Pub Date : 2026-02-01DOI: 10.1016/j.isatra.2025.12.013
Sanjay Kumar , Moina Ajmeri
Regulating the output of unstable process is a great challenge particularly in the presence of process parameters uncertainties, nonlinearity, transportation delays and load disturbances. These processes are even more sensitive to input changes of ramp types. In this communication, a fractional order Smith predictor scheme is analytically designed to handle the unstable process undergoing above mentioned unavoidable conditions. The suitable values of the design parameters β, α and λ are determined by exploring the stability region and investigating system robustness towards process model uncertainties. The suggested control is also well implemented on a nonlinear jacketed continuous stirred tank reactor and the performance enhancement of 71.5 % is achieved under the perfectly matched condition. When the process parameters are perturbed, 73.9 % percentage improvement is observed. Performance indices such as Integral of Squared Error (ISE), Integral of Time-weighted Absolute Error (ITAE), Integral of Absolute Error (IAE), and Total Variation (TV) are also calculated.
{"title":"Handling ramp inputs and nonlinearity in unstable systems with fractional order modified Smith predictor control","authors":"Sanjay Kumar , Moina Ajmeri","doi":"10.1016/j.isatra.2025.12.013","DOIUrl":"10.1016/j.isatra.2025.12.013","url":null,"abstract":"<div><div>Regulating the output of unstable process is a great challenge particularly in the presence of process parameters uncertainties, nonlinearity, transportation delays and load disturbances. These processes are even more sensitive to input changes of ramp types. In this communication, a fractional order Smith predictor scheme is analytically designed to handle the unstable process undergoing above mentioned unavoidable conditions. The suitable values of the design parameters β, α and λ are determined by exploring the stability region and investigating system robustness towards process model uncertainties. The suggested control is also well implemented on a nonlinear jacketed continuous stirred tank reactor and the performance enhancement of 71.5 % is achieved under the perfectly matched condition. When the process parameters are perturbed, 73.9 % percentage improvement is observed. Performance indices such as Integral of Squared Error (ISE), Integral of Time-weighted Absolute Error (ITAE), Integral of Absolute Error (IAE), and Total Variation (TV) are also calculated.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 342-356"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Distributed sliding mode controllers are proposed to address the optimal consensus problem for high-order nonlinear multi-agent systems under intermittent communication networks. Specifically, agents exchange information with neighbors only during non-overlapping time intervals, whereas all communication ceases completely during the interruption intervals. This feature significantly complicates the achievement of consensus. Under partial observability constraints, unmeasurable states are estimated via adaptive state observers. Additionally, a distributed optimization algorithm is employed to minimize the cost function and construct the optimal reference signal. To mitigate the problem of non-existent high-order derivatives, Hermite interpolation is adopted for optimal virtual signals. The distributed sliding mode controllers are designed to ensure that the tracking error of each agent converges to zero. Finally, stability analysis confirms the boundedness of the closed-loop distributed cooperative optimization framework, and simulation results verify the efficacy of the proposed method in practical scenarios.
{"title":"Distributed optimal consensus of nonlinear multi-agent systems under intermittent communication networks","authors":"Konghao Xie , Xiujuan Zhao , Shiming Chen , Zheng Zhang , Yuanshi Zheng","doi":"10.1016/j.isatra.2025.12.019","DOIUrl":"10.1016/j.isatra.2025.12.019","url":null,"abstract":"<div><div>Distributed sliding mode controllers are proposed to address the optimal consensus problem for high-order nonlinear multi-agent systems under intermittent communication networks. Specifically, agents exchange information with neighbors only during non-overlapping time intervals, whereas all communication ceases completely during the interruption intervals. This feature significantly complicates the achievement of consensus. Under partial observability constraints, unmeasurable states are estimated via adaptive state observers. Additionally, a distributed optimization algorithm is employed to minimize the cost function and construct the optimal reference signal. To mitigate the problem of non-existent high-order derivatives, Hermite interpolation is adopted for optimal virtual signals. The distributed sliding mode controllers are designed to ensure that the tracking error of each agent converges to zero. Finally, stability analysis confirms the boundedness of the closed-loop distributed cooperative optimization framework, and simulation results verify the efficacy of the proposed method in practical scenarios.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 88-100"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2026-02-01DOI: 10.1016/j.isatra.2025.12.018
Hamed Jabbari Asl , Anh Vu Le , Eiji Uchibe
This paper introduces a novel model-free and partially model-free algorithm for inverse optimal control, also known as inverse reinforcement learning, aimed at estimating the cost function of continuous-time nonlinear deterministic systems. Using the input-state trajectories of an expert agent, the proposed algorithm separately utilizes control policy information and the Hamilton-Jacobi-Bellman equation to estimate different sets of cost function parameters. This design allows the framework to achieve broader applicability while maintaining a model-free formulation. Moreover, the model-free version reduces computational complexity compared to existing methods, as it requires solving a forward optimal control problem only once during initialization. In contrast, in the partially model-free version, this step can be bypassed entirely for systems with known input dynamics. Simulation results demonstrate the effectiveness and efficiency of the proposed approach, highlighting its potential for real-world deployment in autonomous systems and robotics.
