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Fuzzy Fixed-Time Fault-Tolerant control of Uncertain Nonlinear systems with Non-affine Faults and Its Application in Manipulator systems

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International Journal of Fuzzy systems 2024年第2期26卷 540-552页

作者： Bai, Yang Sun, Zong-Yao Chen, Chih-Chiang Meng, Qinghua Institute of Automation Qufu Normal University Shandong Qufu273165 China Department of Systems and Naval Mechatronic Engineering National Cheng Kung University Tainan70101 Taiwan School of Mechanical Engineering Hangzhou Dianzi University Zhejiang Hangzhou310018 China

This paper aims to solve two challenging problems in fuzzy control: the complexity explosion caused by iterative derivation of the virtual control laws in design process and the fuzzy adaptive feedback stability for a class of uncertain nonlinear systems. Firstly, the difficulty in backstepping control design for high-order nonlinear systems is solved by combining adding a power integrator method with the dynamic surface control technique and using the fuzzy logic system to approximate unknown nonlinear functions. Then, the non-affine fault of system states and control output can be transformed into a nonlinear one with unknown parameters. The proposed control strategy not only drives the tracking error to converge to an adjustable region of the origin within a fixed time, but also maintains the stability of the closed-loop systems. An advantage is that the convergence time does not depend on the initial state. Finally, the stabilization of a manipulator system is investigated to demonstrate the effectiveness of the control scheme. © The Author(s) under exclusive licence to Taiwan Fuzzy systems Association 2023.

关键词： Fuzzy control

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Parameter Estimation and Tracking control of MIMO Linear systems Without Prior Knowledge of control Signs and Parameter Bounds

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IEEE Transactions on Automatic control 2024年第6期70卷 3695-3710页

作者： Xu, Yuchun Zhang, Yanjun Zhang, Ji-Feng Chinese Academy of Sciences Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Beijing100190 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology State Key Lab of Automation Intelligent Unmanned Systems Beijing100081 China University of Chinese Academy of Sciences School of Mathematics Sciences Beijing100149 China Zhongyuan University of Technology School of Automation and Electrical Engineering Zhengzhou450007 China Chinese Academy of Sciences Academy of Mathematics and Systems Science Beijing100190 China

Dealing with the uncertain high-frequency gain matrix, denoted as Kp, is a fundamental problem in multivariable adaptive control systems. In this paper, we propose a new solution for parameter estimation and adaptive control for a general class of multi-input multi-output discrete-time linear time-invariant systems. The proposed scheme does not require any prior knowledge of the sign or bound information of Kp, and thus, significantly relaxes the design conditions in traditional multivariable adaptive control systems. Compared with the commonly used Nussbaum gain or multi-model techniques for addressing the unknown signs of Kp, the proposed scheme does not rely on any additional design conditions or any switching mechanism, while still ensuring closed-loop stability and asymptotic output tracking. Specifically, an output feedback adaptive control law is developed based on a matrix decomposition technique, which leads to derivation of a modified estimation error model. Subsequently, a gradient-based parameter update law is formulated only relying on the non-zero condition of the leading principle minors of Kp. Through designing gain functions and stable filters, the controller is always non-singular and does not involve any causal contradiction problem. Simulation study showcases the design process and demonstrates the effectiveness of the proposed scheme. © 1963-2012 IEEE.

关键词： MIMO systems

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Nested Sliding Mode control Based Impact Angle Guidance with Bounded Input

Nested Sliding Mode Control Based Impact Angle Guidance with...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Surve, Prajakta Kumar, Shashi Ranjan Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

In this paper, a nonlinear guidance law for impact angle-constrained interception of nonmaneuvering targets, respecting the bounds on the control input - the commanded interceptor lateral acceleration, is proposed. By modeling the required interceptor lateral acceleration as a first-order dynamics, which is a function of the maximum permissible value of control input and guidance command, the control input is maintained within the predefined bounds. The dynamics is chosen in such a way that the resulting input will never violate the prescribed bounds. To design the guidance command, also known as commanded lateral acceleration, we employ a sliding surface based on the error between actual and desired line-of-sight (LOS) angles and the LOS rate, facilitating a collision course with zero miss distance. A secondary sliding surface is designed as a function of the primary sliding surface and its rate. This sliding surface enables the control over the required interceptor lateral acceleration. An effective guidance command for precise interception at given impact angle, considering the bounds on control input, is then derived using the sliding mode control technique. Numerical simulations validate the merits and claims of the presented guidance approach. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Sliding mode control

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Fault Diagnosis Based on the Updating Strategy of Interval-Valued Belief Structures

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Chinese Journal of Electronics 2025年第4期23卷 753-760页

作者： Xiaobin Xu Ping Liu Yanbo Sun Chenglin Wen Institute of Systems Science and Control Engineering School of Automation Hangzhou Dianzi University Hangzhou China Department of Control Science and Engineering School of Astronautics Harbin Institute of Technology Harbin China

