Robust fractional order sliding mode control of doubly-fed induction generator (DFIG)-based wind turbines

Wind power plants have nonlinear dynamics and contain many uncertainties such as unknown nonlinear disturbances and parameter uncertainties. Thus, it is a difficult task to design a robust reliable controller for this system. This paper proposes a novel robust fractional-order sliding mode (FOSM) controller for maximum power point tracking (MPPT) control of doubly fed induction generator (DFIG)-based wind energy conversion system. In order to enhance the robustness of the control system, uncertainties and disturbances are estimated using a fractional order uncertainty estimator. In the proposed method a continuous control strategy is developed to achieve the chattering free fractional order sliding-mode control, and also no knowledge of the uncertainties and disturbances or their bound is assumed. The boundedness and convergence properties of the closed-loop signals are proven using Lyapunov׳s stability theory. Simulation results in the presence of various uncertainties were carried out to evaluate the effectiveness and robustness of the proposed control scheme.     

Experimental sensorless control for a coupled two-tank system using high gain adaptive observer and nonlinear generalized predictive strategy

In this paper an adaptive control for a coupled two-tank system is proposed. This control strategy uses a generalized predictive controller, whose main method is to minimize a multistage cost function defined over a prediction horizon. Furthermore, to implement this controller in the framework of the sensorless control from the only measurement of the liquid level in the bottom tank, an adaptive interconnected high gain observer is developed for estimating the liquid level in the upper tank and the two constant parameters of the system. Two design features are worth to be emphasized. Firstly, the control calibration is achieved through the tuning of only two scalar design parameters. Secondly, the exponential convergence to zero of the state observation and parameter estimation errors is established under a well defined condition. Finally, the theoretical results are corroborated through simulation and experimental results which highlight the efficiency and applicability of the proposed observer–controller scheme.     

基于神经网络的非线性系统约束预测控制

利用非线性激励函数的局部线性表示,提出一种可用于非线性过程的基于神经网络模型的约束广义预测控制算法。该算法将非线性搜索转化为只对当前控制增量的约束,避免了非线性优化求解,并不需要很多的计算量。文中给出了仿真结果。     

一种隐式广义预测自校正控制算法及仿真研究

广义预测控制是一种新型的远程预测控制方法,它集多种算法的优点为一体,具有较强的鲁棒性。采用不辨识对象模型参数的隐式算法,更是大大减少了计算工作量,节省了时间。该文介绍了一种隐式广义预测自校正控制算法且对其进行仿真研究,分析仿真结果,总结参数变化对整个系统性能的影响,结果说明了该算法的优越性和可行性。     

Speed sensorless model predictive current control of doubly-fed induction machine drive using model reference adaptive system

This paper presents a speed sensorless control scheme named as finite control set-model predictive current control (FCS-MPCC) using a modified fictitious ohmic quantity (R) based model reference adaptive system (MRAS) for grid-connected doubly-fed induction machine (DFIM) drive. The variables of the reference model of this speed sensorless scheme (R-MRAS) are represented in stationary reference frame while those for the adaptive model are denoted in synchronously rotating reference frame. The sensorless formulation thus obtained is completely independent of any stator/rotor resistance terms. The scheme is also devoid of any stator/rotor flux estimation. Moreover, the intuitiveness of FCS-MPCC brings in additional flexibility in comparison to the conventional control techniques like field oriented control (FOC) and direct torque control (DTC). The overall scheme demonstrates faster execution time than FOC/DTC based control of DFIM drive. The proposed control algorithm is simulated and tested for limited speed range application in MATLAB/Simulink. The validation of simulation results are further done by experimentation on a dSPACE-1103 based DFIM laboratory setup.     