{"title":"Data-driven inverse optimal control for continuous-time nonlinear systems","authors":"Hamed Jabbari Asl , Anh Vu Le , Eiji Uchibe","doi":"10.1016/j.isatra.2025.12.018","DOIUrl":"10.1016/j.isatra.2025.12.018","url":null,"abstract":"<div><div>This paper introduces a novel model-free and partially model-free algorithm for inverse optimal control, also known as inverse reinforcement learning, aimed at estimating the cost function of continuous-time nonlinear deterministic systems. Using the input-state trajectories of an expert agent, the proposed algorithm separately utilizes control policy information and the Hamilton-Jacobi-Bellman equation to estimate different sets of cost function parameters. This design allows the framework to achieve broader applicability while maintaining a model-free formulation. Moreover, the model-free version reduces computational complexity compared to existing methods, as it requires solving a forward optimal control problem only once during initialization. In contrast, in the partially model-free version, this step can be bypassed entirely for systems with known input dynamics. Simulation results demonstrate the effectiveness and efficiency of the proposed approach, highlighting its potential for real-world deployment in autonomous systems and robotics.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 101-111"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the context of three-dimensional angle-of-arrival (3D-AOA) target tracking, this study proposes a state-constrained and noise-separated pseudo-linear Kalman filtering (SC-NS-PLKF) algorithm to address nonlinear filtering challenges. Whereas existing bias-compensated (BC), instrumental-variable (IV) and unbiased (UB) PLKF methods only correct the pseudo-linear bias, SC-NS-PLKF achieves high-precision unbiased estimation with enhanced algorithmic stability. Specifically, this method (i) derives a new pseudo-linear measurement model through nonlinear equivalent transformation and noise separation; (ii) employs auxiliary filtering to supply the target position required by NS-PLKF and constructs an ellipsoidal constraint domain that guarantees divergence prevention; (iii) provides a rigorous proof of bounded estimation error and includes a complexity analysis to validate computational efficiency. Extensive Monte-Carlo simulations demonstrate significant gains in accuracy and stability compared to state-of-the-art methods.
