International Journal of Robust and Nonlinear Control最新文献

{"title":"Robust Adaptive Nonlinear Admittance Control of Robotic Manipulators With Extra-Intra Uncertainties and Disturbances","authors":"Shubo Zhang,&nbsp;Zhong Chen,&nbsp;Xianming Zhang","doi":"10.1002/rnc.7946","DOIUrl":"https://doi.org/10.1002/rnc.7946","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper focuses on achieving rapid convergence in finite time for robust trajectory tracking in robotic manipulators with unknown uncertainty bounds. To address the issues of excessive control torque and control reversal at the initial stage, a novel robust adaptive fast terminal sliding mode control (RAF-TSMC) method is developed. The method ensures faster transient responses and higher steady-state tracking accuracy and eliminates singularities while mitigating chattering effects. Additionally, to enhance the physical collaboration in human–robot interactions, a nonlinear admittance control method integrated with RAF-TSMC is developed. Benefiting from adaptive compliance characteristics, this method improves the suppleness and flexibility of a human–robot interaction in uncertain environments. Finally, the effectiveness of the proposed controller is validated using a two-link robotic manipulator subjected to uncertainties and external forces. The results demonstrate that the proposed RAF-TSMC controller can effectively minimize tracking errors and convergence time, and the proposed nonlinear admittance control with RAF-TSMC can enhance the flexibility and adaptability of the robot system.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4841-4856"},"PeriodicalIF":3.2,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Input–Output Approach to Structured Stochastic Uncertainty in Continuous Time","authors":"Maurice Filo,&nbsp;Bassam Bamieh","doi":"10.1002/rnc.7919","DOIUrl":"https://doi.org/10.1002/rnc.7919","url":null,"abstract":"<div>\u0000 \u0000 <p>We consider the continuous-time setting of linear time-invariant (LTI) systems in feedback with multiplicative stochastic uncertainties. The primary objective of this article is to establish conditions for mean-square stability using a purely input–output approach, avoiding the need for state space realizations. This approach broadens the applicability to a wider range of models, including infinite-dimensional systems and systems with delays. The input–output approach leads to uncovering new tools such as stochastic block diagrams, which are closely related to stochastic integral equations rather than the more commonly used stochastic differential equations. We explore various stochastic interpretations, including Itô and Stratonovich, and develop block diagram conversion schemes to transition between these interpretations. The MSS conditions are given in terms of the spectral radius of a matrix operator that takes different forms when different stochastic interpretations are considered.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4462-4479"},"PeriodicalIF":3.2,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fixed-Time Dynamic Event-Triggered Formation Control for Unmanned Aerial-Ground Vehicle (UAV-UGV) Heterogeneous System","authors":"Xing Guo,&nbsp;Qing Li,&nbsp;Qijia Yao,&nbsp;Xiaoya Lu","doi":"10.1002/rnc.7937","DOIUrl":"https://doi.org/10.1002/rnc.7937","url":null,"abstract":"<div>\u0000 \u0000 <p>This study proposes a fixed-time trajectory tracking control method based on the dynamic event-triggered mechanism (DETM) to address the formation problem for unmanned aerial-ground vehicle (UAV-UGV) heterogeneous systems subject to external disturbances. Firstly, to estimate external disturbances for each member in the system, a fixed-time disturbance observer (FTDO) is constructed. Then, based on the integration of FTDO, backstepping control, and fixed-time stability theory, a fixed-time formation control protocol is developed to make the system own faster transient response and fixed-time formation convergence error independent of initial states, while using a non-linear filter to eliminate computer explosion problem in the process of backstepping design. Subsequently, a DETM is integrated into the control protocol such that the merits of lower control frequency and lower communication burden on the system can be achieved. The proposed method can not only improve the robustness, but also save the system energy while ensuring tracking accuracy. Finally, compared with existing methods, the simulation results show the validity and superiority of the proposed method.