This article investigates a fractional-order coupled Hindmarsh-Rose neural networks model. Firstly, the existence and stability of an equilibrium point in the system are verified. Then, the periodic bifurcation behavi...
This article investigates a fractional-order coupled Hindmarsh-Rose neural networks model. Firstly, the existence and stability of an equilibrium point in the system are verified. Then, the periodic bifurcation behavior of the system on a two-parameter plane is studied, and numerical simulations show the existence of both non -chaotic and chaotic plus periodic bifurcation behavior on the two-parameter plane. Finally, a feedback controller was designed to stabilize the bifurcation point of the delayed system and increase the stable range of the system.
Input-output feedback linearization is a nonlinear control method that relies on a precise dynamical model. Combining Q -learning techniques, an input-output feedback linearization correction framework is presented to...
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Input-output feedback linearization is a nonlinear control method that relies on a precise dynamical model. Combining Q -learning techniques, an input-output feedback linearization correction framework is presented to accomplish model-free feedback linearization of affine nonlinear systems in order to tackle the problem caused by the unknown dynamics model. This framework formulates a model reference tracking control problem that guides the input-output relationship of the nonlinear system into a linear relationship. Due to the two Lie derivative terms present in the feedback linearized controller, the controller is designed as a dual network structure. To overcome the issue of coupling in the dual-network controller, a model-free Q -learning method is presented to solve the unknown controller network weights. The proposed method is experimentally validated on a single-link flexible joint manipulator system, and the resultant linearized system exhibits dynamics similar to the desired linear system in a new tracking task, proving the effectiveness of the proposed method.
This paper presents an improved stability criterion and controller design scheme condition for a networked control system under denial of service (DoS) attack. Firstly, the DoS attack interval is divided into attack i...
This paper presents an improved stability criterion and controller design scheme condition for a networked control system under denial of service (DoS) attack. Firstly, the DoS attack interval is divided into attack interval and no attack interval, therefore, a switching-like event-triggered control can be established to reduce the waste of network resources and improve network efficiency. Then, the studied system is transformed into a time-delay system, and an improved stability criterion and controller design method are established by using Lyapunov-Krasovskii functional (LKF). Finally, the effectiveness of the proposed method is verified by a simulation example.
In this paper, the stability of Amplidyne Electrical systems (AESs) with a time-varying delay is studied. Firstly, the model of AESs with a time-varying delay is established. Secondly, an augmented Lyapunov-Krasovskii...
In this paper, the stability of Amplidyne Electrical systems (AESs) with a time-varying delay is studied. Firstly, the model of AESs with a time-varying delay is established. Secondly, an augmented Lyapunov-Krasovskii functional (LKF) is constructed. Then, a less conservative delay-dependent stability criterion for AESs with a time-varying delay is obtained by utilizing the generalized reciprocally convex combination and an advanced negative-determination quadratic function lemma. Finally, the superiority and effectiveness of the proposed criterion is verified by a numerical example.
This paper is concerned with $H_{\infty}$ performance state estimation of static neural networks with a time-varying delay. First, a PI estimator with exponential term is used to estimate neuron states based on outp...
This paper is concerned with $H_{\infty}$ performance state estimation of static neural networks with a time-varying delay. First, a PI estimator with exponential term is used to estimate neuron states based on output measurement. Second, an augmented Lyapunov-Krasovskii functional (LKF) containing delay-product-type non-integral terms and single integral terms is constructed by introducing negative definite terms. After that, a criterion with less conservatism is derived based on extended reciprocally convex matrix inequality. Finally, a numerical example is provided to reveal the effectiveness of the proposed approach.
A new Gaussian approximate (GA) filter for nonlinear systems with one-step randomly delayed measurement and correlated noise is proposed in this paper. Firstly, a general framework of Gaussian filter is designed under...
A new Gaussian approximate (GA) filter for nonlinear systems with one-step randomly delayed measurement and correlated noise is proposed in this paper. Firstly, a general framework of Gaussian filter is designed under Gaussian assumption on the conditional density. Then, the implementation of Gaussian filter is transformed into the approximation of the Gaussian weighted integral in the proposed frame. Secondly, a new cubature Kalman filtering(CKF)algorithm is developed on the basis of the spherical-radial cubature rule. The efficiency and superiority of the proposed method are illustrated in the numerical examples.
