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Taking the piezoelectric beam as research object, filtered-U least mean square (FULMS) control algorithm for feed-forward adaptive control is analyzed and compared with filtered-x least mean square (FXLMS) feed-forward control algorithm, which can solve the problem that the vibration feedback may affect the measuring of the reference signal in FXLMS. By introducing FXLMS and FULMS control algorithm,...
Microturbine generator system is one of the most promising distributed generation systems because it is small, efficient and mobile. When it is running, the high-frequency alternating current of permanent magnet synchronous generator generating must be rectified and inverted into 50Hz AC to meet the user requirements. Normally, the diode rectifier is used. When we need to regulate voltage, the DC/DC...
A neural network (NN)-based backstepping adaptive control is proposed for the stabilized platform system of shipborne weapons (SPOSW) with uncertain nonlinear friction torque and load disturbance. First, with the using of NN approximator, an equivalent model is developed. Where the NN is used to estimate the uncertain nonlinear friction torque. Then, based on the equivalent model, address the problem...
In this paper, the state-space disturbance observer was successfully applied to servo motors to estimate and compensate for load variation. Furthermore, an auto-tuning procedure was developed accordingly to identify the varied parameters for state-space disturbance observer of the motor. Then, a real-time IP position controller based on identified parameters is designed by neural network for permanent...
Wireless multimedia sensor networks (WMSNs) are a new and emerging type of wireless sensor networks (WSNs), which enable applications of multimedia captured through special sensors equipped with cameras or microphones etc. However, WMSNs face the challenges of transport reliability and energy consumption. In this paper, we propose an adaptive error control mechanism based on the importance of link-layer...
In the practical application of Vehicle Plate Recognition, it is greatly effective on Vehicle Plate Recognition for the variety of exterior illumination. which is the most important problems to be taken into account, for realizing excellent Vehicle Plate Recognition system. The paper brings forward an Acquiring Image Adaptive Control System (AIACS) based on locomotor Vehicle through long-term research...
A composite controller is designed based on singular perturbation model of two manipulators handling a flexible payload with external disturbances and parameters uncertainties, where an adaptive sliding mode controller is presented for the slow subsystem. The control algorithm can realize trajectory tracking control in the large range and update some values of parameters effectively, comparing with...
This paper considers the generalized synchronization problems of two different hyperchaotic systems with unknown parameters. By denoting the synchronization error signals as the difference between the state variables of the drive system and the state variables of the response system, the hyperchaotic synchronization problem is transformed into the stabilization control problem of the origin of the...
In this paper, the stabilization problems of a class of new hyperchaotic systems with fully unknown parameters are concerned. Based on the adaptive control idea, two novel adaptive state feedback controllers are designed to implement the asymptotic stabilization of this kind of new hyperchaotic system by choosing appropriate controller structure and parametric updating law, respectively. The effectiveness...
This work is devoted to present a control application in an industrial process of iron pellet cooking in an important mining company in Brazil. This work uses an adaptive control in order to improve the performance of the conventional controller already installed in the plant. The main strategy approached here is known Multi-Network-Feedback-Error-Learning (MNFEL), it uses multiple neural networks...
The paper presents a novel adaptive neural-network based nonlinear model predictive control (NMPC) methodology for hybrid systems with mixed inputs. For this purpose an online self-organizing growing and pruning redial basis function (GAP-RBF) neural network is employed to identify the hybrid system using the unscented Kalman filter (UKF) learning algorithm. A receding horizon adaptive NMPC is then...
On the basis of results of previous studies, this paper overviews several kinds of typical artificial muscles' structural principle, the technological study condition and application status in main fields, and classifies artificial muscles. This paper mainly summarizes domestic and foreign scholars' research results on the control technology of artificial muscles, including neural network control,...
The inherent torque ripple of brushless DC motor limited its scope of application. In this paper, the state space model of system was derived from the mathematical model of motor to generate the desired current. An optimal state feedback controller using the Kalman filter state estimation technique was established aimed at ripple free torque control. An active disturbance rejection control algorithm...
According to the nonlinear and parameter time-varying characteristics of vehicle stability control, a sliding control algorithm is proposed based on radial base function (RBF) neural network. The algorithm not only can reduce the chattering caused by the conventional sliding mode, but also improve the robust of the adaptive neural network control. The simulation results show the algorithm ensures...
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