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This paper presents a position tracking control method for a three degree-of-freedom permanent magnet spherical actuator (PMSA). The control method is designed based on a dynamic model of the PMSA with uncertainties including modelling errors and external disturbance. Sliding-mode surface are adopted to restrain and eliminate the effect of external disturbances. To compensate modelling errors, an...
This paper describes the causes of cogging torque in Permanent Magnet synchronous Motor. Establishes a motor model by ANSOFT software, uses Finite Element Method to quantitative analysis and comparative peak cogging torque and torque with notches at different locations, and different number of auxiliary slot. The conclusion is that notch reasonable can reduce the cogging torque of permanent magnet...
A novel robust sliding-mode controller using neural networks (NNs) is given for trajectory tracking control of permanent magnet spherical actuator (PMSA) with external disturbance and system model errors. The controller is established including sliding-mode scheme and the neural networks. The radial basis function (RBF) neural networks are chosen to approximate the unknown model and uncertainty, as...
The inevitable temperature raise leads to the demagnetization of permanent magnet synchronous motor (PMSM), that is undesirable in the application of electrical vehicle. This paper presents a nonlinear demagnetization model taking into account temperature with the Wiener structure and neural network characteristics. The remanence and intrinsic coercivity are chosen as intermediate variables, thus...
In order to combine the model-based control algorithm with the physical model, this paper proposed a co-simulation system of permanent magnetic spherical motor (PMSM). Firstly, a new track planning was simulated in ADAMS for the convenience of trajectory tracking. Secondly, a new co-simulation interface was presented, thus the model-based control algorithm can be used to control the physical model...
Signal filtering approaches are always used to attenuate noise and enhance useful signal in bearing fault diagnosis. Stochastic resonance (SR) is a nonlinear filter that can utilize noise to enhance weak periodic signal. This study proposes an adaptive SR method which can automatically enhance the bearing fault characteristic frequency (FCF). First, a second-order SR filter is utilized to purify the...
This paper presents a novel tracking controller for a three degrees-of-freedom permanent magnet spherical actuator (PMSA). The controller is designed on the basis of the establishment of dynamics model under uncertainties. The major construction of the controller lies in the use of the matrix regressor to isolate unknown parameters from the PMSA. Moreover, sliding-mode control and robust control are...
As the shortcomings of multi-rigid-body mathematical modeling for permanent magnetic spherical motor (PMSM), such as the complexities vary greatly and even lead to considerable deviations from the actual system. A novel physical modeling method and dynamic simulation based on computer software are proposed in this paper. Firstly, the physical model of PMSM rotor was set up in Solidworks. And then,...
In the AC drive system, the control performance is highly dependent on the accuracy of the electromagnetic parameters. In order to reduce the influences of the parameter variations, a new scheme for on-line rotor time-constant and magnetizing inductance estimation in induction motors is proposed. The algorithm is obtained by interlacing a Bi-Loop recursive least squares algorithm with forgetting factors...
Due to the nonlinear, strong coupling dynamic system of a direct-drive permanent magnet spherical motor (PMSM), an adaptive fuzzy decoupling controller is developed in this paper. The proposed scheme effectively combines the design techniques of adaptive fuzzy control and robust control in order to achieve dynamic decoupling and compensate for approximation errors. Moreover, a regularized matrix inverse...
This paper presents an intelligent tracking control method for a three degrees-of-freedom permanent magnet spherical motor (PMSM). The control method is designed on the basis of the establishment of dynamics model for spherical motor according to Cardan angles. By the use of backstepping design, the nonlinear system of PSMS is divided to several subsystems with less order than that of original system...
The rotor orientation detection of spherical motor is crucial to the closed-loop control. The paper presents the method for measuring rotor orientation based on machine vision. The pattern code generation, deriving method and pattern processing algorithm are introduced. With the model built in OpenGL, measurement errors of three degrees of freedom (DOF) are derived. Resolution and accuracy of the...
In this paper, the problem of continuous tracking control for permanent magnet spherical motor (PMSM) is investigated. Based on the nonlinear rotor dynamic model, the adaptive output feedback control is employed. Among them, the unknown nonlinear model can be directly approximately by fuzzy logic system, while the robust items are used to compensate the estimated errors. Moreover, with the aid of...
The paper has presented a new structure of three-of-degree (3-DOF) permanent magnetic spherical motor (PMSM) including four layers of cylindrical rotor poles and two layers of coils without ferromagnetic core. The radial magnetic field influenced by magnetization direction and different structure of rotor poles are analyzed based on analytic method by toroidal function. With the torque model the effects...
Considering the influence of the unknown uncertainties, a robust adaptive neural network control approach is employed to the controller design for permanent magnet spherical motor (PMSM) under the continuous tracking mode. The unknown nonlinear model can be approximately learning by RBF neural network (RBFNN) system. With the aid of robust items, the external disturbance problem and the approximation...
To solve the trajectory tracking control problem for rigid-link robot manipulators including actuator dynamics, a novel neural network (NN)-based adaptive algorithm is discussed. In the proposed control algorithm, radial basis function neural network (RBFNN) is adopted to approximate the nonlinear dynamics of the robot manipulators' electromechanical system. Moreover, the key features are that, firstly,...
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