High-performance multi-scale control scheme for stable,integrating and unstable time-delay processes

This paper presents a new multi-scale control scheme which is applicable to both stable and integrating/unstable time-delay processes. The salient feature of the proposed scheme is to decompose a given plant into a sum of basic modes, where an individual sub-controller is specifically designed to control each of these modes. An overall multi-scale controller is then synthesized by combining all the sub-controllers in such a way to achieve good cooperation among the different plant modes as to achieve good nominal performance and performance robustness. Extensive numerical study shows that the proposed multi-scale control scheme provides substantial improvement in control performance/robustness over the classical Smith predictor and some of its well-established variants.     

Simple control method for integrating processes with long deadtime

Control of integrating processes with long deadtime is a challenging problem. Using original Smith predictor control structure will result in an offset problem during load disturbance. Using the internal model control (IMC) principle to design the control structure will result in large overshoot during servo response. In this work, a simple modified Smith predictor controller design is proposed for this important type of system. The overall control structure has only two physically meaningful tuning parameters. One is used to set the speed of the closed-loop servo response and the other tuning parameter is used to set the speed of the closed-loop load response. Two examples are used to demonstrate the improved closed-loop performance of the proposed controller design.     

Multi-loop design of multi-scale controllers for multivariable processes

Based on the recently proposed (SISO) multi-scale control scheme, a new approach is introduced to design multi-loop controllers for multivariable processes. The basic feature of the multi-scale control scheme is to decompose a given plant into a sum of basic modes. To achieve good nominal control performance and performance robustness, a set of sub-controllers are designed based on the plant modes in such a way that they are mutually enhanced with each other so as to optimize the overall control objective. It is shown that the designed multi-scale controller is equivalent to a conventional PID controller augmented with a filter. The multi-scale control scheme offers a systematic approach to designing multi-loop PID controllers augmented with filters. Numerical studies show that the proposed multi-loop multi-scale controllers provide improved nominal performance and performance robustness over some well-established multi-loop PID controller schemes.     

多变量时滞过程解耦Smith控制

针对实际工业生产中常见的多输入多输出时滞过程,构造多变量Smith预估控制结构,提出基于对象模型伴随矩阵的解耦器设计方法.通过对解耦后对象的幅频和相频特性分析,获得对象的简化一阶数学模型.根据Smith预估控制结构闭环特征方程的特点,利用Butterworth滤波器极点配置的原理,对解耦后的多变量时滞过程设计PI控制器.结合实际过程中常见的不确定性,分析了控制系统保证鲁棒稳定性的充要条件.最后以实例验证了本文所提方法的优越性.     

Variable control scheme in the cascade processes

The article considers the variables process control scheme for cascade processes. We construct variable sample sizes and sampling intervals (VSSI) control charts to effectively monitor the input variable and the output variable produced by a cascade process. The performance of the proposed VSSI control charts is measured by the adjusted average time to signal derived by a Markov chain approach. An example of the metallic film thickness of the computer connectors system shows the application and the performance of the proposed VSSI control charts in detecting shifts in means of the cascade process. Furthermore, the performance of the proposed VSSI control charts and the fixed sample sizes and sampling intervals control charts are compared by numerical analysis results. These demonstrate that the former is much faster in detecting small and medium shifts. The optimum VSSI control charts are also proposed using optimization technique when quality engineers cannot specify the values of the variable sample sizes and sampling intervals. It has been found that the optimum VSSI control charts work and are thus suggested whenever quality engineers cannot specify the values of variable sample sizes and sampling intervals. Furthermore, the impacts of misusing Shewhart charts to monitoring the process means on the cascade process are also investigated.     

Iterative learning control with Smith time delay compensator for batch processes

How to improve the control of batch processes is not an easy task because of modeling errors and time delays. In this work, novel iterative learning control (ILC) strategies, which can fully use previous batch control information and are attached to the existing control systems to improve tracking performance through repetition, are proposed for SISO processes which have uncertainties in modeling and time delays. The dynamics of the process are represented by transfer function plus pure time delay. The stability properties of the proposed strategies for batch processes in the presence of uncertainties in modeling and/or time delays are analyzed in the frequency domain. Sufficient conditions guaranteeing convergence of tracking error are stated and proven. Simulation and experimental examples demonstrating these methods are presented.     

