Simulation of Greenhouse Heating System Using Fuzzy Smith Cascade Compound Control

Aiming at characteristic of time delay, time-varying parameters and much disturb in glass greenhouse heating system, fuzzy smith cascade compound control policy based on typical PID cascade compound control policy is proposed. Simulation results show that it is effective to overcome the influence of time delay on stability of control system and the system possesses strong robust and good dynamic performance..

Research on fuzzy self-adaptive PI-Smith control in long time-delay system

The long time-delay often exists in industrial process. In order to overcome the big overshoot and long regulating time of the long time-delay system control, a new fuzzy self-adaptive PI-Smith control method is proposed. This method combines the Smith predictive control with fuzzy self-adaptive proportional-integral （PI） control. The traditional proportional-integral-derivative （PID） controller in Smith predictive control is replaced by fuzzy PI controller which utilizes the principle of fuzzy control to tune parameters of PI controller on-line. The results of simulation for electric furnace show that the method has the advantages of shortening regulating time, no overshoot, no steady-state error, excellent control accuracy, and good adaptive ability to the change of system model.

Temperature Control Based on Fuzzy Logic Two-degree-of-freedom Smith Internal Model

According to the characteristics of the large time delay,nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor,a two-degree-of-freedom Smith internal model controller based on fuzzy control is proposed.Firstly,the mathematical model of the temperature control system is established by using the step response method,and then the two-degree-of-freedom Smith internal model controller is designed,and the good tracking performance and disturbance suppression performance can be obtained by designing the set value tracking controller and interference rejection capability.Secondly,the fuzzy control algorithm is used to realize the on-line tuning of the control parameters of the two-degree-of-freedom Smith internal model algorithm.The simulation results show that,compared with the traditional internal model control,fuzzy internal model PID control and two-degree-of-freedom Smith internal model control,the algorithm proposed in this paper improves the influence of lag time on the control system,realizes the separation control of set point tracking and anti-jamming performance and the self-tuning of control parameters,and improves the control performance of the system.

Monitor automatic gauge control strategy with a Smith predictor for steel strip rolling

The simplified transfer function diagram block for a monitor automatic gauge control （Mon-AGC） system of strip steel rolling process was investigated. The new notion of strip sample length was given. In this way, the delay time varying with the rolling speed was evaded. After a Smith predictor was used to monitor the AGC system, the control laws were deduced for both proportional and integral regulators. The control strategies showed that by choosing the controller parameter P=∞ for both control algo- rithms each regulator could compensate the whole strip gage error in the first control step. The result shows that the integral algo- rithm is more controllable for the system regulating process and has a better steady-state precision than the proportional regulator. Compared with the traditional control strategy, the new control laws have a faster response speed and a hieher steadv-state precision.

基于BP神经网络的Smith-Fuzzy-PID算法在阀门定位中的应用研究

为解决气动调节阀控制过程中出现的超调大、精度低等问题,本文采用BP神经网络整定出较优的PID(Proportional Integral Derivative)控制参数,对Smith预估控制器以及模糊控制器进行设计,实现了基于BP神经网络的Smith-Fuzzy-PID控制方法。搭建了实验平台,通过阶跃响应实验来对控制方法进行验证,验证结果表明,提出的方法调节过程无超调,调节时间仅为1.9 s,定位精度在±0.5%以内,有效提高了系统的稳定性,实现了气动调节阀的快速精准定位。

Application of Smith Predictor Based on Single Neural Network in Cold Rolling Shape Control