基于T-S模糊模型的非线性系统广义预测控制

针对离散非线性系统,提出一种基于T-S模糊模型的广义预测控制方法。该方法将采样点的T-S模糊模型转化为采样点线性模型与非线性误差叠加的线性形式,通过迭代修正非线性误差,使具有非线性误差的线性模型预测控制律逐渐逼近采样点T-S模糊模型预测控制律。同时,该预测控制方法也能适用于当系统受输入输出约束时的控制。仿真结果验证了所提出的TS模糊模型广义预测方法有效。     

一种离网型风力发电系统的不平衡控制策略

研究一种不平衡负载下离网型双馈电机的定子端与转子端变换器协调控制策略.在系统数学模型的基础上,对转子端变换器提出了一种直接电压控制方案,为了提高系统的动态响应和鲁棒性,设计了一种基于扩张状态观测器的转子电流控制方案,即通过扩张状态观测器估计系统总扰动,并以前馈方式消除该扰动.针对负载不平衡问题,通过在定子端采用三相四脚变换器对定子电流的零、负序分量进行补偿,消除了不平衡负载对双馈感应电机的不利影响,改善了发电系统的电能质量.为了减少控制器的计算负担,对定子端变换器交流侧的电流采用比例-谐振(PR)控制,有效地避免了繁琐的正、负序分离计算,简化了控制算法.仿真和实验结果验证了该方案的正确性及可行性.     

考虑分散式风电的配网电压稳定性研究

根据分散式风电场接入配电网的等效模型,分析了双馈风电机组接入配电网的无功出力特性。利用双馈风电机组快速的动态无功响应特性,提出了风电机组自身无功出力参与各接入点无功电压控制的分散式风电无功电压协调控制方案。通过监测分散式风电场各接入点出力与电压信息,采用过滤集合的原对偶内点法求解无功电压协调控制模型,在满足各接入点电压约束的同时,均衡了风电场的无功裕度,提高了配电网的电压稳定性。通过30节点配电网算例验证了所提模型及控制的合理性和有效性。     

基于预测函数控制和扰动观测器的永磁同步电机速度控制

设计了基于预测函数控制的速度控制器,以减小永磁同步电机的转矩波动,提高电机的转速控制精度。针对因外部扰动因素引起的控制器跟踪性能下降问题,设计了基于预测函数控制和扰动观测器的双环控制器;通过扰动观测器估计系统扰动,并据此产生转矩电流补偿量对控制量进行前馈修正,从而实现扰动的抑制。实验结果显示：当电机从静止跟踪到设定600 r/min转速时,系统没有超调,稳态精度为2 r/min;当电机以600 r/min稳速运行并加入1.6 N·m的转矩扰动时,转速最大波动为5 r/min。与传统的PI控制算法相比,所设计的控制器使转速波动减小了4.2% 。仿真分析和实验数据表明：基于预测函数控制和干扰观测器的控制器能够有效地抑制扰动,提高系统转速跟踪精度。     

SRG风力发电系统最大风能追踪控制研究

针对在实验室条件下实现SRG风力发电系统的最大风能追踪控制的问题,对风力机的运行特性及其模拟实现方案、开关磁阻电机的工作原理及其控制方法等方面进行了研究,并对风力发电系统中实现最大风能追踪的控制策略进行了介绍,提出了基于转速反馈的SRG发电系统最大风能追踪控制方案,同时对直流电机进行了转矩控制以实现风力机输出特性的模拟.在SRG风力发电系统平台上对风力机模拟系统进行了测试评价,并进行了变风速条件下的最大风能追踪试验.研究结果表明,直流电机能够有效模拟风力机的输出特性,控制简单,抗干扰能力强,基于转速反馈的MPPT控制方法能够在风速变化时快速调节SRG输出,准确地实现最大风能跟踪.     

Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics

This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable.     

小型脱网风力发电系统功率优化控制

脱网小型风力发电系统对边远地区供电具有无可比拟的优越性。构建了以鼠笼式感应电机为发电系统的脱网小功率风力发电系统,给出了主电路拓扑结构。实现了空气动力学子系统、机械传动链子系统的分析和建模,结合鼠笼式感应电机的矢量控制,详细设计了系统的功率控制环,在MATLAB环境下进行了系统仿真,仿真结果表明,该系统能实现小功率风力发电系统的功率跟踪优化控制。     

Disturbance-observer-based fuzzy model predictive control for nonlinear processes with disturbances and input constraints

This paper proposes a disturbance-observer-based fuzzy model predictive control (DOBFMPC) scheme for the nonlinear process subject to disturbances and input constraints. The proposed control scheme is composed of the baseline fuzzy model predictive control (FMPC) law designed on the Takagi–Sugeno fuzzy model and the disturbance compensation law. To build a fuzzy model of appropriate complexity and accuracy for the nonlinear process model, a systematic approach is developed via the gap metric to determine the linearization points. With FMPC, the asymptotic stability is theoretically proved, and the input constraints are satisfied by both the free control variables and the future control inputs in the form of the state feedback law. The disturbance compensation gain is designed such that the influence of the disturbance is removed from the output channels by the composite DOBFMPC law at the steady state. The application to a subcritical boiler–turbine system demonstrate the effectiveness of the proposed control scheme.     

