Research on Flux Observer Based on Wavelet Neural Network Adjusted by Antcolony Optimization

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.

The direct torque control (DTC) system, which is based on induction machine drive is a developed and simple control method. It allows high dynamic performance with very simple hysteresis control scheme; However, its disadvantages are high current, torque, and flux ripple. In this paper, DTC of induction machine drive has been improved by using the applications of artificial intelligence (AI) approaches to reduce the current, torque, and flux ripples and also get better performance of the machines. At the conclusion of this study, the outcomes of traditional DTC and artificial intelligent methods are compared. By the program MATLAB/SIMULINK, the modeling and simulation results of the DTC system for induction machine (IM) have been proposed.

Direct torque control (DTC) systems for open-end winding permanent magnet synchronous motors (OEW-PMSM) with common DC bus generate zero sequence currents (ZSC) and large torque ripple, resulting in increased system loss and poor operating characteristics. In this paper, a DTC based on five level torque hysteresis (FLTH) is proposed to improve the system performance. Firstly, an online calculation and selection strategy based on switch table is designed to suppress ZSC. By analyzing the composition of zero sequence voltage and using the double vector method to suppress it, the ZSC can totally be suppressed in theory, without affecting the system performance. On this basis, this paper proposes to add FLTH to DTC to reduce torque ripple. FLTH can not only effectively use many voltage vectors, but also reduce torque ripple. In the case study, the torque ripple rate has been reduced by 53%. Through simulation and experiment, the conventional DTC and the FLTH DTC are compared, and the results prove the validity of the proposed strategy.

In order to predict the deformation displacement of the dam and maintain the safety of the dam operation, this paper takes the Xiaolangdi Dam in Luoyang City, Henan Province as the research object, and uses the 52-period monitoring data of a monitoring point on the dam as the data source. The Spearman rank correlation coefficient analysis method was used to analyze the correlation of 15 influencing factors affecting the dam deformation, and the main influencing factors were determined. The wavelet neural network is constructed, the optimal wavelet function and the number of hidden layer nodes are determined, and the dam displacement prediction is realized. By comparing with BP neural network, the superiority of wavelet neural network is verified. The results show that the main factors affecting dam deformation are T0, sinT, cosT and H, respectively. The RMSE and MAE of the prediction results of the wavelet neural network are 0.1932 dm and 0.1398 dm, respectively, which are reduced by 0.6092 dm and 0.444 dm compared with the BP neural network. The research results can provide some reference value for the safe operation and maintenance of the dam.

Winches are widely used on board ship’s deck machinery for anchor handling and mooring. The marine winch market was dominated by hydraulic systems and there is a trend to be replaced by more efficient electrical drive system. For both anchoring and mooring control, full load torque is required through the entire speed range including zero speed operation. This poses a challenge for the inverter driven motor control, especially when there is no speed or position sensor. This thesis aims to develop advanced control algorithms of permanent magnet (PM) machine including direct torque control (DTC) and sensorless control for marine winch application. In this thesis, direct torque control, as a new type of high-performance ac driving system after vector control technique, is mainly concerned. Furthermore, since the traditional switch-table based DTC ac motor drive is usually affected by the torque ripple problem and steady-state error problem in torque, this thesis introduced a modified 12-sector DTC control method. The subsystems of traditional DTC system and modified DTC system for permanent magnet synchronous machine (PMSM) are modeled and designed in PSIM software. Then the simulation models of the above two control strategies are also established. Simulation research is conducted and the results are corresponding with theory analysis: the improved system has good dynamic and static performance; less flux and torque ripple especially in the low speed range. The second part of this thesis is to realize sensorless control of DTC control system. Considered the actual situation on board, different methods for high-speed range and low-speed range are discussed. The rotating high frequency (hf) voltage signal injection as low-speed sensorless control method is good for its simplicity and better tracking accuracy, while the back-EMF integral as high-speed method is suitable for its mature industrial applications. And the hf injection method used in this thesis is designed to compatible with the DTC method applied in this thesis, which successfully extended the speed range without sacrificing the simplicity of DTC method.