Flatness is one of the most important criterion factors to evaluate the quality of the steel strip. To improve the strip＇ s flatness quality, the most frequently used methodology is to employ the closed-loop automatic shape control system. However, in the shape control system, the shape-meter is always installed at the down way of the exit of the cold rolling mill and can not sense the changes of the strip flatness in the rolling gap directly. This kind of installation results in the delay of the feedback in the control system. Therefore, the stability and response performance of the system are strongly affected by the delay. At present, there is still no mature way to design controllers for systems with time delay. Although the conventional PID controller used in most practical applications has the capability to compensate the delay, the effect of the compensation is limited, especially for the systems with long time delay. Smith predictor, as a compensator for solving this problem, is now widely used in industry systems. However, the request of highly precise model of the system and the poor adaptive performance to the changes of related parameters limit the application of the Smith predictor in practice. In order to overcome the drawbacks of the Smith predictor, a new Smith predictor based on single neural network PID （SNN-PID） is proposed. Because the single neural network is employed into the Smith predictor to improve the controller＇s self-adaptability, the adaptive capability to the varying parameters of the system is improved. Meanwhile, for the purpose of solving the problems such as time-consuming and complicated calculation of the neural networks in real time, the learning coefficient of neural network is divided into several stages as usually done in expert control system. Therefore, the control system can obtain fast response due to the improved calculation speed of the neural networks. In order to validate the performance of the proposed controller, the experiment is conducted on the shape control system in a 300 mm four-high reversing cold rolling mill. The experimental results show that the SNN-PID with Smith predictor controller can effectively compensate the delay effects and achieve better control performance than the conventional PID controller.

基于Smith模糊PID控制的固体电蓄热供热温控系统研究

固体电蓄热供热的温控系统存在滞后性,导致系统响应缓慢,抗干扰能力和能源利用率大大降低。为了解决这一问题,以某高校的固体储能供热示范工程为基础,提出了采用基于Smith模糊PID控制的方法对温控系统进行控制。实验结果显示,该温控系统的控温精度可达到±0.8℃,调节时间缩短了5 min。分析结果表明,与传统的PID控制方法相比,这种控制方法能够更有效地减小控制过程中的扰动影响,显著缩短调节时间,使系统更快进入稳定状态,有效克服了传统大滞后系统对稳定性的不利影响,温控效果优于传统PID控制。

基于Smith预估补偿的加热炉炉温控制策略

加热炉炉温具有大时滞、时变、非线性和干扰因素多等特点,易造成炉温波动频繁、偏差较大。针对加热炉炉温特点,提出基于Smith预估补偿的炉温控制策略。借助Matlab仿真软件对加热炉炉温控制系统进行辨识,将预估补偿控制策略应用到辨识系统中,验证了控制策略的有效性。仿真结果表明,该控制策略的动态性能指标较佳,可有效改善炉温控制系统的稳定性和抗干扰性。

基于Smith预估器的模糊PID调车自动驾驶系统速度控制研究

针对铁路站场调车作业的复杂性,研发基于调车的自动驾驶系统可降低劳动强度并提高车站作业效率,而速度控制策略是系统的重点和难点。根据调车牵引控制系统和制动控制系统特性,建立传递函数模型,并对模型参数的不稳定因素进行分析;利用Smith预估方法处理时滞系统的优势,结合模糊PID算法,设计基于Smith预估器的模糊PID控制器(简称新型控制器);通过模拟模型参数不稳定,分别使用阶跃响应曲线和司机实操速度曲线进行仿真,对比传统的PID控制器、模糊PID控制器与新型控制器的控制效果。结果表明:新型控制器适应能力更强,速度跟踪效果和停车精度都更高。

高速永磁同步电机解耦控制——低载波比数字延时与Smith预估控制

永磁同步电机(PMSM)运行在高速工况时,由于逆变器的开关频率受限使得载波比较低,会出现数字延时加剧的问题,直接影响了系统的控制性能,甚至造成系统失稳。针对低载波比工况下的数字延时问题,首先对数字延时环节进行精确的复矢量建模,并基于转速及电流环带宽的根轨迹、闭环零极点图及波特图分析数字延时对系统性能的影响,并给出考虑延时后系统的临界失稳转速。结合复矢量解耦策略,提出一种改进的基于Smith预估控制的解耦延时补偿电流控制策略,能够避免高速低载波比工况下系统失稳的问题,提高了电流环的稳定性,同时具有较好动态响应能力和解耦性能。采用Simulink仿真对比验证了所提的解耦延时补偿控制策略的有效性。