This paper presents the dynamic method for fault diagnosis based on the updating of Interval-valued belief structures (IBSs). The classical Jeffrey's updating rule and the linear updating rule are extended to the framework of IBSs. Both of them are recursively used to generate global diagnosis evidence with the form of Interval basic belief assignment (IBBA) by updating the previous evidence with the incoming evidence. The diagnosis decision can be made by global diagnosis evidence. In the process of evidence updating, the similarity factors of evidence are used to determine switching between the extended Jeffrey's and linear updating rules, and to calculate the linear combination weights. The diagnosis examples of machine rotor show that the proposed method can provide more reliable and accurate results than the diagnosis methods based on Dempster-Shafer evidence theory.

关键词： Fault diagnosis Accuracy Evidence theory Rotors Switches Reliability theory Real-time systems

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Adaptive Unscented Kalman Filter Based Sensor Fusion for Aircraft Positioning Relative to Unknown Runway

Adaptive Unscented Kalman Filter Based Sensor Fusion for Air...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Ghosh, Nabarun Maity, Arnab Intelligent Systems and Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Maharashtra Mumbai400076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper proposes an estimator to provide precise position, velocity, and orientation for a landing aircraft relative to the runway based on image sensors, IMU sensor data, and barometric sensor measurements. This work excludes GPS data, as it is expected that the proposed estimator can be used for fault detection in GPS and instrument landing systems. The runway is unknown, and hence, its width is estimated online. An adaptive UKF-based approach is adopted to estimate the states. In order to verify the nearer-to-practical performance and accuracy of bias estimation, realistically simulated data that constitute noises and biases from the sensors are taken into consideration. The proposed approach provides a solution for nonlinear state estimation in the presence of measurement noises that are non-additive. In addition to this, it provides estimates of the unknown measurement noise covariance. A comparative study is conducted between the conventional UKF and the proposed AUKF to analyze the adopted approach. Results show that the proposed algorithm gives comparable estimation results and faster convergence than the conventional UKF. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Fault detection

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Quality-Relevant Modeling and Monitoring of Industrial Cyber-Physical systems: The Semi-Supervised Dynamic Latent Variable Models

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 39-47页

作者： Zhou, Le Wang, Yaoxin Wu, Yuanqing He, Shenghuang Song, Zhihuan Zhejiang University of Science and Technology Department of Automation and Electrical Engineering Hangzhou310023 China Guangdong University of Technology Department of Automation Guangzhou510006 China Dongguan University of Technology Department of Computer Science and Technology Dongguan523808 China Ningbo Industrial Internet Institute Ningbo315012 China Zhejiang University Department of Control Science and Engineering Hangzhou310027 China

In modern industrial cyber-physical systems, a mass of process variables has been obtained by the high-sampling online sensors. Meanwhile, the key quality indexes are usually obtained infrequently from the laboratory. Hence, these quality variables are with low sampling rate. To avail of the complete process and quality variables with various sampling rates in the dynamic processes, a set of semi-supervised dynamic latent variable models are proposed for dynamic modeling and quality-relevant monitoring. The proposed models have built a unified structure to consider both the auto-correlations and cross-correlations between the process and quality variables with unbalanced sampling sizes. Hence, the feature extraction of the time series data is dynamically adjusted under the guidance of the quality variables. Then, the quality-relevant monitoring schemes are proposed, which is validated by a numerical case and an actual wastewater treatment process. © 2024 IEEE. All rights reserved.

关键词： Indexes Probabilistic logic Kalman filters Noise Cyber-physical systems Analytical models Parameter estimation Time series analysis Process monitoring Numerical models

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A Diffusion Model for Traffic Data Imputation

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 606-617页

作者： Bo Lu Qinghai Miao Yahui Liu Tariku Sinshaw Tamir Hongxia Zhao Xiqiao Zhang Yisheng Lv Fei-Yue Wang the School of Artificial Intelligence University of Chinese Academy of Sciences Baidu Inc. IEEE the State Key Laboratory for Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Meituan Guangdong University of Technology the Department of Transportation Engineering School of Transportation Science and Technology Harbin Institute of Technology

Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems(ITS) in the real world. As a state-of-the-art generative model, the diffusion model has proven highly successful in image generation, speech generation, time series modelling *** now opens a new avenue for traffic data imputation. In this paper, we propose a conditional diffusion model, called the implicit-explicit diffusion model, for traffic data imputation. This model exploits both the implicit and explicit feature of the data simultaneously. More specifically, we design two types of feature extraction modules, one to capture the implicit dependencies hidden in the raw data at multiple time scales and the other to obtain the long-term temporal dependencies of the time series. This approach not only inherits the advantages of the diffusion model for estimating missing data, but also takes into account the multiscale correlation inherent in traffic data. To illustrate the performance of the model, extensive experiments are conducted on three real-world time series datasets using different missing *** experimental results demonstrate that the model improves imputation accuracy and generalization capability.

