Robust Stability Analysis of Smith Predictor Based Interval Fractional-Order Control Systems:A Case Study in Level Control Process

The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this work.Interval uncertainties are a type of parametric uncertainties that cannot be avoided when modeling real-world plants.Also,in the considered Smith predictor control structure it is supposed that the controller is a fractional-order proportional integral derivative(FOPID)controller.To the best of the authors'knowledge,no method has been developed until now to analyze the robust stability of a Smith predictor based fractional-order control system in the presence of the simultaneous uncertainties in gain,time-constants,and time delay.The three primary contributions of this study are as follows:ⅰ)a set of necessary and sufficient conditions is constructed using a graphical method to examine the robust stability of a Smith predictor-based fractionalorder control system—the proposed method explicitly determines whether or not the FOPID controller can robustly stabilize the Smith predictor-based fractional-order control system;ⅱ)an auxiliary function as a robust stability testing function is presented to reduce the computational complexity of the robust stability analysis;andⅲ)two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise reduction.Finally,four numerical examples and an experimental verification are presented in this study to demonstrate the efficacy and significance of the suggested technique.

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.

Tuning of fuzzy PID controller for Smith predictor

An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.

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.

Robust tuning method for modified smith predictor

A robust tuning method for ο^Astroem＇s two-degree of Freedom Modified Smith Predictor （MSP） is proposed, and it can achieve the fast setpoint and load disturbance responses independently. The tuning rules may meet the requirements within a certain delay margin according to the robustness theory. The simulation results illustrate that the tuning method is efficient compared with other controllers. Finally, the MSP controller is applied to the 15L batch fermentation system for controlling the temperature in bioreactor, and the experiment results further verify that the robust tuning rules may achieve good performance.

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.

A simple anti-windup method for the Modified Smith Predictor

For the first-order integrating processes with long delay, a Modified Smith Predictor (MSP) was analyzed when the control signal saturated. If the MSP controller has no anti-windup scheme, the saturation effectively chops off the control input resulting in performance deterioration. Thus, a simple and effective anti-windup scheme, without an additional parameter, is designed for the MSP. Simulation results illustrate that the proposed method may achieve good performance under the nominal and model uncertainty cases.

Smith Predictor Based Robust Rapid Tracking Controller

Precise model is hard to get in real application,a Smith predictor based robust rapid tracking controller for inaccurate model is proposed. Zero phase error feedforward controller which increases system closed-loop dynamics and disturbance observer based Smith feedback control which diminishes model hysteresis and improves stability are integrated. This method is applied in the noncircular machining with piezoelectric ceramic driver. The simulation and experiment show that the performance robustness and stability are well balanced in bandwidth about 200 Hz. The controller can decrease system hysteresis and get good tracking performance for predefined square-wave input signal.

基于改进Smith预估器的振动台子结构试验方法研究

振动台子结构试验是一种有效的实时结构混合试验方法,利用振动台和其他加载装置进行联合加载,可以提升振动台的加载能力。针对试验过程中受到干扰影响的振动台子结构试验控制系统,提出一种基于Smith预估器的控制方法。介绍了基于主动质量驱动器加载方法的振动台子结构试验装置和工作原理以及Smith预估器的实现方式。分析了时滞对控制系统的影响,当控制系统引入4 ms的时滞时,仿真结果发散,系统模型存在纯滞后环节,因此容易发生较严重的震荡。为解决此问题,引入Smith预估器与改进的Smith预估器并进行相应的数值仿真工作。仿真结果表明:基于传统Smith预估器的振动台子结构试验方法能够保证系统仿真结果不再发散,但其结果较为一般;而基于改进Smith预估器的振动台子结构试验方法结果更为理想,其峰值误差与均方根误差等相关评价指标都相对较小,说明所提方法可以有效解决时滞系统的稳定性问题。

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。

基于全部参数自适应Smith预估补偿的永磁同步电机滑模前馈控制及扰动抑制

在永磁同步电机控制系统中,逆变器的延迟效应会降低系统的跟踪性能和稳定裕度。引入Smith预估补偿器可以补偿延迟环节对系统性能的影响,但Smith预估补偿器要求延迟时间和被控对象模型参数已知,这不符合实际情况。为此提出时变模型自适应预估方法,分别对延迟时间和被控对象模型参数进行自适应估计,实现Smith预估补偿器的全参数自适应。设计基于位置输出超前值预测和扰动抑制的滑模前馈控制器,与全参数自适应Smith预估补偿控制相结合,确保控制系统的全局稳定,降低系统对参数不确定的敏感性,并提高系统的抗扰性。仿真结果表明,与传统及多种改进的Smith预估补偿方法相比,该方法有着更高的跟踪精度,即使在非理想条件下,对参数不确定依然具有较强的鲁棒性,对随机扰动依然具有较强的干扰抑制能力。

