Laboratory Implementation of Direct Torque Controller based Speed Loop Pseudo Derivative Feedforward Controller for PMSM Drive

This paper,evaluate the effectiveness of a proposed speed loop pseudo derivative feedforward(PDFF)controller-based direct torque controller(DTC)for a PMSM drive against the performance of existing PI speed controller-based DTC and hysteresis current controller(HCC).The proposed PDFF-based speed regulator effectively reduces oscillation and overshoot associated with rotor angular speed,electromagnetic torque,and stator current.Two case studies,one using forward-to-reverse motoring operation and the other involving reverse-to-forward braking operation,has been validated to show the effectiveness of the proposed control strategy.The proposed controller's superior performance is demonstrated through experimental verification utilizing an FPGA controller for a 1.5 kW PMSM drive laboratory prototype.

Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor

This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.

A novel fuzzy logic direct torque controller for a permanent magnet synchronous motor with a field programmable gate array

A high-performance digital servo system built on the platform of a field programmable gate array (FPGA),a fully digitized hardware design scheme of a direct torque control (DTC) and a low speed permanent magnet synchronous motor (PMSM) is proposed. The DTC strategy of PMSM is described with Verilog hardware description language and is employed on-chip FPGA in accordance with the electronic design automation design methodology. Due to large torque ripples in low speed PMSM,the hysteresis controller in a conventional PMSM DTC was replaced by a fuzzy controller. This FPGA scheme integrates the direct torque controller strategy,the time speed measurement algorithm,the fuzzy regulating technique and the space vector pulse width modulation principle. Experimental results indicate the fuzzy controller can provide a controllable speed at 20 r min-1 and torque at 330 N m with satisfactory dynamic and static performance. Furthermore,the results show that this new control strategy decreases the torque ripple drastically and enhances control performance.

Direct Torque Control System and Sensorless Technique of Permanent Magnet Synchronous Motor

The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many basic theoretical problems that must be clarified. Thispaper describes an investigation about the effect of the zero voltage space vectors in the DTCsystem of PMSM and points out that if using the zero voltage space vectors rationally, not only canthe DTC system be driven successfully but also the torque ripple is reduced and the performance ofthe system is improved. This paper also studies the sensorless technique in the DTC system of PMSMand configures the DTC system of PMSM with sensorless technique including zero voltage spacevectors. Numerical simulations and experimental tests have proved the theory correct. In thecondition of sensor-less, the DTC system of PMSM is wide-rangely speed adjusting, and the ratio ofspeed adjustment is 1: 100.

Application of neural networks for permanent magnet synchronous motor direct torque control

Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.

Direct adaptive control for lane keeping in intelligent vehicle systems

In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slid angle are fast.

Controlled Secure Direct Communication Protocol via the Three-Qubit Partially Entangled Set of States

In this paper,we first re-examine the previous protocol of controlled quantum secure direct communication of Zhang et al.’s scheme,which was found insecure under two kinds of attacks,fake entangled particles attack and disentanglement attack.Then,by changing the party of the preparation of cluster states and using unitary operations,we present an improved protocol which can avoid these two kinds of attacks.Moreover,the protocol is proposed using the three-qubit partially entangled set of states.It is more efficient by only using three particles rather than four or even more to transmit one bit secret information.Given our using state is much easier to prepare for multiqubit states and our protocol needs less measurement resource,it makes this protocol more convenient from an applied point of view.

Distributed Asymptotic Consensus in Directed Networks of Nonaffine Systems With Nonvanishing Disturbance

In this paper the distributed asymptotic consensus problem is addressed for a group of high-order nonaffine agents with uncertain dynamics,nonvanishing disturbances and unknown control directions under directed networks.A class of auxiliary variables are first introduced which forms second-order filters and induces all measurable signals of agents’states.In view of this property,a distributed robust integral of the sign of the error(DRISE)design combined with the Nussbaum-type function is presented that guarantees not only the desired asymptotic consensus,but also the uniform boundedness of all closed-loop variables.Compared with the traditional sliding mode control(SMC)technique,the main feature of our approach is that the integral operation in the proposed control algorithm is designed to be adopted in a continuous manner and ensures less chattering behavior.Simulation results for a group of Duffing-Holmes chaotic systems are employed to verify our theoretical analysis.

