异步电动机直接转矩控制系统研究

传统的感应电机直接转矩控制系统存在转矩脉动大等缺点,为提高感应电机直接转矩控制系统的动态性能,采用一种改进的转矩估算模型,在推导其数学模型的基础上,采用MATLAB/SIMULINK仿真软件对感应电机新型直接转矩控制系统进行建模与仿真,仿真实验研究结果表明：采用改进的转矩估算模型可以提高异步电动机直接转矩控制系统的动态性能。     

A robust vector control for induction motor drives with an adaptive sliding-mode control law

A novel adaptive sliding-mode control system is proposed in order to control the speed of an induction motor drive. This design employs the so-called vector (or field oriented) control theory for the induction motor drives. The sliding-mode control is insensitive to uncertainties and presents an adaptive switching gain to relax the requirement for the bound of these uncertainties. The switching gain is adapted using a simple algorithm which does not imply a high computational load. Stability analysis based on Lyapunov theory is also performed in order to guarantee the closed loop stability. Finally, simulation results show not only that the proposed controller provides high-performance dynamic characteristics, but also that this scheme is robust with respect to plant parameter variations and external load disturbances.     

Data-driven adaptive optimal control of linear uncertain systems with unknown jumping dynamics

This paper focuses on the optimal control of a DC torque motor servo system which represents a class of continuous-time linear uncertain systems with unknown jumping internal dynamics. A data-driven adaptive optimal control strategy based on the integration of adaptive dynamic programming (ADP) and switching control is presented to minimize a predefined cost function. This takes the first step to develop switching ADP methods and extend the application of ADP to time-varying systems. Moreover, an analytical method to give the initial stabilizing controller for policy iteration ADP is proposed. It is shown that under the proposed adaptive optimal control law, the closed-loop switched system is asymptotically stable at the origin. The effectiveness of the strategy is validated via simulations on the DC motor system model.     

Performance comparison of a Canonical Switching Cell with SPWM and SVPWM fed sensorless PMBLDC motor drive under conventional and fuzzy logic controllers

In this paper, speed control, torque ripple minimization and Power Factor Correction (PFC) of a Canonical Switching Cell (CSC) with Sinusoidal and Space Vector Pulse Width Modulated (SVPWM) sensorless Permanent Magnet Brushless DC (PMBLDC) motor drive system with varying load is discussed. The constant speed of operation with minimum torque ripples and Unity Power Factor (UPF) operation during transient state is the most difficult control part in the motor drive system. At the starting condition, the current is too high due to the absence of back EMF and therefore the motor will start with high torque ripples. In order to eliminate these torque ripples during starting condition by limiting the starting current of the motor, it is necessary to have properly designed Canonical Switching Cell (CSC) converter and an intelligent controller, which will improve the power factor of the supply system and reliability of the PMBLDC motor drive. Here, the speed control, torque ripple minimization and power factor correction of a sensorless PMBLDC motor during starting and running condition with conventional and fuzzy logic controllers are proposed. The performance parameters of a PMBLDC motor with these controllers is analyzed through MATLAB/Simulink software.     

Multi-VSM based fuzzy adaptive cooperative control strategy for MVDC traction power supply system

This paper studies the control of a medium-voltage DC (MVDC) traction power supply system for rail transit (RT). In order to optimize the ability of DC voltage fluctuation and frequency regulation of rail trains, a fuzzy adaptive cooperative secondary control strategy based on improved virtual synchronous machine (VSM) is proposed. Firstly, the improved VSM control strategy is adopted in the traction substations (TSSs), which makes the RT trains have the external characteristics of synchronous generator and have certain inertia and damping support capacity, so as to improve the ability of the RT traction system to cope with traction network transient changes. Secondly, the virtual inertia and virtual damping can be dynamically adjusted by the system frequency deviating from the nominal steady-state frequency, and the dynamic fuzzy adjustment can be carried out by the fuzzy logic system to slow down the frequency fluctuation. Then, due to the different power supply distances and parameter settings between multiple TSSs, cooperative control is used to coordinate local TSS perceptions of information between adjacent TSS to achieve consistency of frequency response of multiple TSSs under different parameters. Besides, a time-varying switching topology handoff method is considered to select the optimal communication topology between adjacent base stations. Finally, simulation results verify the effectiveness of the proposed control strategy.     

