated by using the event-triggered control strategy. It is shown that Zeno behavior can be excluded in the above consensus issues by choosing parameters appropriately. Finally, several numerical examples are given to demonstrate the effectiveness and reliability of the proposed approaches.
{"title":"Prescribed-time leader-follower consensus and containment control for nonlinear multi-agent systems with event-triggered control protocols","authors":"Wangming Lu, Zhiyong Yu, Xuening Xu, Haijun Jiang","doi":"10.1177/01423312241260916","DOIUrl":"https://doi.org/10.1177/01423312241260916","url":null,"abstract":"This paper discusses the prescribed-time leader-follower consensus and containment control problems for a class of nonlinear multi-agent systems with external disturbances. First, an event-triggered control protocol with sign function is proposed, which can ensure that all agents achieve consensus within a prescribed time. Second, as the sliding mode control has the advantage of good robustness to external disturbances, an improved event-triggered control protocol is designed by using the integral sliding mode control method and some sufficient conditions are derived for achieving the prescribed-time leader-follower consensus. Moreover, the prescribed-time containment control problem for multi-agent systems with multiple leaders is investigated by using the event-triggered control strategy. It is shown that Zeno behavior can be excluded in the above consensus issues by choosing parameters appropriately. Finally, several numerical examples are given to demonstrate the effectiveness and reliability of the proposed approaches.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1177/01423312241261127
Olfa Yahya, Z. Lassoued, Zied Aboud, K. Abderrahim
Modeling of industrial production processes is becoming increasingly challenging due to their large number of variables. These variables often are highly correlated and introduce nonlinear and complex features. In this paper, we are interested to model an industrial dicalcium phosphate (DCP) drying process. Attempting to solve this issue is motivated by the need to improve several production conditions, such as minimizing the consumption of natural gas and reducing the pollution rate. In fact, applying an advanced control approach requires a dynamic model for the monitored plant. This work proposes a multivariable mathematical model for the DCP dryer within the Tunisian Chemical Group factory. A steady-state model has been reproduced using Aspen Plus software tool to implement the different functionalities of the system as well as involved reactions. Indeed, since the main operation in the drying process is the combustion reaction of the liquified petroleum gas (LPG) in the furnace that produce the necessary heat to reach a target value of temperature at the dryer outlet, we focus on determining a dynamic model for the furnace. To do so, we have proposed two approaches. The first is based on the Aspen dynamic tool. The second is based on the left matrix fraction description (LMFD) identification approach. The obtained results have been successfully validated using real measurements.
由于工业生产过程中存在大量变量，其建模工作正变得越来越具有挑战性。这些变量通常高度相关，并具有非线性和复杂的特征。在本文中，我们有兴趣对工业磷酸二钙（DCP）干燥过程进行建模。试图解决这一问题的动机是需要改善一些生产条件，如尽量减少天然气消耗和降低污染率。事实上，采用先进的控制方法需要为受监控的设备建立动态模型。这项工作为突尼斯化工集团工厂内的 DCP 干燥机提出了一个多变量数学模型。使用 Aspen Plus 软件工具重现了一个稳态模型，以实现系统的不同功能和相关反应。事实上，由于干燥过程中的主要操作是熔炉中液化石油气（LPG）的燃烧反应，该反应产生必要的热量以达到干燥器出口处的目标温度值，因此我们将重点放在确定熔炉的动态模型上。为此，我们提出了两种方法。第一种是基于 Aspen 动态工具。第二种是基于左矩阵分数描述 (LMFD) 识别方法。所获得的结果已通过实际测量成功验证。
{"title":"An experimentally validated model for a multivariate drying industrial process","authors":"Olfa Yahya, Z. Lassoued, Zied Aboud, K. Abderrahim","doi":"10.1177/01423312241261127","DOIUrl":"https://doi.org/10.1177/01423312241261127","url":null,"abstract":"Modeling of industrial production processes is becoming increasingly challenging due to their large number of variables. These variables often are highly correlated and introduce nonlinear and complex features. In this paper, we are interested to model an industrial dicalcium phosphate (DCP) drying process. Attempting to solve this issue is motivated by the need to improve several production conditions, such as minimizing the consumption of natural gas and reducing the pollution rate. In fact, applying an advanced control approach requires a dynamic model for the monitored plant. This work proposes a multivariable mathematical model for the DCP dryer within the Tunisian Chemical Group factory. A steady-state model has been reproduced using Aspen Plus software tool to implement the different functionalities of the system as well as involved reactions. Indeed, since the main operation in the drying process is the combustion reaction of the liquified petroleum gas (LPG) in the furnace that produce the necessary heat to reach a target value of temperature at the dryer outlet, we focus on determining a dynamic model for the furnace. To do so, we have proposed two approaches. The first is based on the Aspen dynamic tool. The second is based on the left matrix fraction description (LMFD) identification approach. The obtained results have been successfully validated using real measurements.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1177/01423312241259821
Jianfei Zheng, Xinyue Geng, Changhua Hu, Hong Pei, Zhengxin Zhang
Remaining useful life (RUL) prediction techniques based on degradation modeling to ensure the safety and reliability of stochastic degraded devices are of critical value. However, although the performance degradation of various devices in engineering practice is affected by multi-timescales, there are few RUL prediction methods for stochastic degraded devices with dual time scales in the existing literature. The research of prediction methods considering continuous and discrete time scales is blank. Toward this end, this paper proposes a novel prognostic method for nonlinear degradation devices based on the continuous-discrete dual time scales. First, the performance degradation with a discrete timescale is determined with a compound Poisson process and integrated into the diffusion process model to establish a nonlinear dual-timescale degradation model. Subsequently, the joint expression of the dual-timescale RUL distribution of the device in the first hitting time sense solves with threshold transformation. Finally, the effectiveness and superiority of the proposed method are verified through a numerical simulation and a gyroscope example. The experimental results show that the proposed method can provide more comprehensive information about the life distribution and effectively improve the accuracy of the RUL prediction.