{"title":"A state-constrained and noise-separated pseudo-linear Kalman filtering algorithm for 3D-AOA model","authors":"Jinjie Huang , Qingyang Jia , Hengyu Liang , Xiaojun Ban","doi":"10.1016/j.isatra.2025.12.038","DOIUrl":"10.1016/j.isatra.2025.12.038","url":null,"abstract":"<div><div>In the context of three-dimensional angle-of-arrival (3D-AOA) target tracking, this study proposes a state-constrained and noise-separated pseudo-linear Kalman filtering (SC-NS-PLKF) algorithm to address nonlinear filtering challenges. Whereas existing bias-compensated (BC), instrumental-variable (IV) and unbiased (UB) PLKF methods only correct the pseudo-linear bias, SC-NS-PLKF achieves high-precision unbiased estimation with enhanced algorithmic stability. Specifically, this method (i) derives a new pseudo-linear measurement model through nonlinear equivalent transformation and noise separation; (ii) employs auxiliary filtering to supply the target position required by NS-PLKF and constructs an ellipsoidal constraint domain that guarantees divergence prevention; (iii) provides a rigorous proof of bounded estimation error and includes a complexity analysis to validate computational efficiency. Extensive Monte-Carlo simulations demonstrate significant gains in accuracy and stability compared to state-of-the-art methods.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 465-476"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2026-02-01DOI: 10.1016/j.isatra.2025.12.051
Zhiyuan Huang , Jun Zhang , Zhilin Liu
To address the high computational complexity of model predictive control (MPC) in trimaran motion reduction, this paper develops a low-complexity predictive control framework that integrates three key mechanisms. First, within the control horizon, the control input is constructed as the sum of an optimal baseline and auxiliary variables, ensuring constraint satisfaction and smooth switching. Second, the auxiliary variables are parameterized by Laguerre functions, thereby compressing the optimization dimension. Third, a double-constraint triggering mechanism based on actuator magnitude and rate adaptively reduces optimization frequency. With appropriately designed terminal constraints, closed-loop input-to-state stability (ISS) is established via Lyapunov theory. Simulations under Sea State 4 demonstrate that the proposed method reduces the root-mean-square (RMS) value of heave displacement by 58.61% and pitch angle by 50.27% compared to uncontrolled baselines. Experimental tests on a 1:10 scaled trimaran further confirm its practical effectiveness. Importantly, the controller achieves real-time feasibility with a computation time of 36 ms for a 100-step horizon, well within the 50 ms control cycle.
针对三体船运动减速中模型预测控制（MPC）计算复杂度高的问题，提出了一种集成三种关键机制的低复杂度预测控制框架。首先，在控制视界内，将控制输入构造为最优基线和辅助变量之和，保证约束满足和平滑切换；其次，利用拉盖尔函数对辅助变量进行参数化，压缩优化维数；第三，基于执行器大小和速率的双约束触发机构自适应降低优化频率。在适当设计终端约束的情况下，利用李亚普诺夫理论建立闭环输入-状态稳定性（ISS）。Sea State 4下的仿真结果表明，与未控制基线相比，该方法可将升沉位移的均方根（RMS）值降低58.61%，俯仰角降低50.27%。1:10比例三体船的试验进一步证实了该方法的实用性。重要的是，控制器在50 ms的控制周期内，以36 ms的计算时间实现了100步视界的实时可行性。
{"title":"Low computational complexity model predictive control for high-speed trimaran motion reduction","authors":"Zhiyuan Huang , Jun Zhang , Zhilin Liu","doi":"10.1016/j.isatra.2025.12.051","DOIUrl":"10.1016/j.isatra.2025.12.051","url":null,"abstract":"<div><div>To address the high computational complexity of model predictive control (MPC) in trimaran motion reduction, this paper develops a low-complexity predictive control framework that integrates three key mechanisms. First, within the control horizon, the control input is constructed as the sum of an optimal baseline and auxiliary variables, ensuring constraint satisfaction and smooth switching. Second, the auxiliary variables are parameterized by Laguerre functions, thereby compressing the optimization dimension. Third, a double-constraint triggering mechanism based on actuator magnitude and rate adaptively reduces optimization frequency. With appropriately designed terminal constraints, closed-loop input-to-state stability (ISS) is established via Lyapunov theory. Simulations under Sea State 4 demonstrate that the proposed method reduces the root-mean-square (RMS) value of heave displacement by 58.61% and pitch angle by 50.27% compared to uncontrolled baselines. Experimental tests on a 1:10 scaled trimaran further confirm its practical effectiveness. Importantly, the controller achieves real-time feasibility with a computation time of 36 ms for a 100-step horizon, well within the 50 ms control cycle.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 694-711"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145936853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2026-02-01DOI: 10.1016/j.isatra.2025.12.035
Chao Jia, Junjie Ping
In this paper, we propose a predefined-time nonsingular sliding mode control (SMC) method based on emotional neural networks (ENN) for disturbed nonlinear systems. Firstly, based on the predefined-time stability (PDTS) theory, a new sufficient condition is constructed. By introducing a novel adaptive continuously adjustable exponential term into the Lyapunov stability lemma, this modification abandons the traditional fixed parameterization of exponential terms. Secondly, by introducing ENN to approximate the equivalent control term, a nonsingular SMC is designed, meanwhile solving the issue of unknown dynamics. Using Lyapunov theory, this paper rigorously proves the system’s PDTS in both the reaching and sliding phases. Finally, simulations on the inverted pendulum and deep-sea vehicle manipulator show that they can track the target trajectory in 0.22 and 0.23 s respectively, outperforming comparison methods.