Direct Yaw Moment Control for Distributed Drive Electric Vehicle Handling Performance Improvement

For a distributed drive electric vehicle（DDEV） driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control（DYC） has been widely studied and applied to vehicle stability control. Good vehicle handling performance： quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts： a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error（ITAE） function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method： yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.

Model Predictive Control-Based Direct Torque Control for Matrix Converter-Fed Induction Motor with Reduced Torque Ripple

To reduce the torque ripple in motors resulting from the use of conventional direct torque control(DTC),a model predictive control(MPC)-based DTC strategy for a direct matrix converter-fed induction motor is proposed in this paper.Two new look-up tables are proposed,these are derived on the basis of the control of the electromagnetic torque and stator flux using all the feasible voltage vectors and their associated switching states.Finite control set model predictive control(FCS-MPC)has then been adopted to select the optimal switching state that minimizes the cost function related to the electromagnetic torque.Finally,the experimental results are shown to verify the reduced torque ripple performance of the proposed MPC-based DTC method.

Dynamic modeling and direct power control of wind turbine driven DFIG under unbalanced network voltage conditions

This paper proposes an analysis and a direct power control (DPC) design of a wind turbine driven doubly-fed induction generator (DFIG) under unbalanced network voltage conditions. A DFIG model described in the positive and negative synchronous reference frames is presented. Variations of the stator output active and reactive powers are fully deduced in the presence of negative sequence supply voltage and rotor flux. An enhanced DPC scheme is proposed to eliminate stator active power oscillation during network unbalance. The proposed control scheme removes rotor current regulators and the decomposition processing of positive and negative sequence rotor currents. Simulation results using PSCAD/EMTDC are presented on a 2-MW DFIG wind power generation system to validate the feasibility of the proposed control scheme under balanced and unbalanced network conditions.

A Novel Fuzzy Direct Torque Control System for Three-level Inverter-fed Induction Machine

Diode clamped multi-level inverter （DCMLI） has a wide application prospect in high-voltage and adjustable speed drive systems due to its low stress on switching devices, low harmonic output, and simple structure. However, the problem of complexity of selecting vectors and capacitor voltage unbalance needs to be solved when the algorithm of direct torque control （DTC） is implemented on DCMLI. In this paper, a fuzzy DTC system of an induction machine fed by a three-level neutral-point-clamped （NPC） inverter is proposed. After introducing fuzzy logic, optimal selecting switching state is realized by applying various strategies which can distinguish the grade of the errors of stator flux linkage, torque, the neutral-point potential, and the position of stator flux linkage. Consequently, the neutral-point potential unbalance, the dr/dr of output voltage and the switching loss are restrained effectively, and desirable dynamic and steady-state performances of induction machines can be obtained for the DTC scheme. A design method of the fuzzy controller is introduced in detail, and the relevant simulation and experimental results have verified the feasibility of the proposed control algorithm.

Analysis and Improvement of an Efficient Controlled Quantum Secure Direct Communication and Authentication Protocol

The controlled quantum secure direct communication(CQSDC)with authentication protocol based on four particle cluster states via quantum one-time pad and local unitary operations is cryptanalyzed.It is found that there are some serious security issues in this protocol.An eavesdropper(Eve)can eavesdrop on some information of the identity strings of the receiver and the controller without being detected by the selective-CNOT-operation(SCNO)attack.By the same attack,Eve can also steal some information of the secret message that the sender transmits.In addition,the receiver can take the same kind of attack to eavesdrop on some information of the secret message out of the control of the controller.This means that the requirements of CQSDC are not satisfied.At last,we improve the original CQSDC protocol to a secure one.