{"title":"A novel prognostic method for degrading devices with nonlinear degradation processes indexed by both continuous and discrete time scales","authors":"Jianfei Zheng, Xinyue Geng, Changhua Hu, Hong Pei, Zhengxin Zhang","doi":"10.1177/01423312241259821","DOIUrl":"https://doi.org/10.1177/01423312241259821","url":null,"abstract":"Remaining useful life (RUL) prediction techniques based on degradation modeling to ensure the safety and reliability of stochastic degraded devices are of critical value. However, although the performance degradation of various devices in engineering practice is affected by multi-timescales, there are few RUL prediction methods for stochastic degraded devices with dual time scales in the existing literature. The research of prediction methods considering continuous and discrete time scales is blank. Toward this end, this paper proposes a novel prognostic method for nonlinear degradation devices based on the continuous-discrete dual time scales. First, the performance degradation with a discrete timescale is determined with a compound Poisson process and integrated into the diffusion process model to establish a nonlinear dual-timescale degradation model. Subsequently, the joint expression of the dual-timescale RUL distribution of the device in the first hitting time sense solves with threshold transformation. Finally, the effectiveness and superiority of the proposed method are verified through a numerical simulation and a gyroscope example. The experimental results show that the proposed method can provide more comprehensive information about the life distribution and effectively improve the accuracy of the RUL prediction.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1177/01423312241257297
Yiyu Shao, Qinrong Qian, Hua Wang
It is difficult to obtain the damage information on large slewing bearings only from vibration signals. In addition, deep learning models trained on old samples do not achieve high accuracy in new tasks. Therefore, this paper uses vibration, temperature, and torque signals of slewing bearings to build a model. Meanwhile, we add attention mechanism to capture internal correlation of them to consider the related factors of remaining useful life (RUL) from multiple angles. The multivariable gated recurrent unit (GRU) based on attention mechanism gated recurrent unit (attention-MGRU) model is adopted to improve the prediction performance. On this foundation, a fine-tuning strategy is introduced to improve the generalization ability of the model. A full-life accelerated test is carried out on the slewing bearing test bench. The model proposed in this paper is compared with GRU prediction model, which utilizes vibration signals and multivariable GRU prediction model. Mean absolute error (MAE) and root-mean-square error (RMSE) are used as measurement indicators. Among different methods, three indicators generated by attention-MGRU show significant superiority. Moreover, the fine-tuned model performs better in new tasks compared with the original model.
{"title":"Remaining useful life prediction of slewing bearings using attention mechanism enabled multivariable gated recurrent unit network","authors":"Yiyu Shao, Qinrong Qian, Hua Wang","doi":"10.1177/01423312241257297","DOIUrl":"https://doi.org/10.1177/01423312241257297","url":null,"abstract":"It is difficult to obtain the damage information on large slewing bearings only from vibration signals. In addition, deep learning models trained on old samples do not achieve high accuracy in new tasks. Therefore, this paper uses vibration, temperature, and torque signals of slewing bearings to build a model. Meanwhile, we add attention mechanism to capture internal correlation of them to consider the related factors of remaining useful life (RUL) from multiple angles. The multivariable gated recurrent unit (GRU) based on attention mechanism gated recurrent unit (attention-MGRU) model is adopted to improve the prediction performance. On this foundation, a fine-tuning strategy is introduced to improve the generalization ability of the model. A full-life accelerated test is carried out on the slewing bearing test bench. The model proposed in this paper is compared with GRU prediction model, which utilizes vibration signals and multivariable GRU prediction model. Mean absolute error (MAE) and root-mean-square error (RMSE) are used as measurement indicators. Among different methods, three indicators generated by attention-MGRU show significant superiority. Moreover, the fine-tuned model performs better in new tasks compared with the original model.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1177/01423312241261108
Mingliang Wang, Ting Wang, Zhijie Wang, Tao Li
This paper considers the problem on tracking control for the medium-scale unmanned autonomous helicopter (UAH) system under external disturbances, actuator faults, and full state constraints. In comparison with existing results, this paper does not only consider asymmetric state constraints but also jointly take the faults and disturbances into account on the UAH system, estimating and compensating for them separately, which can effectively enhance the tracking performance. First, the dynamics of nonlinear UAH system is divided into the position subsystem and the attitude one. Second, an improved barrier Lyapunov function (BLF) is constructed to handle the problem of asymmetric state constraints. Third, in order to estimate the external disturbances and actuator faults, two coupled generalized proportional integral observers (GPIOs) and two fault estimators are designed, respectively. Fourth, based on above estimations, improved BLFs, and backstepping method, two tracking control laws for the position and attitude loops are presented and an overall closed-loop system is established. Then, a sufficient condition ensuring uniform boundedness of tracking and estimation errors is derived. Finally, some simulating results demonstrate the effectiveness and advantage of the proposed control scheme.
