Assessment of Operational Performance in a Power Generation/Selling Integrated Company Using a Dynamic Proportional Adjustment Coefficient

Currently,the operational performance assessment system in the power market primarily focuses on power generation and electricity retail companies,lacking a system tailored to the operational characteristics of power generation/selling integrated companies.Therefore,this article proposes an assessment index system for assessing the operational performance of a power generation/selling integrated company,encompassing three dimensions:basic capacity,development potential,and external environment.A dynamic proportional adjustment coefficient is designed,along with a subjective and objective weighting model for assessment indexes based on a combined weightingmethod.Subsequently,the operational performance of an integrated company is assessed using extension theory.The results in the case study demonstrate the feasibility and effectiveness of the proposed dynamic proportional adjustment coefficient.

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Fractional Order Proportional Integral Derivative Controller Design and Simulation for Bioengineering Systems

This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.

Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot

A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.

Conventional and Added-Order Proportional Nonlinear Integral Observers

In this paper, a kind of fire new nonlinear integrator and integral action is proposed. Consequently, a conventional Proportional Nonlinear Integral (P_NI) observer and two kinds of added-order P_NI observers are developed to deal with the uncertain nonlinear system. The conditions on the observer gains to ensure the estimated error to be ultimate boundness, which shrinks to zero as the states and control inputs converge to the equilibrium point, are provided. This means that if the observed system is asymptotically stable, the estimated error dynamics is asymptotically stable, too. Moreover, the highlight point of this paper is that the design of nonlinear integral observer is achieved by linear system theory. Simulation results showed that under the normal and perturbed cases, the pure added-order P_NI observer can effectively deal with the uncertain nonlinearities on both the system dynamics and measured outputs.

Analysis and Experimental Study of Proportional-Integral Sliding Mode Control for DC/DC Converter

DC/DC converter using the proportional-integral (PI) sliding mode control (SMC) scheme is investigated, including the selection of the switching surface, the proof of the reaching condition and the existence condition of sliding motion. The sliding regime and the local stability are given. The implementation of the PI SMC is simpler than other SMC schemes and the steady-state error is eliminated. A prototype based on Buck converter is built up. The experimental results show that the dynamic performance and robustness to the parameter variations and external disturbances are improved.

Robust Fractional-Order Proportional-Integral Observer for Synchronization of Chaotic Fractional-Order Systems

In this paper, we propose a robust fractional-order proportional-integral(FOPI) observer for the synchronization of nonlinear fractional-order chaotic systems. The convergence of the observer is proved, and sufficient conditions are derived in terms of linear matrix inequalities(LMIs) approach by using an indirect Lyapunov method. The proposed FOPI observer is robust against Lipschitz additive nonlinear uncertainty. It is also compared to the fractional-order proportional(FOP) observer and its performance is illustrated through simulations done on the fractional-order chaotic Lorenz system.

Current control for a shunt hybrid active power filter using recursive integral PI

This paper presents a current control method for a shunt hybrid active power filter （HAPF） using recursive integral PI algorithm. The method improves the performance of the HAPF system by reducing the influence of detection accuracy, time delay of instruction current calculation and phase displacement of output filter. Fuzzy logic based set-point weighing algorithm is combined in the control scheme to enhance its robustness and anti-interference ability. The proposed algorithm is easy to implement for engineering applications and easy to compute. Experiment results have verified the validity of the proposed controller. Furthermore, the proposed recursive integral PI algorithm can also be applied in the control of periodic current as in AC drivers.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

Fuzzy Self-adaptive Proportional Integration Differential Control for Attitude Stabilization of Quadrotor UAV