Robust sliding mode control of a DC/DC Boost converter with switching frequency regulation

This paper presents the design of a hysteresis band controller to regulate the switching frequency in a sliding mode controlled nonlinear Boost power converter. The proposed architecture relies on a piecewise linear modeling of the switching function behavior within the hysteresis band, and consists of a continuous-time integral-type controller that modifies the amplitude of the hysteresis band of the comparator in accordance with the error between the desired and the actually measured switching period. The study provides the dynamical models of the converter operating in sliding mode and the switching frequency control loop. Moreover, the design of the parameters of both the sliding mode control and the switching frequency controller guarantee the fulfilment of the desired output voltage regulation of the Boost converter and the steady state setting of the switching frequency with a known, taylored dynamics. A Boost power converter prototype has been built to validate the proposal. Experimental results confirm the predicted good performance of the controllers, as well as the robustness with respect to changes in the switching frequency reference and the system parameters.     

Adaptive multi objective differential evolution with fuzzy decision making in preventive and corrective control approaches for voltage security enhancement

This paper presents a multi objective differential evolution (MODE) based voltage security enhancement through combined preventive-corrective control strategy. Load shedding, generation rescheduling and optimal utilization of FACTS devices are considered for security enhancement. Maximum l-index of load buses is taken as the indicator of voltage stability. Minimization of cost of FACTS devices, minimization of amount of load shedding along with improvement in voltage stability are the objectives of this multi objective optimization problem. The optimal location of FACTS devices are selected using modal analysis technique. The buses for load shedding are selected based on the minimum eigen value of load flow Jacobian. The proposed MODE algorithm employs DE/randSF/1/bin strategy scheme with self tuned parameter which employs binomial crossover and difference vector based mutation. A fuzzy based decision making algorithm is employed to get the best compromise solution from the non dominated solutions. The proposed MODE is also tested with statistical performance metrices. The proposed methodology is implemented on IEEE 30 bus and IEEE 57 bus test systems. The proposed MODE method provides better solutions in the pareto optimal front than the other optimization techniques such as MOGA and NSGA II under combined preventive–corrective control approach. In IEEE 30 bus system, the amount of load shedding is reduced by 40% and voltage stability is improved by 15% and in IEEE 57 bus system, the amount of load shedding is reduced by 15.4% and voltage stability is improved by 13% by the proposed approach. Hence the simulation results show that the proposed approach provides considerable reduction in the amount of load shedding and enhancement of voltage stability by including generation rescheduling and utilization of FACTS devices.     

Sliding mode control of DC/DC converters

Sliding mode control algorithms for buck and boost power converters are surveyed in the paper. Current and voltage controls are demonstrated for the both cases. It is shown, that direct voltage control for a boost converter results in unstable zero dynamics. Chattering suppression based on harmonic cancellation principle along with switching frequency control is demonstrated.     

Cylinder position control driven by pneumatic digital bridge circuit using a fuzzy algorithm under large stroke and varying load conditions

A digital bridge circuit based on the concept of independent metering control can enable the precise position control of a pneumatic cylinder, but large strokes and variable loads still cause challenges. To solve this problem, a piecewise on/off valve flow compensator and a composite friction observer were innovatively designed in this study, and they were combined with a multiple fuzzy intelligent algorithm to ensure the accuracy and robustness of pneumatic position control. Considering the starting and stopping delays and the response processes of on/off valves, a six-stage flow–duty ratio linearization relationship was proposed. Employing a parameter identification method, a static and dynamic composite friction model was presented. Then, a fuzzy PID controller was proposed, and a genetic algorithm was used to optimize the control parameters. Experiment results showed that, when focusing on a large stroke (250 mm) and varying loads (8.5–18.5 kg), for sinusoidal signal with amplitude of 150 mm and frequency of 0.125 Hz and the air supply pressure is 0.5 Mpa, the algorithm in this study could ensure that the steady-state step response error was less than 1% and the root mean squared error of the sinusoidal trajectory tracking was less than 3%.     