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4738-4753"},"PeriodicalIF":3.2,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Adaptive State Observer for the Autonomous Underwater Vehicles With Uncertainties by Utilising Neural Network","authors":"Dung Manh Do,&nbsp;Hai Le Xuan,&nbsp;Thanh Pham Ngoc,&nbsp;Hung Ha Manh,&nbsp;Thai Kim Dinh,&nbsp;Duy Hoang","doi":"10.1002/rnc.7923","DOIUrl":"https://doi.org/10.1002/rnc.7923","url":null,"abstract":"<div>\u0000 \u0000 <p>The article proposes a novel adaptive observer utilising a two-hidden-layer neural network to estimate the states, including positions, rotations and velocities in the North-East-Down (NED) reference frame, of Autonomous Underwater Vehicles (AUVs). The studied AUVs are characterised by uncertain and nonlinear mathematical models, as well as the effects of unknown environmental disturbances. In addition to the novelty of the observer's structure, a salient feature of the proposed observer lies in its ability to estimate accurately unmeasured states irrespective of the strong nonlinear output-to-state mapping of the AUVs and inaccurate output measurement. In terms of designing output-feedback controllers, instead of proposing a particular controller, the class of output-feedback controllers for the AUV system has been systematically investigated such that the stability of the closed-loop AUV system is ensured when combined with the proposed observer. The efficacy of the proposed observer has been verified rigorously through theoretical analysis and simulation results.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4497-4522"},"PeriodicalIF":3.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fault-Tolerant Control of Post-Stall Maneuver for Fighter Aircraft Against Center of Gravity Shift and Actuator Faults","authors":"Pengfei Li,&nbsp;Yuehui Ji,&nbsp;Yu Song,&nbsp;Junjie Liu,&nbsp;Zengqiang Chen","doi":"10.1002/rnc.7925","DOIUrl":"https://doi.org/10.1002/rnc.7925","url":null,"abstract":"<div>\u0000 \u0000 <p>Addressing the challenge of fault-tolerant control and control allocation (CA) during post-stall maneuver of fighter aircraft equipped with thrust vectoring, a fault-tolerant control strategy is proposed. First, aiming at the effect on flight quality of the center of gravity shift caused by factors like uneven fuel combustion and structural damages during the post-stall maneuver, a predefined time extended state observer is proposed to estimate and compensate for the effects of center of gravity shift, strong coupling and modeling errors. Additionally, a fault diagnosis system is developed to address potential actuator faults, enabling diagnosis of fault occurrence, fault type and fault information. Furthermore, a fault-tolerant CA method, inspired by the concept of daisy chain, is used to enhance the longevity of the thrust vectoring nozzle. Finally, the effectiveness of the proposed control strategy is verified by numerical simulation.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4581-4596"},"PeriodicalIF":3.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Fixed-Time Consensus of Uncertain Multi-Agent Systems With Event/Self-Triggered Strategy Under Directed Graphs","authors":"Zhuoning Zhang,&nbsp;Yongbao Wu,&nbsp;Lei Xue,&nbsp;Jian Liu,&nbsp;Changyin Sun","doi":"10.1002/rnc.7910","DOIUrl":"https://doi.org/10.1002/rnc.7910","url":null,"abstract":"<div>\u0000 \u0000 <p>This article studies the practical fixed-time consensus (Fd-TC) for uncertain multi-agent systems (MASs) under strongly connected directed graphs utilizing adaptive event/self-triggered controllers, respectively. Considering the uncertainty in the agent's non-linear dynamic parameters, the adaptive event-triggered controller is designed by incorporating an event-triggered strategy with an adaptive control scheme, which achieves the practical Fd-TC for uncertain non-linear MASs and the settling time remains constant irrespective of the initial conditions. Moreover, the designed controller is independent of any global information, including communication topology and network size. It also employs the hyperbolic tangent function to tackle Zeno and non-differential issues. Following this, the adaptive event-triggered controller serves as the foundation for introducing a self-triggered controller, which eliminates the necessity for continuous monitoring and guarantees practical Fd-TC. Furthermore, the results are extended to a more generalized case with uncertain disturbances, highlighting the adaptability of the designed controller. Finally, two numerical simulation examples are conducted to validate the efficacy of the developed controllers.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 10","pages":"4346-4358"},"PeriodicalIF":3.