{"title":"A nonsingular predefined time sliding mode control method with continuously variable exponents for nonlinear systems based on emotional neural network","authors":"Chao Jia, Junjie Ping","doi":"10.1016/j.isatra.2025.12.035","DOIUrl":"10.1016/j.isatra.2025.12.035","url":null,"abstract":"<div><div>In this paper, we propose a predefined-time nonsingular sliding mode control (SMC) method based on emotional neural networks (ENN) for disturbed nonlinear systems. Firstly, based on the predefined-time stability (PDTS) theory, a new sufficient condition is constructed. By introducing a novel adaptive continuously adjustable exponential term into the Lyapunov stability lemma, this modification abandons the traditional fixed parameterization of exponential terms. Secondly, by introducing ENN to approximate the equivalent control term, a nonsingular SMC is designed, meanwhile solving the issue of unknown dynamics. Using Lyapunov theory, this paper rigorously proves the system’s PDTS in both the reaching and sliding phases. Finally, simulations on the inverted pendulum and deep-sea vehicle manipulator show that they can track the target trajectory in 0.22 and 0.23 s respectively, outperforming comparison methods.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 194-209"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145897146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2026-02-01DOI: 10.1016/j.isatra.2025.12.044
Wei Zhang, Xiangcheng Ye, Junjian Huang
This paper investigates security synchronization in complex dynamical networks (CDNs) using a self-triggered impulsive control (STIC) with actuation delays and a quantizer. 1) By integrating network topology and Lyapunov function theory, we introduce a new self-triggered mechanism (STM), unlike traditional computationally intensive STMs, which embeds a fixed dwell time to eliminate Zeno behavior and avoid continuous state monitoring, solving the delay-induced desynchronization issue ignored by existing STIC studies. 2) A logarithmic quantizer is fused with STM, reducing communication resource consumption compared to unquantized STIC, while ensuring low relative quantization error. 3)Global Asymptotic Stability in the Mean (GAS-M) synchronization criteria are derived via the Lyapunov method and graph theory, explicitly linking STM parameters, network topology, and attack intensities. 4) A numerical example of Chua’s circuits under deception attacks and denial-of-service (DoS) attacks is provided to demonstrate the effectiveness of the theoretical findings on GAS-M under random attacks.
{"title":"Security synchronization of complex dynamical networks under deception and DoS attacks via self-triggered impulsive control with actuation delays","authors":"Wei Zhang, Xiangcheng Ye, Junjian Huang","doi":"10.1016/j.isatra.2025.12.044","DOIUrl":"10.1016/j.isatra.2025.12.044","url":null,"abstract":"<div><div>This paper investigates security synchronization in complex dynamical networks (CDNs) using a self-triggered impulsive control (STIC) with actuation delays and a quantizer. 1) By integrating network topology and Lyapunov function theory, we introduce a new self-triggered mechanism (STM), unlike traditional computationally intensive STMs, which embeds a fixed dwell time to eliminate Zeno behavior and avoid continuous state monitoring, solving the delay-induced desynchronization issue ignored by existing STIC studies. 2) A logarithmic quantizer is fused with STM, reducing communication resource consumption compared to unquantized STIC, while ensuring low relative quantization error. 3)Global Asymptotic Stability in the Mean (GAS-M) synchronization criteria are derived via the Lyapunov method and graph theory, explicitly linking STM parameters, network topology, and attack intensities. 4) A numerical example of Chua’s circuits under deception attacks and denial-of-service (DoS) attacks is provided to demonstrate the effectiveness of the theoretical findings on GAS-M under random attacks.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 150-157"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2026-02-01DOI: 10.1016/j.isatra.2025.12.033
Zhaoke Ning , Xinglian Zhou , Juncong Yang , Hanlin Dong , Xudong Wang
This article focuses on designing an innovative security control methodology for linear networked control systems under deception attacks, which are stochastically attacked by two unknown-bounded deception signals. Firstly, an ambiguity set is introduced to characterize all potential deception signals that satisfy the identical mean-covariance constraints instead of bounded constraints. Then, chance constraints concerning system state and control variables are formulated to mitigate conservatism in the security control design. On the basis of the principle of distributionally robust optimization, chance constraints are addressed by handling a deterministic convex reformation problem. Subsequently, a stochastic model predictive control approach is deployed to realize the recursive feasibility and convergence of the controlled model. Finally, different scenarios of malicious attacks concerning the DC-DC boost converter are presented with the aim of validating the superiority of the designed approach.
