ISA transactions最新文献

{"title":"Motion control strategy for robotic arm using deep cascaded feature-enhancement Bayesian broad learning system with motion constraints.","authors":"Jiyong Zhou, Guoyu Zuo, Xiang Li, Shuangyue Yu, Shuaifeng Dong","doi":"10.1016/j.isatra.2025.02.027","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.027","url":null,"abstract":"<p><p>Intelligent control strategies can significantly enhance the efficiency of model parameter adjustment. However, existing intelligent motion control strategies for robotic arms based on the broad learning system lack sufficient accuracy and fail to account for the effects of joint motion limitations on overall control performance. To address the aforementioned challenges, this paper proposes a robotic arm motion control strategy based on a deep cascaded feature-enhanced Bayesian broad learning system with motion constraints (MC-DCBLS). Firstly, the motion control strategy based on a deep cascaded feature-enhanced Bayesian broad learning system (DCBBLS) is designed, which simplifies the modeling process and significantly improves control accuracy. Secondly, the motion constraint mechanism is introduced to optimize the control strategy to ensure that the robotic arm motion does not break through the physical limit. Finally, the parameter constraints of the control strategy network were obtained by introducing the Lyapunov theory to ensure the stability of the robotic arm motion control. The effectiveness of the proposed control strategy was validated through both simulations and physical experiments. The results demonstrated that the strategy significantly improved the accuracy of robotic arm motion control, with the root mean square error (RMSE) in position tracking reduced to 0.038 rad. This represents a 61.26% reduction in error compared to existing techniques.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631147","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":"Global fixed-time position-constrained guidance and adaptive fuzzy prescribed performance control using novel shift function for multiple unmanned surface vehicles formation.","authors":"Haiyan Tong, Mingxiao Sun, Tiantian Luan","doi":"10.1016/j.isatra.2025.02.034","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.034","url":null,"abstract":"<p><p>Guidance and control of multiple unmanned surface vehicles (Multi-USVs) present many challenges due to their under-actuation and the unknown environmental disturbance. This research addresses the formation guidance and control problems of multi-USVs by designing a global fixed-time constrained guidance and control formation approach. First, a global fixed-time control Lyapunov function (GFCLF) is proposed using an innovative shift function to deal with the fixed-time output partial constraint. Subsequently, a fixed-time asymmetric position-constrained guidance algorithm for multi-USVs formation is designed by combining the line-of-sight guidance principle, the leader-follower structure, and the suggested GFCLF. Second, a global fixed-time prescribed performance function (GFPPF) is designed to solve the global tracking error performance constraint problem. Then, global fixed-time adaptive fuzzy prescribed performance control laws are developed to achieve the tracking control for the multi-USVs formation task, in which a fixed-time adaptive fuzzy logic system is designed to approximate the unknown disturbance of USVs. Furthermore, the closed-loop control system stability analysis is proven to support that all tracking error signals are bounded in a fixed time. Finally, simulations and comparative cases using the physical USV model are studied to demonstrate the practicality and superiority of theoretical results.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143618131","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":"Adaptive terminal super-twisting prescribed performance controller for near-space vehicle based on data-driven model.","authors":"Tianchen Zhang, Yibo Ding, Xiaokui Yue, Naying Li","doi":"10.1016/j.isatra.2025.03.001","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.03.001","url":null,"abstract":"<p><p>A data-driven adaptive terminal super-twisting prescribed performance controller (DASTPC) is designed for near-space vehicle (NSV) to satisfy transient and steady-state performance, and prevent scramjet choking. Firstly, a novel predetermined-time performance function is proposed to guarantee that tracking error can converge to a prescribed bound of small residual sets at the predetermined time. Compared with traditional performance functions, the predetermined-time performance function can achieve faster respond speed, realize more accurate convergence, and avoid overlarge initial value of actuators. Secondly, by combining the predetermined-time performance function with sliding mode control, a novel non-singular fast terminal sliding surface and an improved adaptive super-twisting reaching law are proposed to improve computational efficiency and accelerate convergent rate of system. The adaptive reaching law can avoid excessive gains and attenuate chattering by automatically tuning control gain. Thirdly, a deep recurrent neural network-based long-short term memory (LSTM) is employed to learn time-series historical flight dynamics data offline, so as to construct a data-driven LSTM training model. This data-driven model replaces nominal dynamics model of NSV in DASTPC, effectively suppressing model uncertainties. In addition, a homogeneous high-order sliding mode observer is utilized to compensate for external disturbances, avoiding excessive parameter estimation. Since boundary conditions of the predetermined-time performance function are fully satisfied, the DASTPC can effectively restrict amplitude of angle of attack, thus ensuring the intake condition of scramjet. Ultimately, to illustrate the superiority of DASTPC, several sets of simulations are performed on NSV subject to prescribed performance bound, external disturbances and parameter perturbations.