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.

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。

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。

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.

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.

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.

Design of Smith Predictor Based Fractional Controller for Higher Order Time Delay Process

Normally all real world process in a process industry will have time delay.For those processes with time delays,obtaining satisfactory closed loop performances becomes very difficult.In this work,three interacting cylindrical tank process is considered for study and the objective of the work is to compensate for time delays using smith predictor structure and to maintain the level in the third tank.Input/Output data is generated for the three interacting tank process.It is approximated as Integer First Order Plus Dead Time system(IFOPDT)and Fractional First Order Plus Dead Time system(FFOPDT).Smith predictor based fractional order Proportional Integral controller and Integer order Proportional Integral controller is designed for the IFOPDT and FFOPDT model using frequency response technique and their closed loop performance indices are compared and tabulated.The servo and regulatory responses are simulated using Matlab/Simulink.

Improved Smith prediction monitoring AGC system based on feedback-assisted iterative learning control

The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P 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 roll-ing speed was evaded. After a Smith predictor was used to monitor the AGC system, the control laws were deduced for both propor-tional 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 higher steady-state precision.

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.

ROBUST SMITH PREDICTIVE CONTROLLER FOR PROCESS WITH INVERSE RESPONSE

Smith predictor known as the time delay compensator was extended to control the process with inverse response.Modern robust control theory was employed to design the robust controller,which has only one parameter to be determined with compromise among the rise time,undershoot,robustness and capability to reject disturbance of the closed loop system.The former two specifications can be assessed quantitatively and the latter two qualitatively.Examples show that the proposed method has significant improvements and wide applicable ranges for inverse response process.

胎面重量控制系统的CPSO优化Smith预估线性自抗扰策略

针对轮胎行业橡胶复合挤出线重量控制系统过程机理复杂、扰动过多且难以测量等问题,设计了一种史密斯预估与线性自抗扰控制(Smith prediction-linear active disturbance rejection control,Smith-LADRC)相结合的控制方式以实现对胎面重量的稳定控制。建立仿真模型与比例-积分-微分(proportional-integral-differential,PID)、LADRC、Smith-PID进行控制效果对比以验证其优势,同时针对此控制器调参困难引入混沌粒子群算法(chaotic particle swarm optimization,CPSO)进行参数整定。经实验结果表明:Smith-LADRC相较于上述3种控制方法能够使系统具有较好的抗干扰性和鲁棒性;采用CPSO算法寻优后,相比于粒子群算法(particle swarm optimization,PSO),可以很好地达到控制目的,系统输出响应快速性均得到提高,相比手动调节能更好地对系统输出进行控制,同时节省参数调节时间,提高控制效率。

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。

垃圾渗滤液污水处理设备的臭氧投加复合抗扰控制

垃圾渗滤液污水处理设备中的臭氧投加系统具有大时滞、大惯性和多扰动的特点,导致难以实时调整臭氧投加量,从而影响后续设备出水水质。针对以上问题,在水流量比例的控制方面提出一种基于扰动观测器的改进型Smith预估器与滑模控制相结合的复合抗扰控制。其中,滑模控制为主控制器,扰动观测器用于估计出系统的集总扰动并反馈至前向通道消除扰动的不利影响,以便于Smith预估器更好地进行时滞补偿。仿真和实验结果表明,复合抗扰控制相较于PID控制和自抗扰控制具有更好的控制性能和抑制扰动的能力,能够有效提高垃圾渗滤液污水处理设备的出水水质。