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144206953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuro-Observer Based Adaptive Fixed-Time Fault-Tolerant Control for Uncertain Teleoperation System With Input Saturation and Asymmetric Time-Varying Output Constraints","authors":"Longnan Li,&nbsp;Lanyong Zhang,&nbsp;Zhenyu Lu,&nbsp;Chenguang Yang","doi":"10.1002/rnc.7920","DOIUrl":"https://doi.org/10.1002/rnc.7920","url":null,"abstract":"<p>The issue of master-slave synchronization tracking control for uncertain teleoperation systems with input saturation and asymmetric time-varying output constraints under actuator failure is investigated. Firstly, a neural network-based nonlinear disturbance observer is designed to mitigate the negative impact of the compound uncertainty. Secondly, asymmetric barrier functions are introduced in the design of virtual control terms to implicitly handle the asymmetric time-varying output constraints issue. Following this, we leverage adaptive techniques to solve the problem of unknown control gains induced by actuator failure and develop an adaptive fixed-time fault-tolerant control approach. Using the Lyapunov stability theorem and fixed-time theory, it is rigorously proven that the closed-loop system is practically fixed-time stable and the system output is strictly confined within the asymmetric time-varying constraint boundaries. Finally, two typical actuator failure scenarios are considered during numerical simulations to validate the effectiveness and comprehensive performance of the developed approach.</p>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4536-4553"},"PeriodicalIF":3.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rnc.7920","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Special Issue on Model Predictive Control Under Disturbances and Uncertainties: Safety, Stability, and Learning","authors":"Wen-Hua Chen,&nbsp;Mark Cannon,&nbsp;Rolf Findeisen,&nbsp;Jun Yang","doi":"10.1002/rnc.7930","DOIUrl":"https://doi.org/10.1002/rnc.7930","url":null,"abstract":"&lt;p&gt;Model Predictive Control (MPC) has established itself as one of the most powerful advanced control strategies, combining conceptual simplicity with the ability to handle constraints and optimize performance. However, the presence of disturbances and uncertainties in real-world systems imposes significant challenges, necessitating robust, adaptive, and computationally efficient solutions. This Special Issue of the &lt;i&gt;International Journal of Robust and Nonlinear Control&lt;/i&gt; is dedicated to advancing the state-of-the-art in MPC under disturbances and uncertainties, with a focus on safety, stability, and the integration of learning techniques. We are proud to present a collection of 19 high-quality papers that address these challenges and push the boundaries of MPC research.&lt;/p&gt;&lt;p&gt;The Call for Papers for this Special Issue invited contributions on novel theoretical developments, innovative design and analysis tools, and practical applications of MPC in the presence of disturbances and uncertainties. The response from the research community was overwhelming, and after a rigorous peer review process, 19 papers were selected for publication. These contributions reflect the latest advancements in disturbance and uncertainty modeling, robust and adaptive MPC, learning-based approaches, and applications across diverse domains such as robotics, automotive systems, energy systems, and aerospace.&lt;/p&gt;&lt;p&gt;The accepted papers cover a wide range of topics, organized around the following key themes:&lt;/p&gt;&lt;p&gt;Liu et al. [&lt;span&gt;1&lt;/span&gt;] introduce a stochastic MPC framework for discrete nonlinear systems using a multistep control strategy, while Parsi et al. [&lt;span&gt;2&lt;/span&gt;] propose a scalable tube MPC approach for uncertain linear systems using ellipsoidal sets. Manzano et al. [&lt;span&gt;3&lt;/span&gt;] explore input-to-state stability in predictive control based on continuous projected kinky inference, providing theoretical guarantees for uncertain systems.&lt;/p&gt;&lt;p&gt;Yang [&lt;span&gt;4&lt;/span&gt;] presents a data-driven MPC framework for unknown linear systems using online learning, and Klöppelt et al. [&lt;span&gt;5&lt;/span&gt;] introduce a novel constraint-tightening approach for robust data-driven predictive control. Pan et al. [&lt;span&gt;6&lt;/span&gt;] bridge the gap between data-driven methods and stochastic MPC, offering new insights into data-driven stochastic control.