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。

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。

基于改进型Smith预估计器与大数据的光伏电网调频逐步惯性控制方法

光伏电网频率调整过程中,依靠常规Smith预估控制器实现电网调频控制,对模型精度具有较强的依赖性,控制策略实施后最大频率变化率(rate of change of frequency,RoCoF)较大。因此,提出基于改进型Smith预估计器与大数据的光伏电网调频逐步惯性控制方法。首先,采集历史气象数据和光伏电网运行数据,应用大数据分析领域的密度峰值聚类算法进行划分处理,再筛选相似日数据输入长短期记忆网络中,预测出未来光伏发电的功率变化;然后,依托逐步惯性控制思想,设计包含短时超发、转速恢复等多个阶段的电网调频控制策略,将模糊自适应比例-积分-微分(proportion-integration-differentiation,PID)控制器融入常规Smith预估计器,从而升级得到优化版的Smith预估计器;最后,在不受被控模型变化影响的情况下,依据预估补偿原理完成逐步惯性调频控制,并应用麻雀搜索算法求解出最优控制参数。实验结果表明:该控制方法实施后,光伏电网运行过程中最大RoCoF仅为0.086 Hz/s,有效降低了对模型精度的依赖性,保证了电力系统的稳定运行。

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。

一种带有反馈滤波器的自整定Smith预估器设计及其在纸张横幅定量控制中的应用

针对纸张横幅定量控制所存在的强耦合及大时滞特性,本研究提出了一种Smith预估器加模糊自整定PID复合控制策略。采用“区域化点”法并引入前置矩阵对非方系统进行降维,然后取降维后系统关联矩阵的逆矩阵作为解耦器,将系统转变为与稀释水阀数量一致的多个单回路。针对稀释水流浆箱的横幅定量控制系统大时滞特性,设计一种带有反馈滤波器的自整定Smith预估器控制方案,其主控制器采用模糊自整定(Fuzzy-PID)控制器。反馈环滤波器的存在使其可在模型失配情况下降低系统对模型失配误差的敏感度,进一步增强系统鲁棒性。仿真实验结合现场实际应用案例证明,该方案具有可行性和有效性,并且可将横幅定量差指标控制在2%以内。

Design and analysis of a proportional-integral controller based on a Smith predictor for TCP/AQM network systems

Active queue management(AQM)is essential to prevent the degradation of quality of service in TCP/AQM systems with round-trip time(RTT)delay.RTT delays are primarily caused by packet-propagation delays,but they can also be caused by the processing time of queuing operations and dynamically changing network situations.This study focuses on the design and analysis of an AQM digital controller under time-delay uncertainty.The controller is based on the Smith predictor algorithm and is called the SMITHPI controller.This study also demonstrates the stability of the controller and its robustness against network parameter variations such as the number of TCP connections,time delays,and user datagram protocol flows.The performance,robustness,and effectiveness of the proposed SMITHPI controller are evaluated using the NS-2 simulator.Finally,the performance of the SMITHPI controller is compared with that of a well-known queue-based AQM,called the proportional-integral controller.

自适应Fuzzy-Smith-PID控制器在加热炉温度控制中的研究与仿真

以箱式加热炉为研究对象,针对PID控制在温度控制中存在滞后和时变性的缺陷,提出一种带有Smith补偿环节的新型模糊PID控制方案,利用MATLAB实现仿真。由仿真结果可知,相比Smith控制和模糊控制,改进后的系统精度更高,抗干扰性和鲁棒性增强,系统过渡过程较为平稳,整体控制效果理想,具有良好的推广价值。

基于BRGWO算法和滤波Smith预估器的气弹系统时滞控制

气弹控制系统的驱动器、闭环信号回路在实际中会存在时滞环节,由于气弹敏感性和环境复杂性,时滞会引起控制信号迟延并导致气弹控制极速恶化、甚至造成系统失稳,该问题以往研究较少。针对翼型时滞气弹控制问题,设计了一种基于BRGWO算法和改进型滤波Smith的最优气弹控制方法。首先,引入二阶滤波器改进Smith预估器,设计了翼型气弹控制器;然后,创新设计了一种双向随机灰狼优化算法(bidirectional random grey wolf optimization, BGWO),提高了时滞下气弹控制参数的全局寻优能力,该算法改进了不同等级灰狼的狩猎策略,提高跳出非理想值机率、避免陷入局部最优。利用最小增益原理,在理论上证明了闭环系统稳定性。仿真结果表明,对比传统智能优化算法(如遗传算法、灰狼优化算法)和多种已有控制器(经典Smith、PI-PD型Smith和传统滤波Smith预估器),该方法具有更强的时滞补偿能力和更优的气弹控制性能,在不确定时滞、不确定风速、刚度变化和驱动干扰等算例下,保持了优良的时滞气弹控制效果,具有较强的鲁棒性。

基于Smith预估模糊PID的氨法脱硫控制策略

氨法脱硫系统存在滞后大、非线性和实时负荷跟踪性差等问题。针对该问题设计的Smith预估控制器通过补偿延迟时间提高了系统的实时性。但通常采用试凑法来设定系统中的PID(Proportion Integral Differential)参数,导致系统稳定性较差。文中提出模糊PID参数自适应整定控制方法,通过模糊控制器求得PID的3个参数的调整值,自适应地调整PID参数,将SNO_(x)的浓度控制在预设值附近。与传统阶跃信号判断控制效果不同,文中所提方法以实时的负荷数据来进行模型仿真,数据仿真结果也证明了Smith预估模糊PID控制器的可行性。系统稳定时SNO_(x)浓度与预设值的误差在0.5 ppm以内,缩短了调节时间,表明所提方法改善了氨法脱硫控制系统的实时跟踪性,实现了快准稳的脱硫控制性能。