Determination of AVR System PID Controller Parameters Using Improved Variants of Reptile Search Algorithm and a Novel Objective Function

Two novel improved variants of reptile search algorithm(RSA),RSA with opposition-based learning(ORSA)and hybrid ORSA with pattern search(ORSAPS),are proposed to determine the proportional,integral,and derivative(PID)controller parameters of an automatic voltage regulator(AVR)system using a novel objective function with augmented flexibility.In the proposed algorithms,the opposition-based learning technique improves the global search abilities of the original RSA algorithm,while the hybridization with the pattern search(PS)algorithm improves the local search abilities.Both algorithms are compared with the original RSA algorithm and have shown to be highly effective algorithms for tuning the PID controller parameters of an AVR system by getting superior results.Several analyses such as transient,stability,robustness,disturbance rejection,and trajectory tracking are conducted to test the performance of the proposed algorithms,which have validated the good promise of the proposed methods for controller designs.The performances of the proposed design approaches are also compared with the previously reported PID controller parameter tuning approaches to assess their success.It is shown that both proposed approaches obtain excellent and robust results among all compared ones.That is,with the adjustment of the weight factorα,which is introduced by the proposed objective function,for a system with high bandwitdh(α=1),the proposed ORSAPS-PID system has 2.08%more bandwidth than the proposed ORSA-PID system and 5.1%faster than the fastest algorithm from the literature.On the other hand,for a system where high phase and gain margins are desired(α=10),the proposed ORSA-PID system has 0.53%more phase margin and 2.18%more gain margin than the proposed ORSAPS-PID system and has 0.71%more phase margin and 2.25%more gain margin than the best performing algorithm from the literature.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

A fault-tolerant control method for distributed flight control system facing wing damage

With the strong battlefield application environment of the next generation fighter,based on the design of distributed vehicle management system,a fault diagnosis and fault-tolerant control(FTC)method for wing surface damage is proposed in this paper.Aiming at three kinds of wing damage modes,this paper proposes a diagnosis method based on the fault decision tree and forms a fault decision tree for wing damage from the aspects of sample database construction,feature parameter extraction,and fault decision tree construction.Based on the fault diagnosis results,the longitudinal control law based on dynamic inverse and the lateral-directional robust control laws based on linear quadratic regulator(LQR)are proposed.From the simulation examples,the fault diagnosis algorithm based on the decision tree can complete the judgment of three wing surface damage modes within 2 ms,and the FTC law can make the fighter quickly return to a stable flight state after a short transient of 1 s,which achieves the fault-tolerant goal.

Application of PID Controller Based on BP Neural Network in Export Steam’s Temperature Control System

By combining the Back-Propagation （BP） neural network with conventional proportional Integral Derivative （PID） controller, a new temperature control strategy of the export steam in supercritical electric power plant is put forward. This scheme can effectively overcome the large time delay, inertia of the export steam and the influencee of object in varying operational parameters. Thus excellent control quality is obtaitud. The present paper describes the development and application of neural network based controller to control the temperature of the boiler＇s export steam. Through simulation in various situations, it validates that the control quality of this control system is apparently superior to the conventional PID control system.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.

Application of Neural network PID Controller in Constant Temper-ature and Constant Liquid-level System

Guided by the principle of neural network, an intelligent PID controller based on neural network is devised and applied to control of constant temperature and constant liquidlevel system. The experiment results show that this controller has high accuracy and strong robustness and good characters.

基于单片机和PID算法的温度智能控制系统设计

为提高温度控制的智能化水平,设计一种智能温度控制系统。该系统以STC89C52单片机为控制器,采用PID算法控制温度,具有语音播报和手机远程控制等功能。采用DS18B20温度传感器采集环境温度;设计LCD12864显示电路实时显示当前温度、温度上下限以及温度状态;设计WT588D语音提醒电路,当测量温度小于下限或大于上限时发出语音提醒;设计按键电路实现温度上下限值的设定;设计蓝牙通信电路,与手机APP通信,实现远程控制;采用PID算法输出控制量,控制固态继电器驱动加热或降温装置,实现温度控制。其次,对温度控制系统的硬件和软件进行设计,并制作实物进行运行测试。实验结果表明,所设计的温度控制系统能够很好地实现温度控制,从而达到预期效果,且操作方便、成本低,具有较强的应用价值。