In the article, a mathematical model of the DTC (direct torque control) system of an alternating current electric drive is developed for the tasks of urban electric transport rolling stock, as an alternative to complex vector control of an asynchronous motor, taking into account its relevance, principles of operation and causes of occurrence. The research of the mathematical model of the direct control of the torque of the asynchronous motor in MATLAB was carried out, its main shortcomings, which limit the scope of its application, were revealed. The main task of the DTC system is to identify the stator flux linkage, which is solved by integration with error accumulation. The source of error accumulation is the inaccuracy of determining the active resistance of the stator and its changes during the operation of the asynchronous motor. The DTC system has a disadvantage associated with the appearance of torque ripples and rotor speed fluctuations at low loads.

To solve the strong randomicity and slow convergence of the Particle Swarm Optimization(PSO) algorithms, two new particle’s position renewal formulas were analyzed on the basis of extrapolation in mathematics. A new modified PSO algorithms (called Leading PSO algorithms) was put forward. The Direct Torque Control(DTC) System was built in the environment of Matlab(Simulink). The weight and threshold values of BP Neural Network were trained using the modified PSO algorithms. Some disadvantages such as slow convergence speed and easily plunging into the local solution were avoided effectively. The simulation result shows that the system works well, and the rotor speed identifier has great static and dynamic performance.

The Sixth International Symposium on Neural Networks (ISNN 2009)

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.

To overcome integrator initial value, error accumulation and DC offset of pure integration, there proposed a permanent magnet synchronous motor stator flux observation method based on full-dimensional state observer. It uses the stator flux as state vector structural system state equation, the current as the output vector structural system output equation. And it configures the observer poles proportional to the motor model poles and use robust pole assignment algorithm in Matlab for observer gain matrix calculation. Experiments show that the full-dimensional observer on the stator flux observed has higher accuracy. The direct torque control system has better performance.

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.

&lt;span&gt;Multilevel inverter (MLI) is commonly utilized in direct torque control (DTC) for medium and high power applications. The additional voltage vectors generated by MLI can be manipulated to achieve the optimal selection for the inverter switching states in the DTC control systems. Previously, a review of DTC which focused more on the two-level inverter for induction motor as well as a review of the multilevel converter in industrial applications had been implemented individually. However, a review on DTC development in MLI was insufficient in both papers. Therefore, this paper aims to give a comprehensive review of the improvement of DTC via various MLI applications. It is reviewed according to the applicable multilevel inverter topologies in the DTC system. The comparison of DTC by using conventional and multilevel inverter is synthesized. Thus, this review paper will hopefully lead researchers in further research activities actively.&lt;/span&gt;

Electrical capacitance tomography (ECT) technique is a new technique for two-phase flow measurement. ECT is a complex nonlinear problem. To solve the ill-posed image reconstruction problem, image reconstruction algorithm based on wavelet neural networks (WNN) was presented. The principal component analysis (PCA) method was used to reduce the dimension of the input vectors. The transfer functions of the neurons in the WNN were wavelet base functions which were determined by retract and translation factors. The input measurement data were obtained using the ECT simulation software developed by the author. BP algorithm was used to train the WNN, and self-adaptive learning rate and momentum coefficient were also used to accelerate the learning speed. Experimental results showed the image quality has been improved markedly, compared with the typical linear back projection (LBP) algorithm and Landweber iteration algorithm.

This paper proposes a variable speed wind generation system using a direct torque controlled interior permanent magnet synchronous generator. The proposed system has no wind speed and generator position sensors, and thus, it is considered that the proposed system has cost and reliability advantages. The proposed direct torque control (DTC) system in wind power generation has several advantages over conventional current control. First, DTC is well suited for the maximum power point tracking (MPPT) control that is implemented by controlling the generator torque. Second, the method of flux-weakening to maintain the terminal voltage at the limiting value of the converter is simple. Finally, a novel method is proposed for torque limiting, which makes it easy to maintain the armature current at the limiting value. The proposed method accomplishes current limiting using the reactive torque, which is calculated as the inner product of the flux and current. This does not require generator parameters such as magnet flux and inductances. Experimental results demonstrate the effectiveness of the proposed system using a wind turbine emulator instead of the actual wind turbine.

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.