Modified Smith predictor scheme for periodic disturbance reduction in linear delay systems

This paper presents a disturbance reduction scheme for linear systems with time delays. The linear systems in the study are assumed to be nominally stable, minimum phase, and relative degree one systems. The proposed scheme is a combination of Astrom’s modified Smith predictor with a disturbance reduction controller and a grey predictor. Unlike conventional disturbance rejection methods, the scheme proposed in this study does not require the estimation of disturbance frequencies. The grey prediction method is used to approximate the inverse of the time delay and to enhance the robustness of the disturbance reduction scheme against errors in the estimated delay time. The simulation results demonstrate the successful performance of the proposed disturbance reduction method for controlling a linear system with time delays, subjected to both step and periodic disturbances.     

A modified Smith predictive scheme based back-propagation neural network approach for FOPDT processes control

In this paper, a novel control scheme to deal with process uncertainties in the form of disturbance loads and modelling errors, as well as time-varying process parameters is proposed by applying the back-propagation neural network (BPNN) approach. A BPNN predictive controller that replaces the entire Smith predictor structure is initially trained offline. Lyapunov direct method is used to prove that the convergence of this BPNN is guaranteed by selecting a suitable learning rate during the learning process. However, the Smith predictor based BPNN control is an off-line training based algorithm, which is a time consuming method and requires a known process plant input from the controller. A desired control input to the process is difficult to obtain for the training of the network. As a result a group of proper training data (target control inputs and outputs) can hardly be provided. In order to overcome this problem, a BPNN with an on-line training algorithm is introduced for the control of a First Order plus Dead Time (FOPDT) process. The stability analysis is carried out using the Lyapunov criterion to demonstrate the network convergence ability. Simulation results show that this proposed online trained neural Smith predictor based controller provides excellent robustness to process modelling errors and disturbance loads, and high adaptability to time varying processes parameters.     

基于Smith预估补偿的网络控制系统仿真研究

针对网络控制系统中前向通道和反馈通道同时存在随机延迟的问题,提出了一种基于神经元控制器的Smith预估器的设计方案。利用根轨迹法分析了随机延迟对网络控制系统稳定性的影响。结合不完全微分先行PID控制算法,建立了Smith预估模型,在模型不完全匹配的情况下得到较好的控制性能。以直流电机为被控对象进行仿真研究,仿真结果表明该方法的有效性。     

A double two-degree-of-freedom control scheme for improved control of unstable delay processes

A double two-degree-of-freedom control scheme is proposed for enhanced control of unstable delay processes. The scheme is motivated by the modified Smith predictor control in [IEE Proc. Control Theory Appl. 16(5) (1999) 359] and devised to improve in the following ways: (i) one more freedom of control is introduced in our scheme to enable manipulation of disturbance transient response, and is tuned based on minimization of the integral squared error criterion; (ii) four controllers in the scheme are well placed to separately tune the denominators and numerators of closed-loop transfer functions from the set-point and disturbance. This allows easy design of each controller and good control performance for both set-point and disturbance responses. Especially, improvement of disturbance response is extremely great, compared with [IEE Proc. Control Theory Appl. 16(5) (1999) 359; Automatica 36 (2000) 1651]. Internal stability of the proposed structure is analyzed, which has not been reported in the literature on modified Smith predictor control before. Examples are provided for illustration.     

Prediction-based control for a class of unstable time-delayed processes by using a modified sequential predictor

This work presents a prediction-based scheme to control a class of unstable delayed (bio)-chemical processes. The main characteristic of the control scheme is that it is based on a predicted future state that is estimated using a prediction-observation protocol that allows compensating large time-delays. The convergence of the prediction error is shown through standard stability arguments. The stability of the closed-loop system is shown by invoking the separation principle between the prediction error and the control based on estimated variables feedback. Four numerical examples are used to illustrate our results, including two time-delayed benchmark case studies taken from the control process literature.     

Enhanced design of cascade control systems for unstable processes with time delay

In this paper, optimal H₂ internal model controller (IMC) is designed for control of unstable cascade processes with time delays. The proposed control structure consists of two controllers in which inner loop controller (secondary controller) is designed using IMC principles. The primary controller (master controller) is designed as a proportional-integral-derivative (PID) in series with a lead-lag filter based on IMC scheme using optimal H₂ minimisation. Selection of tuning parameter is important in any IMC based design and in the present work, maximum sensitivity is used for systematic selection of the primary loop tuning parameter. Simulation studies have been carried out on various unstable cascade processes. The present method provides significant improvement when compared to the recently reported methods in the literature particularly for disturbance rejection. The present method also provides robust closed loop performances for large uncertainties in the process parameters. Quantitative comparison has been carried out by considering integral of absolute error (IAE) and total variation (TV) as performance indices.     