基于变论域模糊PID的金属热处理过程温度控制方法

为高效且安全地提取金属合金内的可用材质并分析其性能,利用变论域模糊PID技术,实现对热处理过程的温度控制。设定在金属规则状态不变的情况下,论域会随着偏差的缩减出现伸缩,即需要增添新的规则。若偏差率能够支持模糊量化取整,控制器的伸缩因子可能会陷入无法取值的情况。此时,通过二元函数分片双一次插值法计算伸缩因子,在临近分档之间填充新规则,确保伸缩因子取值的连续性。然后,在模糊PID控制过程中加入变论域,依靠控制器实现对金属热处理过程温度的控制。根据实验验证情况可知:该方法有效提高了控制效果,在应用该方法后,缩短了温度控制时间,在100s内就可以是加热温度到达拟定值。

基于PID的电阻炉温度控制仿真

电阻炉是熔炼金属、玻璃成型及陶瓷制造等工业生产中的重要加热设备之一,主要利用电流使炉内电热元件进行发热,在工业背景下,电阻炉温度的准确控制对于生产过程的稳定性和产品质量至关重要。如果温度控制不足够精确,可能会导致材料变质、能源浪费和生产延误,造成一定的经济损失。为了优化这些过程并确保产品质量,精确的温度控制是必不可少的。在分析PID控制器基本原理以及特点的基础上,探讨基于PID的电阻炉温度控制系统设计,并通过Matlab的强大工具和模拟环境,模拟电阻炉温度控制代码,能够帮助进一步理解和改进电阻炉温度控制系统,使电阻炉温度控制更加精准,以满足不断变化的工业需求,生产出更高质量的工业制品,推动制造业的现代化发展。

基于位置式PID的水暖床垫温度控制系统设计

温度控制在生产生活中发挥着举足轻重的作用。位式控制算法在调节具有滞后性的水暖床垫温度控制系统时容易导致温度在目标值上下波动,控制效果不理想。为了解决此问题,设计了一种基于位置式PID的水暖床垫温度控制系统,系统以51内核的微处理器为核心控制器、以负温度系数热敏电阻(Negative Temperature Coefficient,NTC)为温度传感器、以PTC为加热器、以直流电机作为循环水泵。经实际测试结果表明,该系统运行稳定,控温精度在±0.5℃以内,达到了理想的温度控制效果。

应用模糊PID自修正的电镀槽液温度控制方法

电镀槽液温度自动控制过程属于典型的混沌过程,在温度采集的过程中存在明显的非线性波动。典型的比例-积分-微分(PID)控制算法在这种混沌特性与非线性特性干扰下,存在控制精度较低、稳定性和鲁棒性较差等问题。此外,为解决非线性问题,PID算法需要循环迭代计算,存在控制时滞问题。以模糊控制为基础,提出了基于模糊PID的电镀槽液温度自动控制方法。该方法先设计温度数据采集结构,并将移动平均滤波、温度修正算法引入到采用的数据采集结构中,完成电镀槽液的实时温度数据采集。然后将采集到的温度数据作为构建的模糊PID控制器的输入。利用模糊控制规则引入修正因子,实现电镀槽液温度的自动控制。考虑到电镀槽液的时滞特性,在控制器中加入粗糙预估参考模型,对该特性加以抑制,提升控制性能。最后应用实验证明了所提方法的先进性。实验结果表明:所提方法具有较高的控制精度和效率,能够有效降低超调量和波动,应用效果较好。

基于模糊PID控制算法的温度控制系统

本文指出现代的工业生产环境下,由于控制目标的复杂性、动态特征和不可预测的特点,使得传统的PID控制无法满足控制要求。在使用PID技术来调节电锅的温度控制的背景下,将模糊控制与传统控制技术相结合,通过设计模糊控制器的结构、制定模糊控制规则,对PID的参数进行自动调整。结果表明模糊PID控制算法的控制优势显著提升。

基于反向传播神经网络PID的高功率微波炉温度控制

针对现有10 kW高功率工业微波炉,采用继电器作为控制执行器,在使用传统控制方法加热时,温度存在较大超调和明显振荡,系统温度稳定性较低,为解决上述问题将反向传播神经网络PID(BPNNPID)控制引入到该装置微波加热温度控制中,并以自来水为加热对象进行仿真对比与实验验证。首先,利用现有输入输出实验数据,建立工业微波炉温度控制模型;其次,运用MATLAB/SIMULINK搭建高功率工业微波炉温度控制系统并进行仿真对比实验;最后,实验验证BPNNPID控制方法在加热5 kg自来水时工业微波炉的温度控制性能,实验结果表明,较常规PID、模糊PID控制,该方法在微波加热过程中对媒质温度控制超调更小且未发生明显温度振荡,有效改善了高功率工业微波炉工作时的系统温度稳定性,有助于提高产品质量和安全性能。

