Design and Implementation of Stator Resistance Identifier Based on Fuzzy Control

An induction machine operated with a direct self controller (DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic is used in conjunction with direct self control to minimize these problems. A fuzzy logic controller chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determined by observing the vector diagram of flux and currents. The operation of the direct self controller becomes difficult at low speeds due to the effect of change in stator resistance on the flux measurements. To improve the system performance at low speeds a fuzzy resistance estimator is proposed to eliminate the error due to the change in stator resistance. At constant flux and torque commands any change in stator resistance of the induction machines causes an error in stator current. This error is utilized by the fuzzy resistance estimator to correct the stator resistance used by the controller to match the machine resistance. Both a fuzzy controller and fuzzy resistance estimator are simulated for a 3 HP induction motor. The simulation results demonstrate a good performance. >

Matrix converter induction motor drive system operated with a direct torque control (DTC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic is used in conjunction with direct torque control to minimize these problems. A fuzzy logic controller chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determined by observing the vector diagram of flux and currents. The operation of the direct torque controller becomes difficult at low speeds due to the effect of change in stator resistance on the flux measurements. To improve the system performance at low speeds a fuzzy resistance estimator is proposed to eliminate the error due to the change in stator resistance. At constant flux and torque commands any change in stator resistance of the induction machines causes an error in stator current. This error is utilized by the fuzzy resistance estimator to correct the stator resistance used by the controller to match the machine resistance. Both fuzzy controller and fuzzy resistance estimator are implemented using DSP TMS320C6711 for a 3 hp induction motor drive system. Results demonstrate enhanced performance.

As to the ripple problem of the direct torque control system of permanent magnet synchronous motor, this paper present a new method based on the fuzzy logic control. The new method replaces the traditional hysteresis torque controller by a fuzzy logic controller to realize the low ripple effect of the torque and the flux linkage. Also this paper modeling and simulate the new control system using the FIS toolbox provided by the Matlab/Simulink software, and the simulation results shows that the fuzzy control method is far more better than the traditional direct torque control system.

How to correctly select the voltage space vector in a direct torque control system is one of the key techniques to get over the shortcoming of the DTC system at low speed. We introduce the intelligent optimization algorithm to the fuzzy neural network controller adopted by the direct torque control system. Adopting the immune genetic algorithm to optimize the weights and grade of the membership function of the fuzzy neural network can get over the defects that are easy to get in the local minima of BP. It can infer with the stator voltage vector reasonably. It has an easy control system, a dynamic torque response, and a fast rotation speed. It improves the low speed performances of the direct torque system.

This paper presents a new solution, which can completely remove the DC offset and compensate the steady-state error for voltage model flux estimation in an induction motor (IM) direct torque control (DTC) system. The voltage model flux estimator has been paid more attention for its clear concept and simple signal processing, however, the integration drift associated with the inherent initial value error and DC offset input, especially in low speed region, can not be completely eliminated by the conventional low-pass-filter (LPF), in addition, LPF also brings steady-state amplitude and phase errors. Based on Bode plots analysis of some existing integrators, a new integrator with a first-order LPF and a high-pass-filter (HPF) in series is proposed to replace the pure integrator. The filters have adaptive cutoff frequency so as to suit various conditions. With the time phasor method, an error compensation formula is derived, which makes it simpler and easier for the new integrator to be applied to the digital control system. The new integrator with error compensation not only completely eliminates the integration drift, but also realizes errorless flux estimation in steady state. Both the simulation and experimental results on a prototype of 4kW IM DTC system show that the performance of the system especially in low speed region has been improved remarkably. This also verifies the effectiveness of the new integrator.

Induction motors have some inherent characteristics such as multivariate, parameter indeterminacy, strong coupling and non-linearity. These bring about a lot of trouble to the induction motor drive system. Considering the problems of AC speed regulation cause by the motor's inherent characteristics, a fuzzy control strategy based on the RBF neural network was presented. It was designed to make full use of the features of RBF neural network and fuzzy control. A contrastive research was made between the conventional direct torque control system and the fuzzy control system based on RBF. Simulation results show that the fuzzy control strategy based on RBF for direct torque control System has strong robustness, quick response, low overshot.

For the disadvantage of the low flux's observational accuracy of induction motor direct torque control system when it runs in a low velocity, the full order flux observer is used to achieve the stator flux observation.Based on the analysis of four full order flux observer pole placement methods,The impact on observational accuracy and convergence rate was researched with different parameters of the Gain Matrix in the single degree of freedom pole placement method.The simulation results show that to ensure the stability of the system,the impacts on the flux observation were Effectively inhibited when Motor's stator and rotor resistance parameters change through increasing parameter of the Gain Matrix,and the flux observer's robustness was improved.

The traditional direct torque control (DTC) of asynchronous motor has the disadvantages of the flux linkage, large torque ripple and instable switching frequency. To solve the above problems, a new scheme of modulating direct torque control system by adaptive fuzzy PI was put forward. According to the principle of fuzzy control, the regulator can perform the real-time optimization of PI parameters, realizing the good dynamic and static performance of system. In order to verify the feasibility and effectiveness of this scheme, this paper builds a simulation model of direct torque control system based on adaptive fuzzy PI control regulator by using MATLAB and Simulink. The simulation results show that compared with the traditional direct torque control system, the direct torque control system modulated by adaptive fuzzy PI has the merits of obvious reducing in flux and torque ripple, significant improvement on control performance.

