Narrow Results

A new topology for soft starting and speed regulation of wound rotor asynchronous machines is proposed. The feedback regulation is controlled by a microprocessor. A description of the microprocessor and its operation is presented. A theoretical analysis of the topology operation is carried out and verified by PSpice simulations. Experiments with 1.5 kW asynchronous machine are executed. Results of theoretical calculations, PSpice simulations and experiments are in good matching. The experimental investigations show that the proposed algorithm of soft starting is effective.

This paper proposes a hybrid recurrent neuro-fuzzy (RNF) architecture for rotor speed regulation of indirect field oriented controlled (IFOC) induction motor (IM) drive. This approach incorporates Takagi–Sugeno–Kang (TSK) model-based fuzzy logic (FL) laws with a four-layer artificial neural networks (ANNs) scheme. Moreover, for the proposed RNF an improved self-tuning method is developed based on the IM theory and its high performance requirements. The principal task of the tuning method is to adjust the parameters of the FL in order to minimize the square of the error between actual and reference output. The convergence/divergence of the weights is discussed and investigated by simulation.

The main drive system used for four-high mill is usually a double closed-loop DC motor speed regulating system. Generally, the speed controller and current controller are proportional-integral-derivative (PID) controllers. The parameters of these controllers are usually determined by the engineering design method and are constant in the whole process. So the controllers can give good control effect in the rated operating condition. Once disturbance occurs, the control effects are often just passable. In this paper, fuzzy logic is used to adjust the parameters of the speed PID controller to improve the disturbance rejection ability. Simulation results show that the fuzzy tuning PID controller can give better control effect than the regular designed PID control.

An ultrasonic motor speed control scheme is presented in this paper based on neural networks and iterative controller. Suitable ranges of the adaptive learning rates of neural network controller are presented through the theoretical analysis on the proposed model, which could guarantee its stability. The convergence of iterative controller is also discussed. Numerical results show that the control scheme is effective for various kinds of reference speeds of ultrasonic motors. Comparisons with the existing method show that the precision of control could be increased using the proposed method. Simulations also show that the proposed scheme is fairly robust against random disturbance to the control variables.

This study presents a novel neuro-fuzzy (NF)-based auto-tuning proportional integral controller (NFATPI) for accurate speed control, and to ensure optimal drive performances of the indirect field controlled induction motor drive, under system disturbances and uncertainties. The training mechanism of the proposed NF have been developed and illustrated through mathematical formulations. Then, the NF parameters have been updated on-line using a suitable training algorithm. The learning rates of the NF are derived on the basis of the discrete Lyapunov function is also illustrated, in order to confirm the stability and the performance of prediction of the proposed NFATPI. The simulation results confirm the effectiveness of the strategy NFATPI as a robust controller for high performance industrial motor drive systems.

This paper proposes Interval type-2 Fuzzy sliding mode controller based on Backstepping (IT2FBSMC), to control the speed of a dual star induction machine (DSIM), in order to get a robust performance machine. An appropriate control strategy based on the coupling of three methods (Backstepping, sliding mode and type-2 Fuzzy controller) is used to build a robust controller used to approximate the discontinuous control eliminating the chattering phenomenon and guaranteeing the stability of the machine. Moreover, it forces the rotor angular speed to follow a desired reference signal. The simulation results obtained using Matlab/Simulink behavior are presented and discussed. The obtained results show that the controller can greatly alleviate the chattering effect and enhance the robustness of control systems with high accuracy.

In terms of the speed control issues of proportional pump controlled motor system, this paper firstly analyzes the composition and working principle of the system, establishes the mathematical model of the system, and obtains the system characteristics. Then according to the characteristics of the system, this paper designs a new type of fuzzy PID structure, determines the fuzzy linguistic variables and membership functions, and formulates the fuzzy rules, determines the method of fuzzy reasoning and clarification. Finally, this paper carries out the simulation of the system in the MATLAB/Simulink environment, and analyzes system response curves of PID control and fuzzy PID control. The simulation results show that fuzzy PID control is better than conventional PID control on motor speed control.

The path following technique can improve the repeatability and objectivity of the vehicle performance test. In order to improve the path following algorithm application, a new path following algorithm based on a three degree of freedom vehicle model was proposed, considering nonlinear characteristics of side slip angle and lateral force. The effectiveness of the path following algorithm is verified by matlab simulation.

In general, when rolling on a flat surface, vehicles move smoothly as if they collect surface profiles. However, legged robots tend to swing vertically because of the front to back kicking of the legs. Therefore, walking on feet that are jointed to a wheel rim requires a decrease in vertical swing and speed unevenness. We propose a computational method to determine the angular variables of feet that are synchronously driven with the wheel rotations. In addition, we propose a structural model of a four-wheeled skid-steering vehicle (4WSSV) with multiple feet on each wheel. Next, we explain the difficulty of achieving a uniform vehicle speed when the wheels rotate with a constant velocity. To cope with this problem, we consider a control method that minimizes the speed unevenness. We derive an appropriate dynamic wheel rotation range for the case with feet landings. We simulate a walk based on a model for a flat surface with a slope. Finally, the approach is verified with walk demonstrations demonstrating that the vehicle behaves as designed, i.e., without a vertical swing and a close to even speed.

To obtain better speed control performance of smart car, the mathematical model of smart car is built, a velocity estimation method based on complementary filter is used to reduce the noise from velocity measurement based on photoelectric encoder, a Fuzzy-PID controller to control speed of smart car by using the estimation result as the feedback is designed, and comparisons of control performance with conventional PID controller are made in this paper. The experimental results show that the Fuzzy-PID controller for speed control has better control performance than conventional PID.