Security control for two-time-scale cyber physical systems with multiple transmission channels under DoS attacks: The input-to-state stability

This paper investigates the security control problem for a class of two-time-scale cyber-physical systems (TTSCPSs) with multiple transmission channels under the denial-of-service (DoS) attacks. A linear TTSCPSs model is first proposed with slow and fast transmission channels, which correspond to slow and fast physical components in terms of their communicating capacities and sampling rates. The measurement data-packets are transmitted via slow and fast transmission channels which are compromised by asynchronous DoS attacks. A novel composite controller depending on the singular perturbation parameter (SPP) is formulated and corresponding switching laws are designed to achieve certain resilience against DoS attacks. Then, by establishing a SPP-dependent Lyapunov function, sufficient conditions are obtained on the duration and frequency of the DoS attacks, such that, for any SPP less than or equal to a predefined upper bound, the input-to-state stability can be guaranteed for the closed-loop TTSCPSs. Finally, a networked DC motor control system is employed to demonstrate the effectiveness of the proposed security control algorithm.     

开关磁阻电动机的非线性模型预测控制

将非线性预测控制应用于ＳＲＭ传动系统,建立了非线性参数预测模型,并在此基础上优化、校正,设计了ＳＲＭ的非线性速度预测控制器。该控制器具有实时预测、实时优化、实时校正的特点,很好地补偿了ＳＲＭ的非线性特性。与传统ＰＩ控制器相比,非线性模型预测控制器能提供更好的动态、静态特性,转矩脉动大为减小。（仿真结果表明,该控制策略不但正确、有效,而且使ＳＲＭ传动系统性能得到改善。     

Modeling and control analysis of electric driving system considering gear friction based on dual-inertia system

In the electric driving system, the measurement of the motor speed error becomes more and more important, which has an impact on the system vibration suppression. In this paper, based on the single-neuron adaptive PID control method, the dual-inertia system considering gear friction torque is modeled and studied. Firstly, the dual-inertia system with gear friction is established, and dynamic differential equations of it are derived; Then, the comprehensive meshing stiffness and the time-varying friction torque of the gear system are deduced; Next, the Ziegler-Nichlos frequency domain response method is adopted to obtain the parameters of the PID controller. The control methods including the PID, Fuzzy-PID with DOB and single-neuron adaptive PID are utilized to adjust the motor speed of the system; Finally, the effects of gear friction, the moment of inertia of load and control methods on motor speed and system error are analyzed.     

Optimal actuator switching synthesis of observer-based event-triggered state feedback control for distributed parameter systems

The study aims to explore the optimal actuator switching scheme of observer-based event-triggered state feedback control for distributed parameter systems. The performance of distributed parameter systems is improved through the observer-based event-triggered control, in which the state feedback is updated only when a triggered event happens. In such an event-triggered mechanism, the event-based closed-loop system and minimum time interval between consecutive events are bounded. Based on finite horizon linear quadratic regulator (LQR) optimal control, the optimal switching algorithm is proposed based on the event-triggered mechanism during an unfixed time interval. Finally, the proposed scheme is verified through a simulation case.     

A modified adaptive backstepping method for shaft deflection tracking control of magnetically suspended momentum wheel with nonlinear magnetic torque

A modified adaptive backstepping tracking method is proposed to improve the tracking performance of the magnetic bearing system with nonlinear magnetic toque. For a magnetically suspended momentum wheel, two dimensional gyroscopic torque can be produced when the rotor shaft is actively deflected by the active magnetic bearing. High precision rapid tracking control of shaft deflection is desiderated to provide high precision and wide bandwidth outputting torque. The nonlinearity of magnetic bearing is analyzed initially, and the stiffness coefficients of magnetic bearing can be treated as bounded continuous functions with respect to deflection angles. A fuzzy function based adaptive law is proposed to estimate the stiffness coefficients. Combining with a modified backstepping method, the proposed control strategy can deal with the nonlinearity efficiently when the shaft deflects rapidly, and its stability is proved by Lyapunov stability theory. To validate the effectiveness of this method, numerous simulations are performed and the results indicate that this method improves the tracking precision when tracking high frequency reference deflection angles.     