The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

基于改进麻雀优化PID的波浪补偿控制方法

随着海上风电“十四五”规划的不断推动,在深远海域对兆瓦级大功率海上风机的需求量随之增加,其规模也在不断扩大。但是,在吊运、安装等海上工作过程中,复杂海浪对船舶产生的持续影响导致风机安装的精度和效率大幅下降,甚至会对人员安全以及财产造成重大损失。在深远海域复杂海况下对工程船舶进行有效的波浪补偿,可提供稳定的作业环境以保证精准高效地完成各项工作,因此,本文提出了一种基于改进麻雀优化PID的波浪补偿控制方法并将其应用于Stewart补偿平台。首先,建立波浪补偿平台动力学以及运动学反解模型,并设计正解模型迭代求解算法。随后,使用PID进行波浪补偿控制,并通过麻雀搜索算法优化参数。接着,采用Circle混沌映射对其进行初始化分布,以解决初始化不均匀的问题;并采用动态自适应加权、柯西突变以及反向学习以提升算法全局寻优能力。最后,生成4~6级海况下的某工程船运动数据作为系统输入,利用MATLAB和Simulink软件平台搭建模型进行补偿控制验证,并在Stewart硬件平台上做补偿试验。结果表明,改进麻雀搜索算法具有较快的收敛速度、较高的精度和更好的寻优能力,优化后的PID控制方法更适合用于复杂海况下波浪补偿平台的控制优化,可为大功率海上风机安装的补偿平台控制系统设计提供参考。

数控压机伺服控制系统复合控制器I-ABC与PID优化

为了提高数控压机伺服控制系统的控制精度,针对伺服控制系统运行控制过程构建数学模型,在人工蜂群算法基础上融入了云分析模型,之后采用改进人工蜂群算法(Improved Artificial Bee Colony,I-ABC)调节比例-积分-微分(Proportional Integral Differential,PID)参数,建立了一种复合控制方法。研究结果表明:以I-ABC进行PID控制时,可以使幅度差降低到0.4%,相位差基本在-0.54°之内,系统加载精度也获得了明显提升,表现出了更优的跟踪性能。以I-ABC进行PID控制时,能够对多余力起到明显抑制作用,响应速度也获得明显提升,可以有效满足系统的准确控制要求。在系统内加入干扰信号,引入I-ABC实施PID调节可以减小系统超调量,还可以获得更短调节时间,使系统获得更强抗干扰性能。

有源电力滤波器补偿的PI解耦控制技术研究

电网中电压和电流波形的失真会产生谐波,导致电网功率因数降低,并影响电力系统的稳定性和可靠性。为了确保电力系统的正常工作,研究了基于有源电力滤波器补偿的比例积分(PI)解耦控制技术。设计了基于二极管钳位式的有源电力滤波器模型。结合基尔霍博电压法,降低控制谐波和解除部分变量耦合。针对设备非线性产生的谐波,分析有源电力滤波器的可逆性,获得输入雅可比矩阵,以实现滤波器旋转坐标的线性化。利用变换矩阵转换转动角速向量,输入谐波的幅度,输出电流取样延迟,完成无差PI解耦控制。试验结果表明,所提技术能够有效解耦滤波器的谐波电流成分,从而补偿电网中的失真电流。该技术可以减少谐波对电力系统的整体影响,保证设备的正常运行。

引入PID反馈的SHAEKF算法估算电池SOC

电池荷电状态(SOC)的估算精度是电动汽车电池组的重要指标。为提升SOC估算精度,在融合Sage-Husa扩展卡尔曼滤波(SHEKF)算法与自适应扩展卡尔曼滤波(AEKF)算法的基础上,增加比例积分微分(PID)反馈环节,形成改进算法。采用粒子群优化(PSO)算法对二阶RC等效电路模型进行参数辨识;用开源电池数据集对模型和算法进行实验和分析。改进的SHAEKF算法在电池动态应力测试(DST)、北京动态应力测试(BJDST)和美国联邦城市驾驶(FUDS)等工况下的平均估计误差都在1%以内,与单纯的融合算法SHAEKF算法相比,最大误差可减小5%。

NUMERICAL ANALYSIS FOR VOLTERRA INTEGRAL EQUATION WITH TWO KINDS OF DELAY

In this article, we study the Volterra integral equations with two kinds of delay that are proportional delay and nonproportional delay. We mainly use Chebyshev spectral collocation method to analyze them. First, we use variable transformation to transform the equation into an new equation which is defined in [-1,1]. Then, with the help of Gronwall inequality and some other lemmas, we provide a rigorous error analysis for the proposed method, which shows that the numerical error decay exponentially in L~∞ and L_(ω~c)~2-norm. In the end, we give numerical test to confirm the conclusion.