In drilling processes, non-stationary phases corresponding to shifts between operating conditions and changes in downhole formations typically lead to false alarms. Extracting these frequent event patterns is critical...
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In drilling processes, non-stationary phases corresponding to shifts between operating conditions and changes in downhole formations typically lead to false alarms. Extracting these frequent event patterns is critical to build drilling process monitoring and fault diagnosis models. This study aims to extract the frequent event patterns associated with non-stationary phases in drilling time series. In this way, diversified information related to signal changes under normal conditions can be obtained, which is beneficial for suppressing false alarms and improving fault detection performance. The main contributions of this study are twofold: 1) a non-stationary phase detection method is proposed to extract drilling frequent event patterns based on t -distributed stochastic neighbor embedding and relative unconstrained least-squares importance fitting; 2) an event sequence generation method is proposed to express drilling frequent event patterns with a group of symbols. The effectiveness of the proposed method is demonstrated by data from a real drilling project.
In this paper, the master-slave synchronization issue of chaotic Lur’ e systems with time-varying-delay feedback control is investigated. Firstly, the synchronization problem of chaotic system is transformed into the...
In this paper, the master-slave synchronization issue of chaotic Lur’ e systems with time-varying-delay feedback control is investigated. Firstly, the synchronization problem of chaotic system is transformed into the stability problem of chaotic synchronization error system, which is studied based on Lyapunov-Krasovskii functional (LKF) method. Secondly, a novel augmented LKF with more cross terms that related to time-varying delay is proposed. Based on the application of the relaxation integral inequality and the reciprocally convex matrix inequality, an improved synchronization criterion is derived by using the cubic function negative-determination lemma. Finally, a numerical simulation example demonstrates the effectiveness and advantages of the proposed methods.
To ensure reliable localization for Unmanned Aerial Vehicles(UAVs) in the presence of uncertain speed of the Unmanned Ground Vehicle (UGV), this study examines the relative localization problem of UAV-UGV using distan...
To ensure reliable localization for Unmanned Aerial Vehicles(UAVs) in the presence of uncertain speed of the Unmanned Ground Vehicle (UGV), this study examines the relative localization problem of UAV-UGV using distance and bearing measurements. A Correlation of Bearing and Distance-based Relative Localization (CBDRL) algorithm is proposed in this paper under this scenario. The estimation of altitude, distance, and angle are simplified into a representation of the relative positioning between the UAV and UGV. The relative height difference is measured using the barometer in the algorithm. To determine the relative distance, Time of Arrival (TOA) ranging and Ultra Wide Band (UWB) communication are utilized. The relative direction measurement is then determined using the correlations of bearing and distance. We integrate these observations with height, direction, and distance data in an Extended Kalman Filter(EKF) to provide accurate and reliable relative position estimates that allow the UAV to track the target. The simulation results indicate that the CBDRL method developed in this study is superior to previous relative localization algorithms that rely on multi-sensor fusion, and can significantly enhance the accuracy of UAV positioning provided that range and angle measurements are precise enough.
Grid-forming inverter is widely used in grid-connected systems of distributed generation because of its frequency and voltage support capacity and good stability in microgrid,but its large inertia will affect the dyna...
Grid-forming inverter is widely used in grid-connected systems of distributed generation because of its frequency and voltage support capacity and good stability in microgrid,but its large inertia will affect the dynamic response speed of grid-forming *** order to solve this problem,this paper introduces the loop that affects the dynamic response of grid-forming inverter,and carries out small signal modeling for active loop,analyzes the dynamic performance indicators and determinants of typical second-order ***,a method of adding power feedforward coefficient to the forward channel of the power loop is designed,and the response speed of the system with or without feedforward coefficient under the unit step response is ***,the simulation results show that adding the power feedforward coefficient can improve the response speed of the grid-forming inverter during startup and power switching,then achieves the effect of fast control.
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