Event-triggered tracking control for couple-group multi-agent systems

This paper mainly investigates the event-triggered tracking control for couple-group multi-agent systems in a disturbance environment, where the topology of the agents is switching. Consensus protocol is designed for the case that some agents reach a consistent value, while the other agents reach another consistent value. Then, event-triggered control laws are designed to reduce the frequency of individual actuation updating for discrete-time agent dynamics. Moreover, by applying the Lyapunov function method, a sufficient condition of couple-group consensus is established in terms of a matrix inequality when the communication topology is switching. Finally, simulation examples are given to demonstrate the effectiveness of the proposed methods.     

Stability analysis and control synthesis for linear systems with non-symmetrical input saturation

This paper studies the stability and control problem of linear systems with non-symmetrical input saturation. A system with non-symmetrical input saturation is transformed into a system with switching symmetrical input saturation. A switching controller is designed based on a parametric algebra Riccati equation, dwell time and the equivalent switched system. Exponential stability is guaranteed with the proposed switching controller. The main advantages of the proposed method lie in reducing the conservatism caused by directly using symmetrical input saturation control and increasing the state convergent speed. The designed controller can be computed easily by solving the Riccati equation. Numerical examples are provided to demonstrate the effectiveness of the proposed method.     

一种出炉C辊道变频调速系统的数值仿真方法

针对设计热轧厂出炉C辊道传动与控制系统时方案可行性难分析、设备选型难确定等问题,提出了一种面向出炉C辊道,基于Simulink群拖方式的变频调速系统数值仿真方法。通过对系统起动过程中变频器输出电流、电压,电机定子电流、转矩、转速进行仿真分析,验证了该方法的可行性。     

Adaptive output feedback fault tolerant control for uncertain nonlinear systems based on actuator switching

In this paper, an adaptive output feedback fault tolerant control (FTC) based on actuator switching is proposed for a class of single-input single-output (SISO) nonlinear systems with uncertain parameters and possible actuator failures, for which a set of healthy actuators are available as backups. While high-gain K-filters are utilized to estimate the unmeasured states, an adaptive control law is designed to compensate for the parameter uncertainties and certain actuator failures, an actuator switching strategy based on a set of appropriately designed monitoring functions (MFs) is proposed to tackle those serious actuator failures, make tracking error satisfy prescribed transient and steady-state performance and guarantee closed-loop signal boundedness.     

Corresponding drivability control and energy control strategy in uninterrupted multi-speed mining trucks

An hybrid uninterrupted multi-speed transmission (HUMST), based on the integration of a planetary gear set and a 3-speed automatic manual transmission (3-AMT), is developed to satisfy the specific performance indexes of mining trucks. The power-split device can alleviate and eliminate the inherent torque interruption of the 3-AMT during gear shift by implementing the designed cooperative shift control strategy which is optimized by quadratic performance index. In order to achieve fast torque coordination while guaranteeing the driving comfort performance, the torque profiles of the power split device and the traction motor are optimized by Linear-quadratic regulator (LQR) algorithm. Dynamic programming (DP) is implemented as a benchmark to demonstrate the maximum fuel efficiency of the proposed HUMST. Because of the high computational cost of optimal control strategies such as DP, an improved real-time control strategy (IRTCS) using modified Gaussian distribution function is proposed to significantly reduce the computing load. As efficiency-oriented energy control strategy would result in frequent gear shifts, to achieve a desirable tradeoff between the overall efficiency and the shift stability, multi-objective genetic algorithm (MGA) is integrated to optimize the overall performance. The detail mathematical and dynamic model shows that the proposed shifting strategy with LQR can effectively suppress shift jerk, and the proposed IRTCS with MGA can reduce shift frequency by 70.78% to improve the drivability, only sacrificing 4.86% of overall efficiency compared to that of DP.     

Exponential stabilization of a non-uniform rotating disk-beam system via a torque control and a finite memory type dynamic boundary control

This paper is consecrated to the feedback stabilization of the rotating disk-beam system. The beam is assumed to be non-uniform and clamped at its left-end to the center of the disk where a torque control takes place, while a memory boundary control is acting at the right-end of the beam. First, the usual torque control is proposed, whereas the boundary control is designed by taking into account a special type of a memory phenomenon, as well as the dynamic features of the input. Sufficient conditions on the angular velocity of the disk and the memory term are derived to guarantee the existence and uniqueness of solutions of the system. Furthermore, the frequency domain method is utilized in order to achieve the exponential stability of the closed-loop system. The relevance of the theoretical outcomes is shown through several numerical simulations.