Article
Automation & Control Systems
Wasif Shabbir, Li Aijun, Cui Yuwei
Summary: In this work, a novel active fault-tolerant control (FTC) design scheme is developed for nonlinear dynamic systems with modelling imperfections, parametric uncertainties, and sensor faults. An adaptive radial basis function neural network (RBFNN) is used to estimate the uncertain part of the system dynamics, while a nonlinear observer based on the estimated dynamics is designed for sensor fault estimation (FE). The proposed FTC design incorporates the real-time sensor FE into the sliding mode control (SMC) technique and uses a double power-reaching law to improve convergence and mitigate chattering. The stability of the developed active FTC law is proven using the Lyapunov method, and the scheme is implemented on a nonlinear simulation of an unmanned aerial vehicle (UAV) with successful results.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Muhammad Shamrooz Aslam, Irfan Qaisar, Abdul Majid, Perumal Ramaraj
Summary: This paper investigates the mechanism for estimation of sensor and actuator faulty control problem for a class of nonlinear systems, utilizing a transformation scheme and sliding mode observer method. By applying Lyapunov stability theory and linear matrix inequalities, sufficient criteria for ensuring bounded stability are obtained.
Article
Automation & Control Systems
Lejun Chen, James F. Whidborne
Summary: This paper proposes a generalized multivariable super-twisting observer for a class of nonlinear systems with multiplicatively linked unmeasured variables. It provides a sufficient condition for the convergence of the reconstruction errors associated with the unmeasurable variables to zero in finite time. The approach is then applied to estimate aircraft icing accretion despite unreliable sensor measurement, and the results show the capability of the observer to estimate the change of drag coefficient induced by icing accretion and reconstruct the unreliable pitch rate sensor measurement simultaneously.
Article
Automation & Control Systems
Zengjie Zhang, Dirk Wollherr, Homayoun Najjaran
Summary: This article presents a novel force-sensor-less method for estimating external forces in second-order robotic systems. The method utilizes an integral sliding mode observer (ISMO) as a second-order differentiator for position measurement. The ISMO allows for estimation of system states and disturbance without explicit force and velocity measurements. The method is evaluated through numerical simulation and compared with a conventional sliding mode observer (SMO), demonstrating its superior performance.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Zhifeng Gao, Sen Wang
Summary: This study proposes a fault estimation and fault tolerant control (FTC) scheme for a class of nonlinear spacecraft formation flying systems. An decentralized unknown input observer is designed to estimate unknown actuator fault factors, and the estimated values are used for the design of a distributed fault tolerant formation controller. A distributed fault tolerant formation control algorithm using adaptive terminal sliding mode control (ATSMC) technique is proposed to ensure synchronization of follower spacecraft with leader spacecraft in the presence of actuator fault and saturation. The effectiveness of the proposed FTC scheme is verified through numerical examples.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2021)
Article
Automation & Control Systems
Xingjian Sun, Haobo Kang, Hongjun Ma
Summary: This article focuses on sensor fault estimation and fault-tolerant controller design for IT2 fuzzy systems using a sliding mode approach. A novel sliding mode observer and a sliding mode controller in the form of an IT2 fuzzy model are introduced to accurately estimate system states, eliminate sensor faults, and stabilize closed-loop systems. An example of a bolt-tightening tool model is used to demonstrate the validity of the proposed results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Nitin K. Singh, Abhisek K. Behera
Summary: In this paper, a twisting observer is proposed for robustly estimating the states of a second-order uncertain system. The observer approximates the unknown sign term for the non-measurable state with a delayed output-based switching function, and achieves the desired steady-state accuracy by controlling the delay parameter. The application of the observer to output feedback stabilization is also discussed.
Article
Computer Science, Information Systems
Tan Van Nguyen, Huy Q. Tran, Khoa Dang Nguyen
Summary: This study focuses on estimating faults and uncertainties in electro-hydraulic systems through the use of sliding mode observer and unknown input observer models, as well as proposing a combination of actuator and sensor compensation fault techniques. Numerical simulations demonstrate that the proposed method is more efficient than traditional PID controllers and sensor fault compensation methods, even in the presence of noise.