An improved model-based predictive control of vehicle trajectory by using nonlinear function

A new model-based predictive control algorithm for vehicle trajectory control is proposed by using vehicle velocity and sideslip angle. Based on the error function combined with vehicle velocity and side slip of a bicycle model, a predictive control method has been proven to be useful on low velocity. Thus, it could be applied for an autonomous vehicle without a driver. Although an autonomous robot is not necessary to be driven with a high velocity, a commercial vehicle has to be driven at high velocity. Thus the previous predictive control formulation is not enough for a commercial driving system. This study is proposed to enhance the capacity of the predictive controller for rather high speed vehicles. This paper was presented at the 4th Asian Conference on Multibody Dynamics(ACMD2008), Jeju, Korea, August 20–23, 2008. Mr. Jeong-Han Lee is pursuing a Ph.D. degree in Mechanical Engineering at Pusan National University under the supervision of professor Wan-Suk Yoo. His research interests are focused on the area of adaptive control using multibody dynamics. Dr. Wan-Suk Yoo received his Ph.D. degree in 1985 from the University of Iowa. In 1994, he became a full professor at the Pusan National University, and he was selected an ASME fellow. He is serving as a vicepresident of the KSME.     

Performance optimization of linear active disturbance rejection control approach by modified bat inspired algorithm for single area load frequency control concerning high wind power penetration

The linear active disturbance approach is employed to deal with the load frequency control issue of a single area wind power system based on doubly fed induction generator, and the performance of the control law is optimized by using the bat-inspired algorithm. The load frequency control issue has become more challenging in a complex power system based on wind energy conversion system due to the varying feature of the wind penetration, and sustaining the balance between the power generation and demand by rejecting the internal uncertainties in the process model and the external disturbances simultaneously. In the framework of the presented linear active disturbance rejection control approach, by constructing an extended state observer, the total disturbance, including all the unmodelled dynamics in the process model and the external disturbances, can be estimated in real time and then compensated by a simple linear PD control law. The controller parameters tuning is then simplified into the optimization of the two bandwidths: observer bandwidth, and the controller bandwidth. Then, this issue can be achieved by employing the heuristic modified bat inspired algorithm based on the optimization of the proposed performance index. The effectiveness of the proposed approach is validated by the extensive simulation examples of the load frequency control issue involved in the single area power system, taking into account different wind penetration, as well as the external disturbances. The performance robustness of the proposed approach against the parameters perturbation in the process model is also demonstrated via the Monte-Carlo method. The performance superiority of the proposed approach over the conventional Proportional Integral and Fuzzy-Proportional Integral based controller even in the presence of external disturbances and uncertainty in power system parameters under different cases of high wind penetration is also validated from the simulation results.     

不平衡及谐波电网条件下双馈风电变流器的改进控制研究

针对双馈风电机组在电网电压不平衡及谐波畸变条件下的故障穿越问题,分析了此类电网故障对机组运行性能的影响,提出了一种双馈机组转子侧、网侧变流器的协同控制方案。通过改进转子侧、网侧变流器的矢量控制算法,抑制了双馈感应电机的电磁转矩波动,降低了机组输出总有功功率的波动,获得了对称、正弦的机组输出电流。仿真结果表明,所述控制方案能够显著改善双馈风电机组在此类电网故障条件下的运行性能,从而提高机组的故障穿越运行能力。     

变速恒频双馈风力发电机组的逆系统控制研究

为解决矢量控制方法在双馈风力发电机组中存在的对电机参数比较敏感和在扰动下控制不稳定等问题,将逆系统技术应用到双馈感应发电机(DFIG)的控制中.根据输入/输出状态方程得到了逆系统解析表达式,建立了双馈风力发电逆系统闭环控制.在计算机仿真软件Matlab上对该控制系统在电压跌落时和变速恒频时进行了仿真,仿真结果表明逆系统...