基于STM32的密炼机自整定PID温控系统设计

针对密炼机温度控制系统中人工整定PID带来的系统响应不及时、误差大等问题,该文设计了一种基于STM32的自整定PID温度控制系统。对于电动阀只能单极性调节问题,通过设置适当的工艺点来控制继电输出。为提高震荡曲线的辨识,采用参数归一化方法计算震荡曲线的临界增益。考虑密炼机的工作环境和系统响应曲线的频率特性,加入带有临界滞环控制的继电控制方法,提高了特征参数的精确性,更好地整定了PID参数。应用结果表明,基于STM32的PID整定温度控制系统能够将温度误差控制在1℃左右,且控制时间相比于人工PID控制系统提高了30%,极大地满足了密炼机的温度控制要求,具有良好的实用价值。

Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.

Multivariable temperature measurement and control system of large-scaled vertical quench furnace based on temperature field

A temperature control system of 31m vertical forced air-circulation quench furnace is proposed, which is a kind of equipment critical for thermal treatment of aluminum alloy components that are widely used in aerospace industry. For the effective operation of the furnace, it is essential to analyze the radial temperature distribution of the furnace. A set of thermodynamic balance equations modeling is established firsdy. By utilizing the numerical analysis result to modify the temperature measurements, the control accuracy and precision of the temperature are truly guaranteed. Furthermore, the multivariable decoupling self-learning PID control algorithm based on the characteristics of strong coupling between the multi-zones in the large-scaled furnace is implemented to ensure the true homogeneity of the axial temperature distribution. Finally, the redundant structure composed of industrial control computers and touch panels leads to great improvement of system reliability.

基于模糊PID算法的食用菌大棚温度控制系统研究

食用菌大棚温度控制系统是一个具有时滞性的复杂系统,传统的开关量或常规PID控制很难满足设计要求。该研究设计一种基于STM32F103CRT6单片机为控制核心,加入模糊自适应PID控制算法,利用DHT11温湿度传感器进行温度实时采集,单片机运算处理,光耦固态继电器驱动电路对热风机进行控制,从而达到温度调节的目的。并在MATLAB/simulink环境下建立常规PID控制和模糊自适应PID控制的仿真模型,通过仿真结果,对比验证了该方法比常规PID控制方法具有低超调量和调节时间短等较好的控制效果。

Distributed Periodic Event-Triggered Optimal Control of DC Microgrids Based on Virtual Incremental Cost

This article presents a distributed periodic eventtriggered(PET)optimal control scheme to achieve generation cost minimization and average bus voltage regulation in DC microgrids.In order to accommodate the generation constraints of the distributed generators(DGs),a virtual incremental cost is firstly designed,based on which an optimality condition is derived to facilitate the control design.To meet the discrete-time(DT)nature of modern control systems,the optimal controller is directly developed in the DT domain.Afterward,to reduce the communication requirement among the controllers,a distributed event-triggered mechanism is introduced for the DT optimal controller.The event-triggered condition is detected periodically and therefore naturally avoids the Zeno phenomenon.The closed-loop system stability is proved by the Lyapunov synthesis for switched systems.The generation cost minimization and average bus voltage regulation are obtained at the equilibrium point.Finally,switch-level microgrid simulations validate the performance of the proposed optimal controller.

改进麻雀算法在模糊PID温度控制系统的应用

为满足标准金属量器检定的温度控制要求,本文提出了改进的麻雀搜索算法。利用改进的Sine混沌映射初始化种群和萤火虫干扰策略,避免麻雀搜索算法过早陷入局部最优的状况,提高了算法的收敛速度;建立基于模糊PID控制器的温度控制系统的数学模型,并使用改进后的算法优化模糊PID控制器参数。结果表明:利用该算法优化模糊PID控制器,各方面性能都优于其他算法。

Robust Non-fragile PID Controller Design for the Stroke Regulation of Metering Pumps

This job focuses on the stroke regulation of a class of high-precision metering pumps.A parametertuning method of robust non-fragile PID（proportional-integral-derivative）controllers is proposed with the assumption that a PID controller has additive gain perturbations.An H-infinite robust PID controller can be obtained by solving a linear matrix inequality.This approach can guarantee that the closed-loop control systems is asymptotically stable and the H-infinite norm of the transfer function from the disturbance to the output of a controlled system is less than a given constant to attenuate disturbances.The simulation case shows that the control performance of the proposed strategy is significantly better than the traditional PID approach in the situation with perturbations of controller parameters.