Robust Position Observer for Sensorless Direct Voltage Control of Stand-Alone Ship Shaft Brushless Doubly-Fed Induction Generators

The aim of this paper is to investigate an adaptive sensorless direct voltage control(DVC)strategy for the stand-alone ship shaft brushless doubly-fed induction generators(BDFIGs).The proposed new rotor position observer using the space vector flux relations of BDFIG may achieve the desired voltage control of the power winding(PW)in terms of magnitude and frequency,without any speed/position sensors.The proposed algorithm does not require any additional observers for obtaining the generator speed.The proposed technique can directly achieve the desired DVC based on the estimated rotor position,which may reduce the overall system cost.The stability analysis of the proposed observer is investigated and confirmed with the concept of quadratic Lyapunov function and using the multi-model representation.In addition,the sensitivity analysis of the presented method is confirmed under different issues of parameter uncertainties.Comprehensive results from both simulation and experiments are realized with a prototype wound-rotor BDFIG,which demonstrate the capability and efficacy of the proposed sensorless DVC strategy with good transient behavior under different operating conditions.Furthermore,the analysis confirms the robustness of the proposed observer via the machine parameter changes.

Simplified EKF Based Sensorless Direct Torque Control of Permanent Magnet Brushless AC Drives

A simplified extended Kalman filter (EKF) based sensorless direct torque control technique for a permanent magnet brushless AC drive is proposed. Its performance is compared with that obtained with other sensorless methods for estimating the rotor speed and position from a stator flux-linkage. Since the EKF has an inherently adaptive filtering capability and does not introduce phase delay, the technique provides better speed estimates. In addition, the technique is easy to implement and requires minimal computation.

Fuzzy-second order sliding mode control optimized by genetic algorithm applied in direct torque control of dual star induction motor

The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.

Optimal guidance strategy for flexible load based on hybrid direct load control and time of use

The time-of-use(TOU)strategy can effectively improve the energy consumption mode of customers,reduce the peak-valley difference of load curve,and optimize the allocation of energy resources.This study presents an Optimal guidance mechanism of the flexible load based on strategies of direct load control and time-of-use.First,this study proposes a period partitioning model,which is based on a moving boundary technique with constraint factors,and the Dunn Validity Index(DVI)is used as the objective to solve the period partitioning.Second,a control strategy for the curtailable flexible load is investigated,and a TOU strategy is utilized for further modifying load curve.Third,a price demand response strategy for adjusting transferable load is proposed in this paper.Finally,through the case study analysis of typical daily flexible load curve,the efficiency and correctness of the proposed method and model are validated and proved.

Application of direct torque control to electric screw presses for speeding up torque response and reducing starting current

Fast response and stable torque output are crucial to the performance of electric screw presses. This paper describes the design of a direct torque control （DTC） system for speeding up torque response and reducing the starting current of electric screw presses and its application to the J58K series of numerical control electric screw presses with a dual-motor drive. The DTC drive system encompasses speed control, torque reference control, and switching frequency control. Comparison of the DTC dual-AC induction motor drive with corresponding AC servo motor drive showed that for the J58K-315 electric screw press, the DTC drive system attains a higher maximum speed （786 r/min） within a shorter time （1.13 s） during a 250 nun stroke and undergoes smaller rise in temperature （42.0 ℃） in the motor after running for 2 h at a 12 min-1 strike frequency than the AC servo motor drive does （751 r/min within 1.19 s, and 50.6 ℃ rise）. Moreover, the DTC AC induction motor drive, with no need for a tachometer or position encoder to feed back the speed or position of the motor shaft, enjoys increased reliability in a strong-shock work environment.

Robust H_∞ directional control for a sampled-data autonomous airship

A robust H∞ directional controller for a sampled-data autonomous airship with polytopic parameter uncertainties was proposed. By input delay approach, the linearized airship model was transformed into a continuous-time system with time-varying delay. Sufficient conditions were then established based on the constructed Lyapunov-Krasovskii functional, which guarantee that the system is mean-square exponentially stable with H∞ performance. The desired controller can be obtained by solving the obtained conditions. Simulation results show that guaranteed minimum H∞ performance γ=1.4037 and fast response of attitude for sampled-data autonomous airship are achieved in spite of the existence of parameter uncertainties.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ～ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ～(O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits.