多区域互联电力系统的自适应滑模负载频率控制

本文研究了一类计及电动汽车的电力系统中的负荷频率控制问题, 首先, 将电动汽车模型与传统的负载频率控制模型相结合,在未知扰动波动范围的条件下设计了自适应滑模控制律. 其次, 分别考虑了电网调频中的匹配扰动和不匹配扰动问题, 并利用李亚普诺夫稳定性理论导出了匹配和不匹配条件下的系统稳定的充分条件. 最后, 两个区域电力系统的仿真结果表明, 电动汽车作为电源和负载都可以提高电网的频率稳定性, 所设计的控制器可以有效地调节电网的频率波动.     

Observer based robust integral sliding mode load frequency control for wind power systems

This paper investigates the load frequency control (LFC) for wind power systems with modeling uncertainties and variant loads. Since the system state is difficult to be accurately measured due to perturbation of nonlinear load, an observer is designed for reconstructing a substitution system state. Afterwards, an integral sliding surface is designed and a sliding mode LFC (SMLFC) strategy is proposed for reducing frequency deviations of the overall power system. Remarkably, it has been pointed out that a larger convergence rate of the observer error system has positive influences on the SMLFC performances, while the larger observer gain deteriorates the dynamic behavior. For seeking an acceptable balance so as to determine the optimal controller parameters, a collaborative design algorithm is proposed. The proposed method not only guarantees the asymptotical stability of overall power systems but also capable of improving the system robustness. Numerical examples are provided to demonstrate the effectiveness of the proposed methods.     

带有非线性不确定奇异系统的积分滑模控制

针对一类含有非线性不确定的奇异系统, 提出了一种面向性能的鲁棒控制器. 控制器由3部分组成: 积分滑模控制、附加的非线性控制及复合非线性反馈控制. 积分滑模控制可将匹配不确定完全抵消并使系统轨迹进入理想滑模; 附加的非线性控制用来抑制理想滑动模态上非匹配不确定对系统稳定性和性能的影响; 复合非线性反馈控制则保证闭环系统输出按性能要求渐近地跟踪参考输入信号. 最后通过算例说明所提算法的有效性.     

Designing an adaptive type-2 fuzzy logic system load frequency control for a nonlinear time-delay power system

In this paper, a combination of type-2 fuzzy logic system (T2FLS) and a conventional feedback controller (CFC) has been designed for the load frequency control (LFC) of a nonlinear time-delay power system. In this approach, the T2FLS controller which is designed to overcome the uncertainties and nonlinearites of the controlled system is in the feedforward path and the CFC which plays an important role in the transient state is in the feedback path. A Lyapunov–Krasovskii functional has been used to ensure the stability of the system and the parameter adjustment laws for the T2FLS controller are derived using this functional. In this training method, the effect of delay has been considered in tuning the T2FLS controller parameters and thus the performance of the system has been improved. The T2FLS controller is used due to its ability to effectively model uncertainties, which may exist in the rules and data measured by the sensors. To illustrate the effectiveness of the proposed method, a two-area nonlinear time-delay power system has been used and compared with the controller that uses the gradient-descend (GD) algorithm to tune the T2FLS controller parameters.     

一种BUCK变换器附加积分定频滑模控制技术

研究表明,将滑模控制技术应用于BUCK变换器时,其所得到的开关频率是不固定的,并且存在滞环滑模技术中的开关频率对噪声较为敏感等缺点.一般在滞环滑模控制系统中加入一个恒定的时间常数电路,或者利用自适应滞环控制技术,但都要引入外部电路,从而增加了电路的功耗.对此提出了一种附加积分项的定频滑模控制技术,通过将二阶标准系统应用到滑模轨迹中,设计了控制器的滑模系数;分析了引入附加积分对控制器性能的影响;为滑模控制器设计了指数趋近律,改善了趋近运动的动态品质;并利用MATLAB仿真验证了所提出的方法,证实了其在DC-DC变换器中具有较强的实用性.     

TORA系统基于自调节滑模干扰补偿器的解耦滑模控制

针对欠驱动TORA系统,提出一种基于自调节滑模干扰补偿器的解耦滑模控制方法。所提出的控制方法无需系统不确定性上界的先验信息,对于系统不确定性具有良好的适应性。该控制方法包括设计一种自调节滑模干扰补偿器和一种新型的双幂次趋近律,所设计的自调节滑模干扰补偿器能够利用切换增益自适应算法准确逼近上界未知的系统不确定性,所提出的新型双幂次趋近律能够保证系统状态的快速趋近并抑制控制器的高频抖动。采用Lyapunov稳定性理论证明闭环控制系统的稳定性,并通过数值仿真实验验证所提出的控制方法的有效性。     

Performance assessment of thermal power plant load control system based on covariance index

This paper proposes a novel method of performance assessment for load control system of thermal power unit. Load control system is the most important multivariable control system. It is necessary to monitor and evaluate the performance of it. The performance evaluation index system based on covariance is defined, and the performance evaluation rules are given. In MATLAB, the double input and double output object model of the load control system is established, and the dynamic characteristics of the load control system are analyzed under the BF and TF mode. The simulation data, which is based on the parameters retuning, is used as the “benchmark data”, and the simulation data of different controllers are collected as “monitoring data”. For most of the time, the thermal power plant is under the coordinated control mode, and the principle and strategy of the two coordinated control are analyzed, and the engineering realization scheme is given. Operation data in different time periods of two different thermal power plants was acquisition and preprocessing respectively. The principle of selecting “benchmark data” is the minimum of pressure parameter. Two data segments were selected as “benchmark data”, performance assessment and analysis was carried on the data from other time periods. The results show that the validity and reliability of the method based on the evaluation index. In short, the data of the simulation and the load control system of power plant are used to demonstrate the effectiveness of the method.     

一种新型滑模控制双幂次趋近律

针对滑模控制中传统趋近律存在收敛速度慢、时间长和抖振严重等不足,提出一种利用双幂次趋近律提高系统状态收敛速度的设计方案.该双幂次趋近律无论在远离滑动模态还是在接近滑动模态的空间内均具有快速收敛能力.理论分析表明,该双幂次趋近律具有二阶滑模特性,当系统存在不确定性时,系统状态及其导数可以快速收敛到平衡零点的邻域内.仿真结果表明,双幂次趋近律与传统幂次趋近律、指数趋近律、快速幂次趋近律相比,具有更快的收敛速度和更好的运动品质.     

Time-varying sliding mode control for a class of uncertain MIMO nonlinear system subject to control input constraint

To solve the regulator problem of a class of uncertain MIMO nonlinear systems subject to control input constraint, three types of time-varying sliding mode control laws are proposed. The sliding surfaces pass the initial value of the system at the initial time, and are shifted/rotated towards the predetermined ones. The controller parameters are optimized by genetic algorithm (GA). Lyapunov method is adopted to prove the stability and robustness to the parameter uncertainties and external disturbance. By me...     

显式抑制测量误差的改进滑模控制

反馈控制系统中模型不确定性和测量误差的同时出现, 给高精度控制器的设计带来挑战. 经典滑模控制能抵抗一定程度的模型不确定性和输入干扰, 但引入的高增益使得其性能对测量噪声极为敏感, 也容易引起系统强烈抖振. 为此, 本文针对一种典型的角度和角速率测量分别包含高频和低频测量误差条件, 提出了一种改进的基于趋近律的角度跟踪控制方案. 本方案采用低通滤波器来应对高频测量噪声, 同时采用一种新颖的基于模型的测量误差估计器, 来补偿低频测量漂移. 采用Quanser Aero平台进行两自由度角轨迹跟踪控制仿真和实验验证, 并与自抗扰控制等几种典型鲁棒控制方案进行了全面对比, 证实了本文方案性能上的优越性和调参的便捷性.     

柔性自激异步发电系统反演自适应滑模控制

为抑制宽转速范围条件下柔性自激异步发电系统(FS–CAGS)电压定向谐波干扰,提高FS–CAGS鲁棒稳定控制能力,实现功率快速跟踪控制,采用扩展卡尔曼滤波EKF电压定向与反演自适应滑模控制相结合的方法,提出一种EKF电压定向反演自适应滑模直接功率控制新方法.军用底盘集成式直流微电网中FS–CAGS控制仿真实验结果表明,在负载冲击扰动和宽转速突变条件下,相对于传统直接电压定向精确反馈线性化鲁棒控制方法,新控制方法可加快直流输出电压稳定速度,减小电压超调,提高功率跟踪速度, FS–CAGS电流谐波抑制和鲁棒稳定能力得到加强.     

基于主动滑模控制实现一类含有非匹配不确定混沌系统的同步

讨论了一类非匹配不确定混沌系统的同步问题.基于主动控制思想,提出了一种主动滑模控制策略,使得从任意初始条件出发的不确定混沌系统在有限时间内到达滑模面.利用线性矩阵不等式(LMI)技术设计了一个鲁棒稳定的滑模面,以降低非匹配不确定对系统的影响.给出了线性矩阵不等式形式的稳定滑模面存在的充分条件.通过对Rssler系统的同步仿真,验证了该方法的可行性.     

观测器基于自适应滑模控制的半马尔科夫跳变系统

在许多工业系统中都存在时滞的现象,会使得系统控制性能降低,影响系统的稳定,在实际系统中,滑模依赖时变时滞更值得研究,而滑模控制对于外界干扰,非线性和参数不确定具有很好的鲁棒性,并且控制结构简单,视如上情况,针对观测器基于滑模控制的Markov切换系统,设计积分滑模面,并通过估计变量得到误差系统,通过解线性矩阵不等式使得...     

Sliding mode control of boost and buck‐boost power converters using the dynamic sliding manifold

Non‐minimum phase tracking control is studied for boost and buck‐boost power converters. A sliding mode control algorithm is developed to track directly a causal voltage tracking profile given by an exogenous system. The approximate causal output non‐minimum phase asymptotic tracking in non‐linear boost and buck‐boost power converters is addressed via sliding mode control using a dynamic sliding manifold (DSM). Use of DSM allows the stabilization of the internal dynamics when the output tracking error tends asymptotically to zero in the sliding mode. The sliding mode controller with DSM links features of conventional sliding mode control (insensitivity to matched non‐linearities and disturbances) and a conventional dynamic compensator (accommodation to unmatched disturbances). Numerical examples demonstrate the effectiveness of the sliding mode controller even for a known time‐varying load. Copyright © 2003 John Wiley & Sons, Ltd.     

Application of type-2 fuzzy logic system for load frequency control using feedback error learning approaches

In this paper, the type-2 fuzzy logic system (T2FLS) controller using the feedback error learning (FEL) strategy has been proposed for load frequency control (LFC) in the restructure power system. The original FEL strategy consists of an intelligent feedforward controller (INFC) (i.e. artificial neural network (ANN)) and the conventional feedback controller (CFC). The CFC acting as a general feedback controller to guarantee the stability of the system plays a crucial role in the transient state. The INFC is adopted in forward path to take over the control problem in the steady state. In this work, to improve the performance of the FEL strategy, the T2FLS is adopted instead of ANN in the INFC part due to its ability to model uncertainties, which may exist in the rules and measured data of sensors more effectively. The proposed FEL controller has been compared with a type-1 fuzzy logic system (T1FLS) – based FEL controller and the proportional, integral and derivative (PID) controller to highlight the effectiveness of the proposed method.     

Output feedback sliding mode control for a linear multi-compartment lung mechanics system

In this paper, we develop a sliding mode control architecture to control lung volume and minute ventilation in the presence of modelling system uncertainties. Since the applied input pressure to the lungs is, in general, nonnegative and cannot be arbitrarily large, as not to damage the lungs, a sliding mode control with bounded nonnegative control inputs is proposed. The controller only uses output information (i.e., the total volume of the lungs) and automatically adjusts the applied input pressure so that the system is able to track a given reference signal in the presence of parameter uncertainty (i.e., modelling uncertainty of the lung resistances and lung compliances) and system disturbances. Controllers for both matched and unmatched uncertainties are presented. Specifically, a Lyapunov-based approach is presented for the stability analysis of the system and the proposed control framework is applied to a two-compartment lung model to show the efficacy of the proposed control method.     