Article
Automation & Control Systems
Mohsen Farbood, Zeinab Echreshavi, Mokhtar Shasadeghi, Saleh Mobayen
Summary: This paper proposes an event-triggered integral sliding mode control (ISMC) for perturbed nonlinear Takagi-Sugeno (TS) fuzzy systems. A disturbance observer is designed to estimate and reduce the unmatched disturbances. Two types of sliding surfaces are established to reduce computational burden and communication resources. The proposed control scheme ensures system performance enhancement and Zeno-free behavior.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Karim Ahmadi, Davood Asadi, Abdelrazzak Merheb, Seyed- Yaser Nabavi-Chashmi, Onder Tutsoy
Summary: A fault-tolerant controller is proposed in this paper to handle the dynamics changes caused by motor faults in multirotor UAVs, in order to ensure flight safety and reliability. The fault-tolerant controller consists of a nonlinear observer and Sliding Mode Control (SMC), which predicts the effect of motor faults and enhances the robustness of SMC against uncertainties and disturbances.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Mathematics
Slim Dhahri, Omar Naifar
Summary: In this study, the challenges posed by external disturbances and actuator and sensor faults in LPV systems are addressed through fault estimation and fault-tolerant tracking control. An adaptive LPV sliding mode observer is developed for simultaneous state and fault estimation, and an FTTC is synthesized based on the online FE information to compensate for the fault effect and improve tracking performance. The stability of the system is ensured using Lyapunov stability theory and LMIs.
Article
Computer Science, Information Systems
Xiaoli Zhang, Zhengyu Zhu, Yang Yi
Summary: This paper discusses a novel control algorithm with fault tolerance and anti-disturbance capabilities for systems affected by actuator faults and mismatched disturbances. Fault diagnosis observer and disturbance observer are designed to estimate unknown faults and disturbances, and a sliding mode controller is proposed to compensate for faults and eliminate disturbances simultaneously. The use of a convex optimization algorithm ensures system stability, with favorable anti-disturbance and fault-tolerant results being demonstrated. The algorithm's validity is confirmed through simulation results on typical UAV systems.
Article
Computer Science, Artificial Intelligence
Muhammad Taimoor, Xiao Lu, Wasif Shabbir, Chunyang Sheng, Muhammad Samiuddin
Summary: This research proposed an adaptive neural network observer to enhance fault detection accuracy and used Lyapunov function theory to adaptively update neural network parameters. The strategy was validated on Boeing 747 100/200 aircraft, demonstrating superior robustness to various faults and disturbances.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Habib Dimassi
Summary: A new fault reconstruction and estimation scheme is proposed in this paper for a class of nonlinear systems with both actuator and sensor faults, under relaxed assumptions. The method enlarges the class of systems and applications compared to existing methods, and utilizes Lyapunov analysis and sliding modes theory for theoretical results. Simulation results on robot systems and vehicles validate the proposed scheme's good performance under disturbances and noise.
Article
Automation & Control Systems
Habib Hamdi, Mickael Rodrigues, Bouali Rabaoui, Naceur Benhadj Braiek
Summary: This paper addresses the problem of fault-tolerant control and fault reconstruction for linear parameter varying descriptor systems with time delay. A polytopic sliding mode observer is synthesized to achieve simultaneous reconstruction of system states and actuator faults, and a fault-tolerant controller is designed to compensate for actuator faults impact by stabilizing the closed-loop system. The gains for the controller and observer are obtained through linear matrix inequalities using convex optimization techniques, showcasing the efficacy of the proposed approach.