Smith预估补偿与积分分离PID在供热控制系统中的应用

针对供热控制系统时延性较大、传统PID策略控制精度不高、易产生超调与静态误差等问题,提出了一种史密斯(Smith)预估补偿与积分分离PID相结合的供热系统控制策略。首先,设计了供水温度控制系统的Smith预估补偿器,以降低热惰性因素对控制性能的影响;其次,给出了积分分离策略,用于消除静态误差;最后,将Smith预估补偿器与积分分离PID在PLC控制系统中进行部署调试,并进行实践研究。实践证明,Smith预估补偿与积分分离PID相结合的控制策略能最大限度地减弱大时延对供热系统的影响,有效提升系统的控制精度与控制性能。

Unified Smith Predictor Based H_∞ Wide-Area Damping Controller to Improve the Control Resiliency to Communication Failure

Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines.Use of wide-area signal is more effective than the local area signal in damping out the inter-area oscillations.Wide area measurement system(WAMS)is convenient to transmit the wide area signal through the communication channel to the remote location.Communication failure is one of the disastrous phenomena in a communication channel.In this paper,a dual input single output(DISO)Hm controller is designed to build the control resiliency by employing two highest observability ranking wide area signals with respect to the critical damping inter-area mode.The proposed controller can provide sufficient damping to the system and also the system remains stabilized if one of the wide-area signals is lost.The time delay is an unwanted phenomenon that degrades the performance of the controllers.The unified Smith predictor approach is used to design a Hm controller to handle the time delay.Kundur's two-area and IEEE-39 bus test systems are considered to verify the effectiveness of the proposed controller.From the simulation results,it is verified that,the proposed controller provides excellent damping performance at normal communication and improves the controller resiliency to counteract the communication failure.

基于抗扰动Smith预估补偿的磨煤机出口风粉温度优化控制

“双碳”背景下,作为高能耗高排放的火电机组,其燃烧性能直接影响发电效率和碳排放量。锅炉燃烧优化控制对运行优化和灵活调峰是有重要意义。电站锅炉磨煤机的出口风粉温度控制面临大延迟、多干扰问题,对燃煤机组安全稳定运行具有重要影响。基于Smith预估控制器,在补偿回路中增设反馈环节,实现了高效抗干扰,提升磨煤机风粉温度控制性能。通过Taylor级数展开和待定系数法求取模型近似转换参数,获得一阶惯性纯滞后模型,进而设计抗扰动型Smith预估补偿控制器。通过与单回路PID控制试验对比,发现Smith预估补偿控制算法可有效补偿控制对象的纯延迟滞后环节,单位阶跃响应超调量降低36.5%,调节时间缩短65.8%。相比经典Smith预估补偿控制算法,抗扰动Smith预估补偿控制算法可提高控制算法的抗扰动性能,并显著改善控制对象的动态特性,单位阶跃响应超调量减小44.7%,调节时间缩短15.7%。同时,实现了扰动最大偏差和收敛时间的降低。最后,在某660 MW超临界一次再热燃煤机组上应用该方法,实现了磨煤机出口风粉温度实际值对设定值的平稳跟踪,进一步验证了该方法的有效性。

Smith预测器在热工自动控制系统中的应用分析

现代锅炉过热器需要在高温高压的环境中工作,锅炉在出口位置过热或者蒸汽温度较高对电厂安全运行具有重要影响。针对延迟、惯性、时变性等问题,火电厂一般选择常规的过热气温控制系统对温度进行控制,尤其是PID控制方式,但是此类控制方式容易造成鲁棒性,整体控制效果不好,容易出现各类问题。基于此,在热工自动控制系统中应用Smith预测器,可以有效解决各种问题,确保热工系统可以实现自动控制的目标。

基于Smith预估模糊PID的浮选液位控制系统设计

浮选机内液位高低影响着浮选效果和生产稳定性,针对煤泥浮选中浮选机液位对浮选结果产生的影响,结合浮选液位控制系统的特点及其性能要求,采用了一种将Smith预估控制、模糊控制、PID控制结合的液位控制系统,并利用MATLAB中Simulink模块设计浮选液位仿真模型,进行仿真分析,同时改变液位以测试系统的稳定性。通过对传统PID、模糊PID及Smith预估模糊PID控制算法进行比较可知,液位控制系统采用Smith预估模糊PID算法,其控制效果由于传统PID和模糊PID控制,调节时间更短,稳定性更强,提高了浮选机液位的稳定性,能更好地满足浮选过程对液位的要求。