Adaptive neural network sliding mode control of a nonlinear two-degrees-of-freedom helicopter system

The helicopter can play an important role in military and civil applications owing to its super maneuvering ability, which is closely related to its control system. To improve control performance, this study presents an adaptive sliding mode control strategy merging an adaptive neural network for a nonlinear two-degrees-of-freedom (2-DOF) helicopter system. By setting up the Lyapunov function, the asymptotic stability of the closed-loop system is guaranteed, the astringency of the neural network weight renewal course is pledged, and the asymptotic attitude adjustment and trajectory tracking for the desired set point are realized. The availability of the adaptive radial basis function sliding mode control is finally verified via the simulation and real implementation on a nonlinear 2-DOF helicopter platform.     

A novel hybrid gravitational search and pattern search algorithm for load frequency control of nonlinear power system

In this paper, a hybrid gravitational search algorithm (GSA) and pattern search (PS) technique is proposed for load frequency control (LFC) of multi-area power system. Initially, various conventional error criterions are considered, the PI controller parameters for a two-area power system are optimized employing GSA and the effect of objective function on system performance is analyzed. Then GSA control parameters are tuned by carrying out multiple runs of algorithm for each control parameter variation. After that PS is employed to fine tune the best solution provided by GSA. Further, modifications in the objective function and controller structure are introduced and the controller parameters are optimized employing the proposed hybrid GSA and PS (hGSA-PS) approach. The superiority of the proposed approach is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as firefly algorithm (FA), differential evolution (DE), bacteria foraging optimization algorithm (BFOA), particle swarm optimization (PSO), hybrid BFOA-PSO, NSGA-II and genetic algorithm (GA) for the same interconnected power system. Additionally, sensitivity analysis is performed by varying the system parameters and operating load conditions from their nominal values. Also, the proposed approach is extended to two-area reheat thermal power system by considering the physical constraints such as reheat turbine, generation rate constraint (GRC) and governor dead band (GDB) nonlinearity. Finally, to demonstrate the ability of the proposed algorithm to cope with nonlinear and unequal interconnected areas with different controller coefficients, the study is extended to a nonlinear three unequal area power system and the controller parameters of each area are optimized using proposed hGSA-PS technique.     

陀螺仪系统同步控制的参数自适应滑模控制

针对带有内部不确定性及外部扰动的陀螺仪混沌系统的同步问题,提出了一种参数自适应滑模控制方法,并给出参数自适应律.该方法不依赖被控混沌系统的数学模型,可以快速跟踪主混沌系统.时域及复频域理论分析表明,由参数自适应滑模控制器组成的闭环控制系统是全局渐近稳定的,而且参数自适应滑模控制器具有良好的抗扰动鲁棒性.仿真结果表明该控制方法计算量小、响应速度快、控制精度高、抗扰动鲁棒性强,在非线性不确定系统控制领域具有广泛的应用价值.     

Fixed frequency sliding mode control of renewable energy resources in DC micro grid

The rising cost of fossil fuels, their high depleting rate and issues regarding environmental pollution have brought the attention of the researchers towards renewable energy technologies. Different renewable energy resources like wind turbines, fuel cells and solar cells are connected to DC micro grid through controllable power electronic converters. In presence of these diverse generation units, robust controllers are required to ensure good power quality and to regulate grid voltage. This paper presents a sliding mode control based methodology to address the above mentioned challenges. The proposed technique keeps the switching frequency constant so that electromagnetic compatibility (EMC) issues can be solved with conventional filter design. Parallel operation of converter in DC micro gird is considered. Chattering reduction and power quality improvement by harmonic cancellation is proposed. A scaled down hardware for unregulated 11.5 V to 17.5 V input and 24V output is designed and tested. The experimental results show good performance of the controller under different loads and uncertain input voltage conditions. Moreover, the results show the robustness of the closed loop system to sudden variations in load conditions. Furthermore, a significant improvement in power quality is achieved by harmonic cancellation of chattering in the output of the converters.