{"title":"Security control for networked control systems with deception attacks: A stochastic model predictive control approach","authors":"Zhaoke Ning , Xinglian Zhou , Juncong Yang , Hanlin Dong , Xudong Wang","doi":"10.1016/j.isatra.2025.12.033","DOIUrl":"10.1016/j.isatra.2025.12.033","url":null,"abstract":"<div><div>This article focuses on designing an innovative security control methodology for linear networked control systems under deception attacks, which are stochastically attacked by two unknown-bounded deception signals. Firstly, an ambiguity set is introduced to characterize all potential deception signals that satisfy the identical mean-covariance constraints instead of bounded constraints. Then, chance constraints concerning system state and control variables are formulated to mitigate conservatism in the security control design. On the basis of the principle of distributionally robust optimization, chance constraints are addressed by handling a deterministic convex reformation problem. Subsequently, a stochastic model predictive control approach is deployed to realize the recursive feasibility and convergence of the controlled model. Finally, different scenarios of malicious attacks concerning the DC-DC boost converter are presented with the aim of validating the superiority of the designed approach.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 318-328"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145866795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2026-02-01DOI: 10.1016/j.isatra.2025.12.042
Xiaoduo Zhang , Huiming Wang , Junxiao Wang , Xianlun Tang
In this paper, a robust disturbance rejection control scheme is proposed for the trajectory tracking of flexible joint robots (FJRs) affected by multi-source disturbances and input saturation. The unknown time-varying disturbances, which are categorized into matched and mismatched, generally encompass uncertainties in internal parameters, coupling effects, unmodeled dynamics, and changing external environments. To address these disturbances, the mismatched disturbances are transformed into matched disturbances through the flatness method, eliminating the computational cost of estimating mismatched disturbances. Meanwhile, a generalized proportional integral observer (GPIO) is adopted to estimate the unmeasurable states and disturbances. In addition, to deal with input saturation, an anti-windup compensation auxiliary system is constructed. Finally, an output feedback control framework based on continuous sliding mode control (CSMC) is further designed. The proposed control approach facilitates asymptotic convergence of the tracking error and mitigates the chattering effect inherent in traditional sliding mode control (SMC), thereby enhancing both control and dynamic performance while satisfying input constraints. A detailed stability analysis of the closed-loop system is also presented. The feasibility and effectiveness of this approach are validated through comparison with a traditional disturbance rejection control scheme.