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Zhuang Liu, Xinpo Lin, Yabin Gao, Ruiqi Xu, Jiahui Wang, Yijie Wang, Jianxing Liu
Summary: This paper investigates the fixed-time control problem of DC-DC buck converter systems with mismatched disturbances. Sliding mode fixed-time observers are constructed to estimate the matched and mismatched disturbances, and a novel segmented terminal sliding mode control variable considering the mismatched disturbances is designed. Additionally, a new second-order fixed-time reaching law is proposed to improve the tracking performance. A novel fixed-time nonsingular TSMC method based on the fixed-time observers is proposed to achieve accurate control in a fixed-time independent of the initial state. Comparative experiments are conducted to validate the effectiveness and practicality of the proposed control strategy.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Engineering, Electrical & Electronic
Xinpo Lin, Chengwei Wu, Weiran Yao, Zhuang Liu, Xiaoning Shen, Ruiqi Xu, Guanghui Sun, Jianxing Liu
Summary: In this article, a fixed-time observer-based sliding-mode control strategy is proposed for a permanent-magnet synchronous motor. The designed controller improves the control performance and guarantees the convergence in a fixed-time manner. An observer is constructed to estimate and attenuate parameter uncertainties and load disturbance to ensure robustness. Experimental results demonstrate the effectiveness and advantages of the proposed control scheme.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Automation & Control Systems
Zhen Zhang, Yinan Guo, Dunwei Gong, Jianxing Liu
Summary: In this study, an improved integral sliding-mode control method is proposed to address the difficulties in controlling the drilling of a hydraulic roofbolter. By using a nonlinear extended state observer and an uncertain gain adaptive law, the proposed method achieves better tracking performance and exhibits good dynamic and steady-state performance.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Automation & Control Systems
Yizhuo Sun, Jianxing Liu, Yabin Gao, Zhuang Liu, Yue Zhao
Summary: In this article, an improved adaptive neural network (NN) nonsingular terminal sliding mode control (NTSMC) scheme is proposed for prescribed-performance trajectory tracking of manipulators with unmodeled dynamics and input saturation. An auxiliary system is constructed to reduce the adverse effect of input saturation. An improved NN-based NTSMC strategy is developed to achieve tunable prescribed tracking errors under limited control and without prior precise knowledge of uncertainties. Theoretical analysis using the Lyapunov function proves the uniform ultimate boundedness of the closed-loop system. Comparative experiments on a ROKAE platform confirm the improved tracking performance of the proposed scheme.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Automation & Control Systems
Ruixia Liu, Ming Liu, Yan Shi, Junsuo Qu
Summary: This paper investigates the adaptive fixed-time control problem for a class of uncertain nonlinear systems with asymmetric time-varying full-state constraints. A nonlinear state-constrained function (NSCF) approach is proposed to handle the full-state constraints problem without switching controller structure and additional assumption about virtual control. Fixed-time command filters (FTCFs) are used to overcome the complexity problem of the traditional backstepping method, and error compensation mechanisms are designed to remove filtering errors. An adaptive fixed-time control strategy is designed under the backstepping control framework, ensuring that all signals in the closed-loop system and tracking error are bounded within fixed-time, and all states are guaranteed to maintain in predefined regions. A simulation example is provided to illustrate the effectiveness of the proposed control scheme.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Engineering, Mechanical
Yizhuo Sun, Jiyuan Kuang, Yabin Gao, Weiliang Chen, Jiahui Wang, Jianxing Liu, Ligang Wu
Summary: This work investigates fixed-time trajectory tracking with prescribed performance for a multi-degree-of-freedom manipulator system subjected to unknown dynamics and input saturation. The radial basis function neural network (RBFNN) is used to compensate for the unknown dynamics online. A prescribed performance function (PPF) is employed to transform the tracking error and ensure the transient and steady-state performance of the control. A fixed-time auxiliary system is proposed to compensate for the input saturation impact, and a non-singular terminal sliding surface is designed based on the compensation error. The stability of the closed-loop system is analyzed, and experimental results validate the effectiveness of the proposed method.
