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This paper considers the global adaptive stabilization via output-feedback for a class of uncertain planar nonlinear systems. Different from the existing related literature, the systems under investigation are subjected to unknown control directions, and simultaneously allow linear unmeasured states dependent growth. To solve the problem, an adaptive output-feedback scheme is proposed, not only to...
In order to meet the needs of smart distribution grid evaluation in different regions and different information integrity systems, this paper presents a comprehensive evaluation system (CES) based on analytic hierarchy process (AHP) and adaptive correction method. First, a hierarchical frame structure of the CES is put forward. Then, a detailed design of the comprehensive evaluation index system (CEIS)...
This paper investigates the consensus problem of multiple uncertain Lagrangian systems with switching topologies. Due to the discontinuity resulted from switching topologies, achieving consensus in the context of uncertain Lagrangian systems is challenging. We propose a new adaptive controller based on dynamic feedback to resolve this problem and additionally propose a new analysis tool for rigorously...
In this paper, an adaptive integrated guidance and control(IGC) law is proposed for the missile intercepting the maneuvering target with impact angle constraint. Considering the parameter uncertainties, a new IGC model is established. Subsequently, the dynamic surface control and adaptive technique are combined to design the adaptive IGC law. Finally, the simulation results are provided to verify...
Islanding detection is an essential function of distributed grid-connected power generation systems, and an islanding detection method based on adaptive reactive power disturbance is proposed in this article. Importing the reactive power disturbance can make RLC loads generate the frequency shift when the power grid is disconnected for fault and the islanding will be detected. The reactive power disturbance...
Conventional sliding mode control (SMC) is so-called robust to the system uncertainty and the external disturbance, however, it requires the knowledge about the upper bound of uncertainties and external disturbances. In the practical system, uncertainties and external disturbances are often unknown. A adaptive backstepping sliding mode controller (ABSMC) is proposed to deal with the uncertainty in...
This note deal with H∞ adaptive event-triggered control on a class of networked control systems with randomly occurring nonlinearities. By employing an adaptive controller, the system is against randomly occurring nonlinearities effectively. Based on a Lyapunov functional, the stability criteria are given. Finally, a numerical example is given to illustrate the effectiveness of the obtained results.
This paper develops an adaptive fault tolerant controller, based on a novel K-filters, to address tracking control problem of a class of nonlinear systems. With the help of fuzzy logic systems, a novel K-filters is proposed to estimate the unmeasured system states. It is proved that the developed controller can guarantee all the signals are bounded and the output tracks a given signal to a neighborhood,...
In this paper, the problem of adaptive tracking control is developed for a class of nonstrict-feedback switched nonlinear constrained systems. Backstepping technology combined with fuzzy logic systems (FLSs) are employed to estimate the unknown nonlinear functions of the switched constrained systems. By using the dynamic surface control (DSC) technology, the “explosion of complexity” can be reduced...
In view of the limitation of the traditional PID controller in the processing of nonlinear time-varying systems, a neuron adaptive PID control algorithm is proposed. Based on the traditional PMSM speed control, the neuron adaptive PID control method is adopted, using the Hebb learning algorithm, the error square is used as the performance index to adjust the parameters online in order to realize the...
The design of adaptive sliding mode control is studied for a class of Markov jump systems(MJSs) with transition rate uncertainties and the partial failures of the actuators. Firstly, the mathematical model of MJSs with the uncertainty of the transition rate and the partial failure of the actuator is established. Secondly, the sliding surface is proposed by combining linear matrix inequality (LMI)...
This paper proposes a neural network controller to achieve the tracking of a robot manipulator with a highly nonlinear structure, and presents a online adaptive control algorithm. The controller based on RBF neural network approximation is designed, and its stability and convergence is analyzed under four different circumstances. By minimizing the system error and considering the characteristic of...
In this paper, we study the fault tolerant control problem of actuator fault by indirect adaptive method. There are normal conditions, the failure of executor partial, interruption, and non-parametric failures of actuator form. We assume that the efficiency factor of actuator is unknown, furthermore, the external disturbances and the boundary of time-varying card failures are also unknown. In addition,...
This work studies the robust stabilization problem of non-triangular delayed nonlinear system. The considered system involves the uncertain dynamics, unknown control coefficient and time delay. By employing a novel Lyapunov-Krasovskii functional and using the backstepping method, we raise a robust controller to guarantee the states of the system bounded. An example is given to verify the validity...
With the emergence of large-scale and high-performance modern production system, how to effectively improve the safety performance of the control system has become an urgent problem to be solved.[1] Fault detection and diagnosis as the main means to improve the reliability of the control system have been widely valued. Fault diagnosis is a technique to use the information in the system to detect the...
In industrial control, there are a large number of nonlinear strongly coupled controlled objects with external disturbance. It is difficult to control the object of such a good effect with classical control theory. Aiming at the problem of disturbance rejection, decoupling and tracking control of this kind of system, PIDNN controller is adopted in this paper, and its weight correction algorithm is...
A novel actuator fault reconstruction scheme based on neural network and adaptive sliding mode observer is presented for a class of nonlinear systems with uncertainty. To improve the accuracy of actuator fault reconstruction, the radial basis function neural network is applied to approximate the uncertainty on line. An adaptive algorithm is designed to modify the gain of the controller by considering...
A robust nonlinear control strategy, based on back-stepping, is presented to adjust the dc-link voltage from the PV system and the current which is used to control the amount of injected active or reactive power into the grid. The control system is projected using an adaptive backstepping technique taking the unknown parameters into consideration. But many times, the problems of differential expansion...
The traditional target detection and identification algorithm is difficult to adapt to the massive data. And the expression of the method it relies on is designed by means of manual, which is not only very time-consuming, but also very dependence for professional knowledge and data itself. Aiming at the problem of pedestrian detection in complex environment, a pedestrian detection algorithm based...
This work presents a path following controller for single Unmanned Surface Vessels (USV) in formation control. Firstly, the USV mathematical model under unknown dynamic sea conditions will be analyzed. And then an adaptive robust controller is designed based on RBF neural network. Finally, the controller stability and robustness with unmodeled dynamics and unknown model parameters perturbation in...
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