{"title":"Continuous sliding mode disturbance rejection control for flexible joint robots with input saturation","authors":"Xiaoduo Zhang , Huiming Wang , Junxiao Wang , Xianlun Tang","doi":"10.1016/j.isatra.2025.12.042","DOIUrl":"10.1016/j.isatra.2025.12.042","url":null,"abstract":"<div><div>In this paper, a robust disturbance rejection control scheme is proposed for the trajectory tracking of flexible joint robots (FJRs) affected by multi-source disturbances and input saturation. The unknown time-varying disturbances, which are categorized into matched and mismatched, generally encompass uncertainties in internal parameters, coupling effects, unmodeled dynamics, and changing external environments. To address these disturbances, the mismatched disturbances are transformed into matched disturbances through the flatness method, eliminating the computational cost of estimating mismatched disturbances. Meanwhile, a generalized proportional integral observer (GPIO) is adopted to estimate the unmeasurable states and disturbances. In addition, to deal with input saturation, an anti-windup compensation auxiliary system is constructed. Finally, an output feedback control framework based on continuous sliding mode control (CSMC) is further designed. The proposed control approach facilitates asymptotic convergence of the tracking error and mitigates the chattering effect inherent in traditional sliding mode control (SMC), thereby enhancing both control and dynamic performance while satisfying input constraints. A detailed stability analysis of the closed-loop system is also presented. The feasibility and effectiveness of this approach are validated through comparison with a traditional disturbance rejection control scheme.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 210-222"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145893589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2026-02-01DOI: 10.1016/j.isatra.2025.12.045
Runzhu Wang, Yi Li, Mengfan Liu, Minglei Zheng, Xiuju Xu, Tao Zhang
Unmanned aerial vehicle (UAV) flight control systems are exposed to diverse security threats, including environmental disturbances, component faults, and cyber-attacks. Existing fault-tolerant control methods lack generalizability in representing such heterogeneous perturbations, particularly adversarial cyber-attacks, due to their reliance on type-specific modeling assumptions. In this study, an Information Flow Metamodel-Based Adaptive Approximate Modeling (IFM-AAM) framework is proposed to address this issue. The framework establishes an Information Flow Metamodel (IFM) as a high-level structural abstraction for approximate modeling. IFM represents heterogeneous perturbations as symbolic anomalies within a unified information flow structure, enabling consistent propagation analysis and impact computation across diverse perturbation sources. The IFM design supports flexible instantiation of domain models (DMs) at appropriate abstraction levels, addressing the computational challenges of modeling densely coupled flight control systems. In addition, a lightweight Actor-Critic reinforcement learning (RL) mechanism is integrated into the instantiated DMs for real-time adaptive tuning of control parameters, further enhancing modeling fidelity under perturbations. Comparative simulations against PX4 Autopilot demonstrate that DMs constructed by IFM-AAM effectively approximate control performance across nominal and diverse perturbation scenarios. These results confirm the effectiveness of our unified representation and propagation analysis for heterogeneous perturbations. Moreover, validations on an onboard computer verify the real-time performance and low computational overhead of DMs.
{"title":"Information flow-based UAV flight control adaptive approximate modeling for perturbation generalization","authors":"Runzhu Wang, Yi Li, Mengfan Liu, Minglei Zheng, Xiuju Xu, Tao Zhang","doi":"10.1016/j.isatra.2025.12.045","DOIUrl":"10.1016/j.isatra.2025.12.045","url":null,"abstract":"<div><div>Unmanned aerial vehicle (UAV) flight control systems are exposed to diverse security threats, including environmental disturbances, component faults, and cyber-attacks. Existing fault-tolerant control methods lack generalizability in representing such heterogeneous perturbations, particularly adversarial cyber-attacks, due to their reliance on type-specific modeling assumptions. In this study, an Information Flow Metamodel-Based Adaptive Approximate Modeling (IFM-AAM) framework is proposed to address this issue. The framework establishes an Information Flow Metamodel (IFM) as a high-level structural abstraction for approximate modeling. IFM represents heterogeneous perturbations as symbolic anomalies within a unified information flow structure, enabling consistent propagation analysis and impact computation across diverse perturbation sources. The IFM design supports flexible instantiation of domain models (DMs) at appropriate abstraction levels, addressing the computational challenges of modeling densely coupled flight control systems. In addition, a lightweight Actor-Critic reinforcement learning (RL) mechanism is integrated into the instantiated DMs for real-time adaptive tuning of control parameters, further enhancing modeling fidelity under perturbations. Comparative simulations against PX4 Autopilot demonstrate that DMs constructed by IFM-AAM effectively approximate control performance across nominal and diverse perturbation scenarios. These results confirm the effectiveness of our unified representation and propagation analysis for heterogeneous perturbations. Moreover, validations on an onboard computer verify the real-time performance and low computational overhead of DMs.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"169 ","pages":"Pages 372-390"},"PeriodicalIF":6.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145879778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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