Smith预估模糊PID控制算法及其在粉末定量称重中的应用

针对上海科源电子科技有限公司研发的定量称重系统(由高精度抖粉装置与万分之一天平组成),在工作中因粉末密度、粉末流动性、颗粒大小、湿度、天平延时等因素造成的非线性和滞后等问题,采用Smith预估模糊PID控制器优化控制方法。首先通过理论分析,得出系统的传递函数,再构建Smith预估的模糊PID控制器,以适应系统的非线性、滞后等特性,最后将此算法代入MATLAB进行仿真并于实际系统中进行1 g定量抖粉实验。Smith预估模糊PID控制算法和传统PID算法的标准差分别为0.0020和0.0042,表明Smith预估模糊PID控制算法在实际环境中稳定性更好,能有效减小系统的称重误差。

基于深度强化学习改进的Smith预估器温度控制

针对牛粪发酵过程具有惯性大、时滞性、参数变化非线性的特点,提出了一种基于深度确定性策略梯度(DDPG)改进Smith模糊PID控制器的温度控制方法。首先,针对传统模糊PID不能对时滞系统有效控制的问题,建立Smith预估模糊PID控制器。其次,使用DDPG算法改进温度控制器,对设计的智能体进行离线训练。最后,通过仿真对所设计控制器进行实验验证。实验结果表明:DDPG改进的Smith模糊PID控制器能有效消除时滞对温度控制的影响,减少超调量和误差,且能避免被控对象参数随时间变化产生动态偏离时造成的系统不稳定。

多模型调度Smith预估算法的湿化器管路温控方法

医用湿化器的管路温度控制是一个具有滞后性、大惯性且模型参数随流量变化的非线性变结构系统,难以采用单一结构的控制算法来实现高品质的动态性能控制。针对这一难题,提出基于多模型结构调度的Smith预估控制方法,该方法在流量平衡点处采用模型调度的方法进行控制器设计。实验测试证明多模型调度的史密斯预估算法适用于不同设定温度在不同流量模式下的管路温度控制,提升了控制系统的动态性能和鲁棒性。

基于改进型Smith预估算法的EC值调控系统仿真与分析

为使EC值调控系统更加稳定,响应更快,给实际EC值调控系统提供了一种可行策略.针对EC值调控过程和特点,建立并描述了具有二次混肥特性的EC值调控过程的二阶数学模型,提出一种结合模糊PID和改进型的Smith预估算法对调控过程进行控制,用MATLAB软件中的Simulink模块对PID、模糊PID和改进型Smith控制算法进行阶跃响应跟踪实验和抗干扰测试实验并进行分析.结果表明:1)PID控制时系统超调量为13.068%,到达稳态的响应时间为97 s,加入干扰后恢复稳态的时间为168 s;2)模糊PID控制时系统超调量为6.989%,到达稳态的响应时间为70 s,加入干扰后恢复稳态的时间为138 s;3)改进型Smith控制时系统超调量为0.505%,到达稳态的响应时间为57 s,加入干扰后恢复稳态的时间为104 s.

基于Smith模糊多级积分分离PID的加热盘温度控制

为提高大尺寸晶圆的加工良率,研究采用金属氧化物导电涂层加热的碳化硅晶圆加热盘分区控制方法,提出基于Smith模糊多级积分分离PID的四分区温控系统,解决高精度要求下晶圆加热盘表面温度一致性问题。通过热效应仿真建立系统模型,分析各区域的热量分布,进而基于PLC控制器搭建加热盘温度控制系统,提出便于实际应用的Smith模糊多级积分分离PID算法提高控制精度,在MATLAB中结合系统模型与常规PID算法进行对比,最后基于所建立的加热盘温度控制系统进行实验验证。仿真结果与实验结果均表明,所提控制方法具有更高的控制精度,可以实现加热盘表面温度一致性稳定在0.05℃左右,平均温度稳态误差±0.05℃,控制效果良好。