This paper investigates the problem of l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> observer design for positive switched systems with time-varying delays via delta operator approach. The purpose is to design a positive observer such that the estimated error exponentially converges to zero and the l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -gain from the disturbance input to the estimated error is less than a prescribed level. Based on the average dwell time approach, a sufficient condition for the existence of a positive l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> observer for the considered system is established by constructing an appropriate co-positive type Lyapunov-Krasovskii functional in delta domain. Finally, a numerical example is presented to explicitly demonstrate the effectiveness and feasibility of the proposed method.
This paper is concerned with the problem of designing a robust observer-based controller for discrete-time networked systems with limited information. An improved networked control system model is proposed and the effects of random packet dropout, time-varying delay, and quantization are considered simultaneously. Based on the obtained model, a stability criterion is developed by constructing an appropriate Lyapunov-Krasovskii functional and sufficient conditions for the existence of a dynamic quantized output feedback controller which are given in terms of linear matrix inequalities (LMIs) such that the augmented error system is stochastically stable with an performance level. An example is presented to illustrate the effectiveness of the proposed method.
This article aims to present a multiple delayed state-feedback control design for exponential H ∞ synchronization problem of a class of delayed neural networks with multiple time-varying discrete delays. On the basis of the drive–response concept and by introducing a descriptor technique and using Lyapunov–Krasovskii functional, new delay-range-dependent sufficient conditions for exponential H ∞ synchronization of the drive–response structure of neural networks are driven in terms of linear matrix inequalities (LMIs). The explicit expression of the controller gain matrices are parameterized based on the solvability conditions such that the drive system and the response system can be exponentially synchronized. A numerical example is included to illustrate the applicability of the proposed design method.
Summary The event‐triggered joint sensor fault estimation and mobile robot (MR) localization (MRL) problem (MRLP) subject to the potential fluctuations of the estimator gain are investigated. From the external sensor to the estimator, to decrease the consumption of sensor energy and cut down network bandwidth resources, an event‐triggered scheme is considered. For the sake of characterizing the phenomenon induced by the inaccurate calculation of estimator gain, an uncertainty with the bounded second moment is employed. The purpose of this study is theoretically to find a feasible and effective approach to the addressed joint estimation problem such that the estimation error (EE) covariance (EEC) meets the given performance index. First, a minimum upper bound (UB) of the EEC is derived. Subsequently, in terms of the proposed joint estimation approach and the corresponding results obtained, an algorithm to address the resilient joint sensor fault estimation and MRLP is summarized. At the end, the effectiveness of the proposed algorithm is validated through conducting a set of comparisive experiments.
This paper addresses the problem of designing quantitative feedback theory (QFT) based controllers for the vibration reduction in a structure equipped with an MR damper. In this way, the controller is designed in the frequency domain and the natural frequencies of the structure can be directly accounted for in the process. Though the QFT methodology was originally conceived of for linear time invariant systems, it can be extended to nonlinear systems. A new methodology is proposed for characterizing the nonlinear hysteretic behavior of the MR damper through the uncertainty template in the Nichols chart. The resulting controller performance is evaluated in a real-time hybrid testing experiment.
Existing controller designs for pendulous accelerometers focus on maintaining angular balance, emphasizing low-frequency measurement performance while neglecting high-frequency dynamic control accuracy. However, in high dynamic conditions, dynamic control errors directly impact accelerometer measurement performance. Through mechanical analysis, residual torque on the pendulum is identified as a major contributor to dynamic control errors in pendulous accelerometers. To enhance the dynamic performance, a torque-balance Linear Quadratic Regulator (LQR) control method is proposed, aiming to suppress dynamic control errors by implementing torque balance control. The effectiveness and stability of this control method is demonstrated through simulations and experiments. Furthermore, this study compares the advantages of torque-balance LQR closed-loop systems in dynamic compensation. The results illustrate that the proposed method significantly enhances accelerometer dynamic control performance and compensated dynamic accuracy, thereby increasing reliability and accuracy in high dynamic conditions.