关键词： Data imputation diffusion model implicit feature time series traffic data

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LiDAR Odometry with Pre-filtering of Plane Feature Points 36

LiDAR Odometry with Pre-filtering of Plane Feature Points

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36th International Technical Meeting of the Satellite Division of the institute of Navigation, ION GNSS+ 2023

作者： Lee, Hanyeol Jung, Jae Hyung Park, Chan Gook Department of Aerospace Engineering Automation and Systems Research Institute Seoul National University Korea Republic of

ISBN: (纸本)9780936406350

In this paper, we propose a pre-filtering method of geometric measurement for LiDAR odometry, which reduces a localization error by data association based on a statistical property. Recently, LiDAR odometry has been mainly developed in such a way that geometric feature points are matched for pose estimation. One of the critical problems affecting localization performance is false association between measurements that deviate from the assumption of matching geometrically identical features in 3D. We propose a pre-filtering method using stable plane feature points. To reduce the risk of false association, a stable plane feature is selected using the covariance of the feature point group on a local plane. After the pre-filtering process, odometry is performed by solving the data association of the measurement. To verify the proposed method, we formulate the LiDAR odometry in the LOAM framework, compare the accuracy of localization with LOAM, and show the improved result through Monte Carlo simulation. © 2023 Proceedings of the 36th International Technical Meeting of the Satellite Division of the institute of Navigation, ION GNSS+ 2023. All rights reserved.

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System for Determining the Shape of the Wavefront of a Nonsinusoidal Periodic Acoustic Wave 17

System for Determining the Shape of the Wavefront of a Nonsi...

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17th International Conference on engineering of Modern Electric systems, EMES 2023

作者： Codoban, Adrian Coroiu, Laura Gergely, Eugen Sarosi, Jozsef University of Oradea Department Control Systems Engineering and Management Oradea Romania University of Szeged Department of Mechatronics and Automation Szeged Hungary

ISBN: (纸本)9798350310634

The shape of the wavefront is important for the most realistic reproduction of the acoustic wave. In acoustics, the wave front (or wave surface) is defined as the totality of points in the space of the propagating medium that have the same instantaneous elongation amplitude. In the ideal case, in a homogeneous and isotropic propagation medium without other disturbances, the wave has a spherical symmetry, i.e. the shape of the wavefront is circular and at large distances from the wave source, due to dispersion, the shape of the wavefront can be considered plan. In practice, however, due to the multiple component harmonics, reflections and possible summations of the primary acoustic wave, the elongation has a non-sinusoidal shape, and the wavefront may have an irregular random shape. Moreover, if the source of the wave or bodies from which it is reflected are in motion, the shape of the wavefront may even be variable in time. The paper presents a method for determining the shape of the wave front of a non-sinusoidal periodic plane acoustic wave, resulting from the addition of several harmonic components, reflected waves, etc. It uses an array of omnidirectional capacitive microphones arranged in line, at equal distances between them. At each of the microphones, the acoustic wave is captured out of phase depending on the position of the microphone in space and the shape of the wave front. These phase shifts placed next to each other give an image of the shape of the wavefront captured by the microphone system. The method presented in this paper reproduces sounds very realistically and can be used in Active Noise Cancel systems, in open spaces, with one or more mobile noise sources. One of the benefits is the increase in hearing comfort in noisy environments. Another is to record sounds with high fidelity. © 2023 IEEE.

关键词： Wavefronts

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A Methodology Establishing Linear Convergence of Adaptive Gradient Methods Under PL Inequality 27

A Methodology Establishing Linear Convergence of Adaptive Gr...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Chakrabarti, Kushal Baranwal, Mayank Tata Consultancy Services Research Mumbai India Department of Systems & Control Engineering Indian Institute of Technology India

ISBN: (纸本)9781643685489

Adaptive gradient-descent optimizers are the standard choice for training neural network models. Despite their faster convergence than gradient-descent and remarkable performance in practice, the adaptive optimizers are not as well understood as vanilla gradient-descent. A reason is that the dynamic update of the learning rate that helps in faster convergence of these methods also makes their analysis intricate. Particularly, the simple gradient-descent method converges at a linear rate for a class of optimization problems, whereas the practically faster adaptive gradient methods lack such a theoretical guarantee. The Polyak-Lojasiewicz (PL) inequality is the weakest known class, for which linear convergence of gradient-descent and its momentum variants has been proved. Therefore, in this paper, we prove that AdaGrad and Adam, two well-known adaptive gradient methods, converge linearly when the cost function is smooth and satisfies the PL inequality. Our theoretical framework follows a simple and unified approach, applicable to both batch and stochastic gradients, which can potentially be utilized in analyzing linear convergence of other variants of Adam. © 2024 The Authors.

关键词： Cost functions

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