&lt;/p&gt;&lt;p&gt;Fang et al. [&lt;span&gt;7&lt;/span&gt;] develop an integrated MPC scheme with disturbance preview, enhancing performance in the presence of known disturbances. Gao et al. [&lt;span&gt;8&lt;/span&gt;] demonstrate practical applications of disturbance rejection in a parabolic trough solar field, and Yu et al. [&lt;span&gt;9&lt;/span&gt;] combine model-free predictive control with a linear extended state observer for disturbance estimation in power converters.&lt;/p&gt;&lt;p&gt;Kögel et al. [&lt;span&gt;10&lt;/span&gt;] address safety-critical applications in autonomous systems through hierarchical MPC and planning. Hall et al. [&lt;span&gt;11&lt;/span&gt;] investigate stability and feasibility in swi","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 7","pages":"2475-2477"},"PeriodicalIF":3.2,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rnc.7930","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fixed-Time Adaptive Neural Control for Physical Human–Robot Collaboration With Time-Varying Workspace Constraints","authors":"Yuzhu Sun,&nbsp;Mien Van,&nbsp;Stephen McIlvanna,&nbsp;Nguyen Minh Nhat,&nbsp;Seán McLoone,&nbsp;Dariusz Ceglarek,&nbsp;Shuzhi Sam Ge","doi":"10.1002/rnc.7922","DOIUrl":"https://doi.org/10.1002/rnc.7922","url":null,"abstract":"<p>Effective physical human–robot collaboration (pHRC) requires strict safety guarantees since robots coordinate with human actions in a shared workspace. Moreover, compliance is essential, enabling robots to adjust their stiffness and behavior in response to human interaction forces. This paper presents a novel fixed-time adaptive neural control method for handling safety constraints that occur in physical human–robot collaboration while also guaranteeing compliance during intended force interactions. The proposed method combines the benefits of compliance control, time-varying integral barrier Lyapunov function (TVIBLF), and fixed-time techniques, which not only achieve compliance during physical contact with human operators but also guarantee time-varying workspace constraints and fast tracking error convergence without any restriction on the initial conditions. Furthermore, a neural adaptive control law is designed to compensate for the unknown dynamics and disturbances of the robot manipulator such that the proposed control framework is overall fixed-time-converged and capable of online learning without any prior knowledge of robot dynamics and disturbances. The proposed approach is finally validated on a simulated two-link robot manipulator and then extended to the simulated UR10 robot. Simulation results show that the proposed controller is superior in the sense of both the tracking error and convergence time compared with the existing barrier Lyapunov function-based controllers while simultaneously guaranteeing compliance and safety.</p>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4480-4496"},"PeriodicalIF":3.2,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rnc.7922","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Triggered Impulsive Synchronization Control of Multi-Agent Systems With Sensing Delays and Deception Attacks","authors":"Jiangyan He,&nbsp;Xing Guo,&nbsp;Lianghao Ji,&nbsp;Zili Chen","doi":"10.1002/rnc.7924","DOIUrl":"https://doi.org/10.1002/rnc.7924","url":null,"abstract":"<div>\u0000 \u0000 <p>The paper explores the mean-square bounded synchronization problem of multi-agent systems (MASs) in the presence of lumped factors, including stochastic interferences, edge-based deception attacks, and sensing delays. To tackle this challenging problem, a new secure delayed impulsive control protocol is proposed, in which the agents receive erroneous signals from their neighbors due to edge-based deception attacks on the transmission channel. Two self-triggered strategies, static and dynamic, are designed to drive the impulsive control, which is correlated with the sensing delay time, the probability of deception attacks occurring, as well as the intensity of the attack signals. Further, we have introduced a boundary floating function to mitigate the impact of external uncontrollable factors on the bounded synchronization of MASs under the dynamic self-triggered strategy. Compared with previous studies, this strategy takes into account the natural disturbances and exhibits greater robustness. Some criteria for the mean-bounded synchronization of MASs are obtained under the designed control protocol by applying the Lyapunov stability theory, Itô formula, and Gronwall-Bellman inequality. Finally, these conclusions are verified by simulation with two examples.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4567-4580"},"PeriodicalIF":3.2,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}