1 Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway 2 College of Automation, Harbin Engineering University, Nantong Street #145, Nangang District, Harbin, China 3 School of Astronautics, Harbin Institute of Technology, P.O. Box 3015, Yikuang Street #2, Nangang District, Harbin, China 4 Laboratory of Modeling, Information & Systems, University of Picardie Jules Verne, Amiens, France
Summary In this paper, several new Razumikhin‐type theorems for impulsive stochastic functional differential equations are studied by applying stochastic analysis techniques and Razumikhin stability approach. By developing a new comparison principle for stochastic version, some novel criteria of the p th moment integral input‐to‐state stability and input‐to‐state stability are derived for the related systems. The feature of the criteria shows that time‐derivatives of the Razumikhin functions are allowed to be indefinite, even unbounded, which can loosen the constraints of the existing results. Finally, some examples are given to illustrate the usefulness and significance of the theoretical results.
The advancement of artificial intelligence algorithms has gained growing interest in identifying the fault types in rotary machines, which is a high-efficiency but not a human-like module. Hence, in order to build a human-like fault identification module that could learn knowledge from the environment, in this paper, a deep reinforcement learning framework is proposed to provide an end-to-end training mode and a human-like learning process based on an improved Double Deep Q Network. In addition, to improve the convergence properties of the Deep Reinforcement Learning algorithm, the parameters of the former layers of the convolutional neural networks are transferred from a convolutional auto-encoder under an unsupervised learning process. The experiment results show that the proposed framework could efficiently extract the fault features from raw time-domain data and have higher accuracy than other deep learning models with balanced samples and better performance with imbalanced samples.
This paper presents an alternative solution to the vibration problem in civil engineering structures. This kind of structures are characterized by the uncertainties of the parameters that describe their dynamics, such as stiffness and damping coefficients. Moreover, the actuators used to mitigate the vibrations caused by earthquakes are usually nonlinear devices with frictional or hysteretic dynamics. In order to account for the uncertainties and the nonlinearities, an adaptive backstepping controller is proposed. Semiactive control force is applied to the structure through a magnetorheological damper together with a passive frictional actuator that isolates the base of a 10-story building. The effectiveness of the controller is shown by comparing the simulation results of the cases when the structure is isolated and when it is not.
In this paper, a wavelet-based approach is presented for estimation of vehicle modal parameters. The acceleration of a colliding vehicle is measured in its center of gravity — this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of a vehicle in time domain), the frequency analysis (identification of the parameters of the crash pulse in frequency domain), and the time-frequency analysis, which comprises those techniques that study a signal in both the time and frequency domains simultaneously, using Morlet wavelet properties. The frequency components of the recorded crash pulse are identified by determining the ridge of the wavelet coefficients matrix. Having knowledge of the natural frequency of the signal, the damping factor for a given mode shape of the signal is estimated. In this work the major frequencies of the crash pulse are determined and the damping factor for the major mode shape is identified. The comparative analysis between the current method's outcome, the response of a model established previously by using different approach and the behavior of a real car is performed and reliability of the actual methods and tools is evaluated.
This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes’ measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results.
Summary This article is devoted to provide further criterion for stochastic stability analysis of semi‐Markovian jump linear systems (S‐MJLSs), in which more generic transition rates (TRs) will be studied. As is known, the time‐varying TR is one of the key issues to be considered in the analysis of S‐MJLS. Therefore, this article is to investigate general cases for the TRs that covered almost all types, especially for the type that the jumping information from one mode to another is fully unknown, which is merely investigated before. By virtue of stochastic functional theory, sufficient conditions are developed to check stochastic stability of the underlying systems via linear matrix inequalities formulation combined with a maximum optimization algorithm. Finally, a numerical example is given to verify the validity and effectiveness of the obtained results.
In this paper, we focus on the issue of adaptive H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> -control design for a class of linear parameter-varying (LPV) systems based on the Hamiltonian-Jacobi-Isaac (HJI) method. By combining the idea of polynomially parameter-dependent quadratic functions and vector projection method to derive an adaptive H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> -control, sufficient conditions with high precision are given to guarantee both robust asymptotic stability and disturbance attenuation of the LPV systems with unknown constant parameters. The applicability of the proposed design method is illustrated on a simple example.