基于金豺优化PID的直流电机调速控制系统

针对传统直流(DC)有刷电机调速系统适应性不强、抗干扰能力和稳健性差等缺点,设计了基于金豺算法优化比例-积分-微分(PID)的直流有刷电机控制系统.在建立电机数学模型的基础上,将金豺优化(GJO)算法应用于PID参数整定,实现对电机的控制,并分别与传统试凑法、反向传播(BP)-PID算法和麻雀算法(SSA)-PID进行对比.仿真结果表明:所设计的控制算法在调节时间上减少了12 ms,超调量降低了3.689%,受到干扰后的调节时间减少了17 ms,表现出更快的调节转速、更强的抗干扰能力和更好的稳健性,为直流有刷电机调速控制提供了一种有效的方案.

基于神经网络PI的电静液作动器温度补偿控制方法研究

电静液作动器(Electro-hydrostatic Actuator,EHA)作为一种高性能集成化的动力执行器,广泛应用于航天航空、工业生产和军事领域。在不同油液温度下,液压油的体积弹性模量、黏度等性质会发生变化,从而对EHA的控制精度产生影响。针对此问题,首先建立了EHA数学模型;其次,设计了反向传播(BP)神经网络对比例积分控制器(PI)控制参数进行在线调节,补偿温度变化对跟踪精度的影响;最后,通过实验验证了传统PI控制的EHA跟踪精度与温度变化有着密切关系,并将BPPI控制器与PI控制器进行实验对比。实验结果表明,所设计的BPPI控制器在不同油液温度下平均跟踪误差之间的差值较PI控制器降低80%以上;且在相同温度下,平均跟踪误差较PI控制器降低60%以上。

全桥LLC谐振变换器的积分滑模-PI混合控制

全桥LLC谐振变换器的PI控制存在响应慢和鲁棒性差的问题,滑模控制存在高频抖振问题。针对这些问题,提出了基于模糊规则切换的积分滑模-PI混合控制方法。首先,通过扩展函数描述法建立全桥LLC谐振变换器的大信号模型,利用输入输出反馈线性化设计滑模面;然后,利用扫频法验证PI控制设计的合理性;最后,经多次实验,确定模糊控制的最佳输入和输出隶属度函数,实现在瞬态时由滑模控制起主导作用,在稳态时仅使用PI控制的混合控制方法。在MATLAB/Simulink中进行仿真分析,仿真结果表明,所提控制方法不仅具有滑模控制的瞬态响应快、鲁棒性强的优点,还消除了高频抖振,具有良好的控制效果。

基于自适应PI控制的superbuck变换器

针对superbuck变换器稳定性易受参数偏移和工况变化影响的问题,提出了一种基于瞬态事件捕获的自适应比例积分(PI)控制方法。在该方法中,事件捕获电路通过计算瞬态响应中输出电压的上冲和下冲次数,根据振荡周期把电压响应分类成不同的瞬态事件。更进一步,对不同的瞬态事件进行加权计算得到PI控制器中的增益,从而调节系统带宽和相位裕度。在阻尼网络发生参数偏移的情况下,当参考电压从25 V变化到28 V时,振荡最大幅度从2 V减小到400 mV。100 W superbuck变换器的实验结果表明,自适应PI控制器在参数偏移和工况变化下有效地改善稳定性。

基于比例谐振自耦PI控制的调速系统

针对永磁同步电机调速系统矢量控制过程中,逆变器死区、电机磁场分布谐波以及电流在采样过程中存在误差等因素导致的电机控制效果不佳问题,提出了一种改进型自耦PI控制的双环控制策略。为减小信号的跟踪误差,采用加速度前馈的方式,将增加Levant微分器的自耦PI控制器引入到永磁同步电机速度环中,确保对含有噪声的输入信号准确求导以提高系统的鲁棒性。另外,所提策略在电流环中将增加加速前馈的自耦PI控制结构的比例项和标准谐振器相结合,构成比例谐振自耦PI控制器,使永磁同步电机在电流环的控制中能更好地补偿电流,达到抑制电流谐波的作用。通过分析伺服系统的控制机理,在被控对象PMSM数学模型的基础上,给出了改进型自耦PI控制结构的设计方法。实验结果表明,所提出的控制策略能够减小电机自身参数变化对系统性能的影响并且在低速域具有良好的抑制电流谐波作用,验证了所设计的改进型自耦PI控制器的有效性。