模糊Smith智能温度控制器的设计与仿真

结合模糊PID控制与模糊自适应Smith预估控制的优点,提出了模糊Smith智能控制方法。用模糊控制方法设计了改进型Smith预估器的滤波时间常数,并制定了其整定规则和参数的模糊自适应调整机构。仿真研究表明,模糊Smith智能控制能改善参数时变的纯滞后系统的控制性能,提高系统控制时的鲁棒性与自适应性。     

滑模等式约束的时滞系统广义预测控制

提出了一种滑模等式约束的广义预测控制方法.该方法将广义预测控制与离散滑模控制结合起来用于具有大惯性、大时滞、时变和非线性的热力站换热机组的供水温度控制系统中,并采用柔化输入信号的方法,可避免广义预测控制算法中的矩阵求逆,有效缩短了预测时域,减小计算量.最后给出了稳定性分析并通过仿真验证了该方法的有效性.     

Design of a bandwidth-on-demand (BoD) protocol for satellite networks modelled as time-delay systems

Bandwidth-on-demand (BoD) access protocols address the problem of guaranteeing a high exploitation of the valuable satellite bandwidth in the presence of large amount of data traffic accessing the satellite network. The novelty of the proposed BoD scheme consists in the use of control theory concepts to model the satellite network as a time-delay system and to generate the bandwidth requests. The proposed scheme, based on the internal model control and on the Smith's principle, yields the following advantages: (i) when the network is not congested, it provides upper-bounds to the queue lengths and to the queuing delays of the satellite terminal buffers; (ii) it is capable of recovering from congested states; (iii) it is independent of the statistical characteristics of the traffic entering the satellite network; (iv) the requests are such that the satellite terminals have always enough traffic to use all the requested bandwidth (so that no bandwidth is wasted). The paper includes simulations showing the effectiveness of the proposed BoD scheme. The work underlying this paper has been performed within the GEOCAST project belonging to the fifth framework Information Society and Technology programme of the European Union.     

一类非自衡加纯滞后系统的双预测P I 控制

提出了一类基于非自衡加大纯滞后过程的双预测PI控制器的结构形式，这种控制器结构筒单，可调参数少，参数的调节方便、直观，仿真结果表明：在干扰和模型失配的情况下，此类控制器仍具有良好的控制性能和鲁棒稳定性，是一种值得在实际工程中推广应用的新型控制器。     

A simple method of tuning series cascade controllers for unstable systems

A simple method is proposed to design P/PI controllers for a series cascade control system for unstable first order plus time-delay （FOPTD） systems. In this paper, the controller design for unstable FOPTD systems cascaded in series with stable/unstable FOPTD systems is considered. The proposed method is based on equating the coefficients of corresponding powers of s and s2 in the numerator to α1 and α2 times those of the denominator of the closed-loop transfer function for a servo problem. The open loop system consists of an unstable FOPTD system cascaded in series with a stable/unstable FOPTD system. Only two tuning parameters （α1 and α2） are required for the design of controllers. The closed-loop performances are evaluated for both the servo and regulatory problems and the performances are found to be better than that of the well established synthesis method. The robustness for uncertainty in the model parameters is studied and compared with that of the controllers designed by the synthesis method.     

Adaptive neural network predictive control for nonlinear pure feedback systems with input delay

This paper presents an adaptive neural control design for nonlinear pure-feedback systems with an input time-delay. Novel state variables and the corresponding transform are introduced, such that the state-feedback control of a pure-feedback system can be viewed as the output-feedback control of a canonical system. An adaptive predictor incorporated with a high-order neural network (HONN) observer is proposed to obtain the future system states predictions, which are used in the control design to circumvent the input delay and nonlinearities. The proposed predictor, observer and controller are all online implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed. The conventional backstepping design and analysis for pure-feedback systems are avoided, which renders the developed scheme simpler in its synthesis and application. Practical guidelines on the control implementation and the parameter design are provided. Simulation on a continuous stirred tank reactor (CSTR) and practical experiments on a three-tank liquid level process control system are included to verify the reliability and effectiveness.