{"title":"Safe tracking control for unmanned autonomous helicopter under actuator faults and outside disturbances","authors":"Mingliang Wang, Ting Wang, Zhijie Wang, Tao Li","doi":"10.1177/01423312241261108","DOIUrl":"https://doi.org/10.1177/01423312241261108","url":null,"abstract":"This paper considers the problem on tracking control for the medium-scale unmanned autonomous helicopter (UAH) system under external disturbances, actuator faults, and full state constraints. In comparison with existing results, this paper does not only consider asymmetric state constraints but also jointly take the faults and disturbances into account on the UAH system, estimating and compensating for them separately, which can effectively enhance the tracking performance. First, the dynamics of nonlinear UAH system is divided into the position subsystem and the attitude one. Second, an improved barrier Lyapunov function (BLF) is constructed to handle the problem of asymmetric state constraints. Third, in order to estimate the external disturbances and actuator faults, two coupled generalized proportional integral observers (GPIOs) and two fault estimators are designed, respectively. Fourth, based on above estimations, improved BLFs, and backstepping method, two tracking control laws for the position and attitude loops are presented and an overall closed-loop system is established. Then, a sufficient condition ensuring uniform boundedness of tracking and estimation errors is derived. Finally, some simulating results demonstrate the effectiveness and advantage of the proposed control scheme.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1177/01423312241254579
T. Nguyen
The electric power steering system is used to improve comfort and steering feel for the user. In this article, we propose to use an integrated nonlinear control strategy for the electric steering system, which is described based on a complicated dynamic model. This work provides two new contributions. First, this control algorithm combines backstepping and proportional–integral (PI) techniques with parameters adjusted by a fuzzy algorithm, so it is called Fuzzy proportional–integral backstepping control (FPIBSC). The output of the PI algorithm is the input of the backstepping technique, while system stability is evaluated based on the Lyapunov function with virtual control variables. Second, road reaction torque is calculated based on a spatial dynamic model, which considers the influence of many other factors. Numerical simulation methods are used to evaluate the performance of the system. According to research findings, the value of the steering motor angle (controlled object) continuously tracks the desired value with negligible error. Under some specific conditions, the error between signals can be reduced to zero. In addition, other outputs that are obtained from the FPIBSC algorithm also tend to follow the reference signal with high accuracy. The phase difference phenomenon only occurs when using the conventional backstepping algorithm instead of FPIBSC. The assisted torque increases as speed decreases or the driver torque increases. In general, the system’s stability is always guaranteed under many different simulation conditions.
{"title":"A novel approach to the FPIBSC strategy for an electric power steering system","authors":"T. Nguyen","doi":"10.1177/01423312241254579","DOIUrl":"https://doi.org/10.1177/01423312241254579","url":null,"abstract":"The electric power steering system is used to improve comfort and steering feel for the user. In this article, we propose to use an integrated nonlinear control strategy for the electric steering system, which is described based on a complicated dynamic model. This work provides two new contributions. First, this control algorithm combines backstepping and proportional–integral (PI) techniques with parameters adjusted by a fuzzy algorithm, so it is called Fuzzy proportional–integral backstepping control (FPIBSC). The output of the PI algorithm is the input of the backstepping technique, while system stability is evaluated based on the Lyapunov function with virtual control variables. Second, road reaction torque is calculated based on a spatial dynamic model, which considers the influence of many other factors. Numerical simulation methods are used to evaluate the performance of the system. According to research findings, the value of the steering motor angle (controlled object) continuously tracks the desired value with negligible error. Under some specific conditions, the error between signals can be reduced to zero. In addition, other outputs that are obtained from the FPIBSC algorithm also tend to follow the reference signal with high accuracy. The phase difference phenomenon only occurs when using the conventional backstepping algorithm instead of FPIBSC. The assisted torque increases as speed decreases or the driver torque increases. In general, the system’s stability is always guaranteed under many different simulation conditions.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141271987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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