NONLINEAR DYNAMICS
(2023)
Article
Automation & Control Systems
Chang Liu, Yueshi Guan, Jianxing Liu, Yijie Wang, Dianguo Xu
Summary: This article proposes a power modulation strategy that improves linearity, power capability, and efficiency simultaneously. The on/off and Outphasing control modes are combined to ensure shallow phase depth in a wide power range. Hybrid modules composed of load independent class f(2) structure and symmetrical class f(2) structures are adopted to match the proposed control scheme, providing constant output voltage in the zero voltage switching (ZVS) state. With optimal efficiency and minimal voltage and current stress, the proposed system can linearly regulate power. An implementation with four modules demonstrates seamless and linear control of output power with efficiency within 82%-93.5%.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Xinpo Lin, Bo Zhang, Shuxian Fang, Ruiqi Xu, Shichang Guo, Jianxing Liu
Summary: This paper proposes a novel adaptive-gain generalized super twisting algorithm for permanent magnet synchronous motors. The stability of the algorithm is proven using the Lyapunov method. The controllers of the speed-tracking loop and the current regulation loop are designed based on the proposed algorithm, and the dynamically adjusted gains contribute to improved transient performance and system's robustness.
Article
Computer Science, Artificial Intelligence
Run Li, Ming Liu, Johannes Teutsch, Dirk Wollherr
Summary: In this paper, a hybrid heuristic algorithm called PSO-WOA is proposed to solve a multi-objective optimization problem in point-to-point trajectory planning of space robots. The algorithm combines the strengths of particle swarm optimization and whale optimization algorithm, and is applied to generate optimal trajectories for redundant free-floating space robots.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Geology
Dongjie Bi, Xuefa Shi, Mu Huang, Miao Yu, Fangyu Shen, Jianxing Liu, Tiancheng Zhou, Tianyu Chen, Fengdeng Shi, Xiaojing Wang, Xiaoke Qiang, Jihua Liu
Summary: Pelagic sediments enriched in rare earth elements and yttrium (REY) have attracted significant attention. However, the mechanism responsible for this enrichment remains unclear due to challenges in obtaining robust geochronology. In this study, we integrated multiple geochronologic approaches to determine a chronostratigraphic framework for a pelagic sediment core collected from the northwestern Pacific Ocean. Our results indicate that REY-rich sediments were deposited prior to -2.5 Ma, with a highly REY-rich sediment layer deposited at -11.5-9.5 Ma. We propose that a low sedimentation accumulation rate and the contribution from active bottom currents are key factors in the enrichment of REY in pelagic sediments.
ORE GEOLOGY REVIEWS
(2023)
Article
Computer Science, Information Systems
Ming Liu, Qiuhong Liu, Lixian Zhang, Guangren Duan, Xibin Cao
Summary: This paper investigates attitude control for flexible spacecraft with actuator faults and limited communication resources. A control torque quantization scheme is proposed to reduce communication burden, and an integral sliding mode control method is designed for stabilization and near-optimal performance. Simulation results demonstrate the efficacy of the proposed method.
SCIENCE CHINA-INFORMATION SCIENCES
(2023)
Proceedings Paper
Automation & Control Systems
Weiming Zhang, Dezhi Xu, Weilin Yang, Jianxing Liu, Fei Hua
Summary: In this paper, a dual observer based model-free adaptive control strategy is proposed for MIMO nonlinear systems with disturbances and I/O constraints. The dual observers consist of an adaptive observer and a discrete extended state observer, which are used for dynamic reconfiguration of the system, estimation of time-varying parameters, and composite disturbance estimation. Based on the information from the dual observers, a dynamic anti-windup compensator and an improved prescribed performance control method are proposed to solve the I/O constraint problem in the sliding mode controller. Stability analysis and simulations are conducted for performance verification.