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143626835","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 general TD-Q learning control approach for discrete-time Markov jump systems.","authors":"Jiwei Wen, Huiwen Xue, Xiaoli Luan, Peng Shi","doi":"10.1016/j.isatra.2025.02.032","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.032","url":null,"abstract":"<p><p>This paper develops a novel temporal difference Q (TD-Q) learning approach, designed to address the robust control challenge in discrete-time Markov jump systems (MJSs) which are characterized by entirely unknown dynamics and transition probabilities (TPs). The model-free TD-Q learning method is uniquely comprehensive, including two special cases: Q learning for MJSs with unknown dynamics, and TD learning for MJSs with undetermined TPs. We propose an innovative ternary policy iteration framework, which iteratively refines the control policies through a dynamic loop of alternating updates. This loop consists of three synergistic processes: firstly, aligning TD value functions with current policies; secondly, enhancing Q-function's matrix kernels (QFMKs) using these TD value functions; and thirdly, generating greedy policies based on the enhanced QFMKs. We demonstrate that, with a sufficient number of episodes, the TD value functions, QFMKs, and control policies converge optimally within this iterative loop. To illustrate efficiency of the developed approach, we introduce a numerical example that highlights its substantial benefits through a thorough comparison with current learning control methods for MJSs. Moreover, a structured population dynamics model for pests is utilized to validate the practical applicability.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607623","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":"Geometric attitude tracking control of quadrotor UAVs with adaptive extended state observers.","authors":"Liping Wang, Jiapeng Chen, Yuyuan Huang, Yongbin Zhu, Hailong Pei","doi":"10.1016/j.isatra.2025.02.025","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.025","url":null,"abstract":"<p><p>This paper studies a geometric attitude tracking control problem of quadrotor unmanned aerial vehicles (UAVs) with adaptive extended state observers (AESOs). Through coordinate transformation, the error dynamic of AESO can be transformed into a canonical form which is easier to analyze by linear time-varying theory. In the presence of unknown disturbances and system uncertainties, the estimated error and stability of AESO can be analyzed. Simultaneously, a geometric tracking controller is developed on SO(3) with AESOs which guarantees that the error exponentially converges to a bounded set related to the estimated error. Some examples and a flight test are given to verify the availability of the control scheme.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639874","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":"Optimized nonlinear robust controller along with model-parameter estimation for blood glucose regulation in type-1 diabetes.","authors":"Atif Rehman, Syed Hassan Ahmed, Iftikhar Ahmad","doi":"10.1016/j.isatra.2025.02.030","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.030","url":null,"abstract":"<p><p>Glucose acts as a fundamental energy source for cells and plays a pivotal role in various physiological processes, including metabolism, signaling, and cellular control. Maintaining precise regulation of blood glucose levels is crucial for overall health and equilibrium. To achieve this balance, insulin is administered either orally or through an artificial pancreas (AP) during sleep, utilizing control algorithms based on mathematical models to regulate blood glucose concentration (BGC). The extended Bergman minimal model (EBMM) is an advanced mathematical framework that incorporates a state variable to accommodate disturbances in insulin levels triggered by factors such as meal intake or exercise-induced sugar burning. In our study, we propose robust nonlinear controllers: adaptive backstepping sliding mode control (AB-SMC), and adaptive backstepping integral super twisting sliding mode control (ABIST-SMC) and compare these with the backstepping sliding mode control (B-SMC) for stabilizing BGC in type 1 diabetic patients. These controllers aim to regulate blood glucose levels in type 1 diabetic patients by providing robust and adaptive control strategies that mitigate disturbances and ensure stability, ultimately enhancing health outcomes and quality of life. Moreover, adaptive parameter estimation is incorporated to eliminate the need for exact model parameter values for control design. The controller gains are meticulously fine-tuned using improved grey wolf optimization, with the integral time absolute error serving as the objective function. Notably, the ABIST-SMC controller emerges as the most efficient, achieving the desired reduction level in less than 1.92 min. The stability of the proposed controllers is rigorously analyzed using the Lyapunov control theory, demonstrating their capability to achieve asymptotic stability. Simulations are conducted to evaluate and compare the performance of the suggested controllers. Additionally, hardware validation is executed using a hardware-in-loop experimental setup.