Direct Torque controlled induction motor (DTC-IM) drives have been used widely over last few decades. DTC-IM drives use the stator resistance of the motor for stator flux estimation which directly depends on the stator resistance of IM. Proper estimation of the stator resistance is very important because stator resistance varies due to the increase in temperature of the machine during operation. An online estimation of the stator resistance of the induction motor using model reference adaptive system (MRAS) and fuzzy logic for the direct torque control drive is modeled and verified in this paper. The error between the actual state variable of the machine and the estimated value of the reference model and rate of change of this error is used as input by the fuzzy estimator which gives the change in resistance value as output. From simulation it has been proved that the estimator can track the stator resistance value within 70 ms when a step change of stator resistance has been applied. The efficacy of the estimator is investigated in simulation by varying the stator resistance from the nominal value which has been done in MATLAB/SIMULINK.

In this paper, the torque ripple problem of six-phase asymmetrical brushless DC motor (BLDCM) is studied. First, the basic structure of BLDCM is introduced, and the operation principle of six-phase asymmetrical BLDCM that is studied in the thesis is expounded. Then, the principle of direct torque control (DTC) system of BLDCM is also discussed, and the improved system is proposed, including using the torque hysteresis loop and opening current hysteresis loop, and choosing the improved voltage vector to make the PWM-ON-PWM modulation. Finally, the DTC system simulation model is built, and the system is also tested by the experiment. According to the results of experiment and simulation, the DTC system designed in this thesis can control the six-phase asymmetrical BLDCM stably and reliably, and the problem of high frequency and torque ripple is solved well.

In a direct torque control system, the stator resistance of induction motors varies with winding temperature. The variation severely influences system performance at low speed. The paper presents a stator resistance on-line estimator based on the fuzzy-neural network. The experimental result and simulation shows that the estimator can accurately measure stator resistance and efficiently improve system performance at low speed.

The traditional direct torque control system of permanent magnet synchronous motor has many problems, such as large torque ripple and variable switching frequency. In order to improve the dynamic and static performance of the control system, a new torque control idea and speed sensorless control scheme are proposed in this paper. First, by deriving the equation of torque change rate, an improved torque controller is designed to replace the torque hysteresis controller of the traditional direct torque control. The improved direct torque control strategy can significantly reduce the torque ripple and keep the switching frequency constant. Then, based on the improved direct torque control and considering the sensitivity of the stator resistance to temperature change, a speed estimator based on the model reference adaptive method is designed. This method realizes the stator resistance on-line identification and further improves the control precision of the system. The performance of the traditional direct torque control and the improved direct torque control are compared by simulation and experiment under different operating conditions. The simulation and experimental results are presented to support the validity and effectiveness of the proposed method.

To reduce traditional direct torque control (DTC) system low speed control precision and the large torque ripple in low speed, a fuzzy control system of DTC was proposed. On the basis of conventional PI regulator, a fuzzy speed PI regulator was designed according to speed error and its rate of change, which could adjust the proportional coefficient k <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf> and integral coefficient k <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</inf> dynamically to adapt the system to the speed variations, and advanced the self-adaptation of speed. In voltage vector fuzzy controller model, the stator flux angle, the stator flux error, and the torque error are reasonably fuzzified into several fuzzy subsets to optimize selection of the voltage vector and decrease the torque ripple. The experimental results show that the proposed fuzzy control system not only can ensure swift speed response, small overshooting, and high steady speed precision, but also can effectively decrease torque ripple in low speed. Additionally, the system improves the observation precision of the stator flux and enhances the robustness of the whole system.

To improve the low-speed dynamic performance of induction motor in direct torque control (DTC), a novel method of stator resistance identification based on wavelet network (WN) is presented and the determination of wavelet network structure is discussed. The inputs of the WN are the current error and the change in the current error and the output of the WN is the stator resistance error. The improved least squares algorithm (LSA) is used to fulfill the network structure and parameter identification. By the use of wavelet transform that accurately localizes the characteristics of a signal both in the time and frequency domains, the occurring instants of the stator resistance change can be identified by the multi-scale representation of the signal. Once the instants are detected, the accurate stator flux vector and electromagnetic torque are acquired by the parameter estimator, which makes the DTC applicable in the low region, optimizing the inverter control strategy. By detailed comparison between the wavelet and the typical backward-propagation (BP) neural network, the simulation results show that the proposed method can efficiently reduce the torque ripple and current ripple, superior to the BP neural network.

With the development of power semiconductor and digital processor technology, the design and application of three-level inverter in electric multiple units(EMU) are more and more extensive. The traditional space vector pulse width modulation (SVPWM) method for the three-level inverter requires estimating the sectors and calculating a lot of trigonometric functions. As a result, the calculation of SVPWM method for microprocessor is very complicated and large. To reduce the calculation working of the PWM module, a SVPWM method based on 60° coordinate system for three-level inverter is focused and discussed in this paper. Finally, a vector control system of asynchronous motor based on DSP was built up to verify the feasibility of this SVPWM method in this paper. Experimental results show that the adopted method can omit a lot of trigonometric functions, and reduce the calculating burden of the control system.