2023 IEEE 12TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE, DDCLS
(2023)
Article
Computer Science, Artificial Intelligence
Biqing Qi, Bowen Zhou, Weinan Zhang, Jianxing Liu, Ligang Wu
Summary: In this article, a simple and efficient defense method from the geometric constraint perspective is proposed, which can significantly improve the robustness against adversarial examples while maintaining excellent performance on normal examples.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yundong Sun, Dongjie Zhu, Haiwen Du, Zhaoshuo Tian
Summary: This paper proposes a multi-hop heterogeneous neighborhood information fusion graph representation learning method, which solves the problem of aggregating multi-hop neighborhood information and learning hybrid metapaths by autonomously extracting multi-hop hybrid neighbors and selectively aggregating different-hop neighborhood information within the same hybrid metapath. It constructs a hierarchical semantic attention fusion model to efficiently integrate different-hop and different-path neighborhood information.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Automation & Control Systems
Jinyu Fu, Guanghui Sun, Jianxing Liu, Weiran Yao, Ligang Wu
Summary: This article addresses a hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP) and proposes approaches for optimal hierarchical coverage and multi-UAV collaboration in a 3-D complex obstacle environment. The proposed strategies include a multi-UAV multilayer projection clustering algorithm, a straight-line flight judgment, and an improved adaptive window probabilistic roadmap algorithm. The sequencing-bundling-bridging framework is used to solve the TSP with obstacles constraints. Simulation experiments demonstrate the feasibility of the proposed strategies in complex obstacle environments for HMDTSP.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Wenjie Cao, Fuke Wu, Minyu Wu
Summary: This paper focuses on the stability of stochastic hybrid systems with random delay driven by a singularly perturbed Markov chain. The limit system is obtained using weak convergence and the martingale method. By utilizing the limit system as a bridge, the moment exponential stability of the original system is established using Razumikhin-type techniques. An example is provided to illustrate the obtained result.
SYSTEMS & CONTROL LETTERS
(2024)
Article
Automation & Control Systems
Vincenzo Basco
Summary: This paper discusses distributed optimization techniques in multi-agent systems with time-varying communication networks and proposes a novel approach that leverages group actions and probabilistic selection of initial states to solve real-world optimization problems in decentralized environments.
SYSTEMS & CONTROL LETTERS
(2024)
Article
Automation & Control Systems
Jennifer Przybilla, Igor Pontes Duff, Peter Benner
Summary: This paper considers the problem of finding surrogate models for large-scale second-order linear time-invariant systems with inhomogeneous initial conditions. Two methodologies are proposed: reducing each component independently and extracting dominant subspaces from Gramians. The error bounds for the overall output approximation are also discussed.
SYSTEMS & CONTROL LETTERS
(2024)
Article
Automation & Control Systems
Shubham Singh, Anoop Jain
Summary: This paper proposes a distributed control design methodology to stabilize a desired formation shape in a multi-agent system while incorporating collision avoidance and connectivity preservation simultaneously. Time-varying constraints are applied to handle collision avoidance and connectivity preservation, and the concept of asymmetric time-varying barrier Lyapunov function is exploited to derive the stabilizing distributed control law.
SYSTEMS & CONTROL LETTERS
(2024)
Article
Automation & Control Systems
Han Zhang, Axel Ringh
Summary: Inverse Optimal Control (IOC) is a powerful framework for learning behavior from expert observations. In this study, we focused on identifying the cost and feedback law from observed trajectories. We proved that identifying the cost is generally an ill-posed problem, but we constructed an estimator for the cost function and showed that it provides a statistically consistent estimate for the true underlying control gain. The constructed estimator is based on convex optimization and exhibits statistical consistency in practice.
SYSTEMS & CONTROL LETTERS
(2024)
Article
Automation & Control Systems
Ky Quan Tran, Pham Huu Anh Ngoc
Summary: This paper investigates the exponential contraction in mean square of general functional differential equations with Markovian switching. Explicit criteria for such contraction are derived through a novel approach. An illustrative example is provided.
SYSTEMS & CONTROL LETTERS
(2024)
Article
Automation & Control Systems
Jiangyan Pu, Qi Zhang
Summary: This paper examines the continuous time intertemporal consumption and portfolio choice problems of an investor in a generalized stochastic differential utility preference of Epstein-Zin type with subjective beliefs and ambiguity. The paper provides closed-form optimal consumption and portfolio solutions with subjective beliefs and numerical solutions with ambiguity for the Heston model in an incomplete market.
SYSTEMS & CONTROL LETTERS
(2024)