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639887","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":"Modeling and design of power conditioning unit of CubeSat electrical power subsystem with robust nonlinear MPPT controller.","authors":"Muhammad Noman, Usman Ali Afzal, Iftikhar Ahmad, Shahzad Ahmed","doi":"10.1016/j.isatra.2025.02.020","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.020","url":null,"abstract":"<p><p>Two non-inverting buck-boost converters, one for each solar panel of the X and Y axes of CubeSat have been used to condition the power with a common output capacitor on DC bus. The power generated from each axis of the solar panel is added to the DC-bus along with the power generated by the less illuminated solar panels. For the proposed model, Synergetic control, Sliding Mode Control, and Super Twisting Sliding Mode Control algorithms have been implemented for the MPPT, and their results are compared with each other. The results indicate that the ST-SMC performs well and gives the best dynamic performance and robustness under varying load conditions of temperature, irradiance, and disturbance. Moreover, the stability of the system is validated by using the Lyapunov stability criterion.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569161","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":"Event-triggered boundary consensus force control for PDE modeling multi-flexible manipulators with both actuator delay and communication delay.","authors":"Xinyang Ma, Jinkun Liu","doi":"10.1016/j.isatra.2025.02.026","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.026","url":null,"abstract":"<p><p>A distributed adaptive consistency controller is designed for PDE modeling multi-flexible manipulators with both actuator delay and communication delay. The input integral is fed back into the controller to avoid the influence of the actuator delay. The adaptive law is designed to observe the ideal signal for the agent without the ideal signal information. The event-triggered method is used in the adaptive law to reduce information transmission pressure and simplify analysis. Based on the integral Krasovskii Lyapunov function and the adaptive law, the designed controller works even with the unknown communication delay between manipulators. A matrix composed of the system and controller parameters is designed, representing the convergence rate of the system, and the optimization function FMINCON is used to optimize the matrix, in order to obtain appropriate controller coefficients. Control goal realization and the stability of the closed-loop system are proven via the Lyapunov direct method. Simulation results verify the effectiveness of the proposed controller.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588695","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":"Data-based tuning of bumpless feedforward for tracking of multi-phase trajectories with application to wire-bonding machine.","authors":"Yifan Xu, Silu Chen, Zhuang Xu, Chi Zhang, Weizhen Wang, Dunant Halim","doi":"10.1016/j.isatra.2025.02.028","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.028","url":null,"abstract":"<p><p>To improve the settling time for high-speed point-to-point motion, a piecewise-model feedforward controller is introduced which utilizes multiple inverse sub-models with bumpless transfer between them. As the transfer function of this bumpless feedforward controller is non-commutative and non-invertible, a set of special perturbation and reference inputs are designed to extract the signals required for computing the gradient of the cost function. In this way, the optimal parameters within different motion phases are found within an integrated process. It is experimentally demonstrated in a wire-bonding machine that the root-mean-square of tracking error is improved by at least 15.3% in settling phase by the proposed data-based tuning method with bumpless feedforward controller, compared with existing tuning methods with uniform feedforward controller.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607641","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":"Cooperative control for a ROV-based deep-sea mining vehicle with learned uncertain nonlinear dynamics.","authors":"Yuheng Chen, Haicheng Zhang, Weisheng Zou, Haihua Zhang, Daolin Xu","doi":"10.1016/j.isatra.2025.02.033","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.02.033","url":null,"abstract":"<p><p>To overcome the bottleneck problem of the track slippage of the tracked mining vehicle in the traditional deep-sea mining system, this paper proposes an enhanced remotely-operated vehicle (ROV)-based deep-sea mining system. A ROV-based Deep-sea Mining Vehicle (RDMV), consisting of two ROVs and a mining robot (MRT), is instead of the traditional tracked Deep-sea mining vehicle. Firstly, the dynamic model of the RDMV as a control object is established based on Lagrangian function. Secondly, a cooperative control strategy is proposed for traction and sinking control of the RDMV. A distributed model predictive control (DMPC)-based controller is developed to obtain virtual speed control laws to meet the control objects. To track the virtual speed control laws, a learning-based model predictive control (LMPC)-based controller is investigated to compute the ROVs' optimal control input, where a Kinky Inference (KI) prediction function is introduced in the state transition model to estimate the unknown external disturbances under random noise. Finally, the feasibility and the superiority of the LMPC controller is preliminarily verified in a degenerate individual motion control of a ROV, and then the cooperative control strategy is proven to be effective through numerical simulations.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588689","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}