Performance assessment of cascade controllers for nitrate control in a wastewater treatment process

A cascade control strategy is proposed to the benchmark simulation model 1 (BSM1) to enhance the treatment performance of nitrogen removal in a biological wastewater treatment plant. The proposed control approach consists of two control loops, a primary outer loop and a secondary inner loop. The method has two controllers of which the primary loop has a model predictive control (MPC) controller and the secondary loop has a proportional-integralderivative (PID) controller, which is a cascade MPC-PID controller. The primary MPC controller is to control the nitrate concentration in the effluent, and the secondary PID controller is to control the nitrate concentration in the final anoxic compartment. The proposed method controls the nitrate concentrations in the effluent as well as in the final anoxic reactor simultaneously to strictly satisfy the quality of the effluent as well as to remove the effects of disturbances more quickly by manipulating the external carbon dosage rate. Because the control performance assessment (CPA) technique has the features of determining the capability of the current controller and locating the best achievable performance, the other novelty of this paper is to suggest a relative closed-loop potential index (RCPI) which updates the CPA technology into a closed-loop cascade controller. The proposed method is compared with a cascade PID-PID control strategy and the original PID controller in BSM1 and an improved performance of the suggested cascade MPC-PID controller is obtained by using the CPA approach.     

工业过程的先进控制

在分析工业过程特点的基础上，总结了工业过程先进控制的发展现状，阐述了PID控制器参数整定和模型预测控制的基本概念和内容，讨论了工业过程先进控制的核心内容及其带来的可观的经济效益，并探讨了先进控制软件的产业化问题。     

FPGA based QDMC control for reverse-osmosis water desalination system

Model-based predictive control (MPC) is a widely used advanced control algorithm in process industries, such as chemical plants and oil refineries. Quadratic dynamic matrix control (QDMC) is one of the popular MPC strategies. In this paper, the QDMC controller is used to control a simulated reverse-osmosis (RO) water desalination system with spiral wound element (SWM). A cascaded control system was designed with the QDMC controller and a PID controller for the desalination process, where the QDMC controller optimizes the set point of the PID controller and directly controls one output. In order to make the implementation more convenient, this paper also studies the implementation of QDMC control system based on a field programmable gate array (FPGA) chip. A support software is developed to help engineers adjust the parameters of the QDMC controller. Since the QDMC controller is implemented in an embedded system, the overall system cost is reduced, which is helpful to the application of RO desalination system.     

基于LMI的鲁棒PID控制器设计及工业应用

针对工业广泛应用的PID控制器,提出一种PID控制器性能评价及鲁棒参数优化的设计方法,该方法将PID控制器性能评价与鲁棒参数整定问题转化为线性矩阵不等式(LMI)凸优化问题进行求解,并利用所提方法开发了工业应用注册软件.     

An energy effective PID tuning method for the control of polybutadiene latex reactor based on closed-loop identification

The PBL (Polybutadiene Latex) production process is a typical batch process. Changes of the reactor characteristics due to the accumulated scaling with the increase of batch cycles require adaptive tuning of the PID controller being used. In this work we propose a tuning method for PID controllers based on the closed-loop identification and the genetic algorithm (GA) and apply it to control the PBL process. An approximated process transfer function for the PBL reactor is obtained from the closed-loop data by using a suitable closed-loop identification method. Tuning is performed by GA optimization in which the objective function is given by ITAE for the setpoint change. The proposed tuning method showed good control performance in actual operations.     

数控交流伺服系统三环整定及应用

建立三相永磁同步电机数控交流伺服系统的三环控制框图,分析了三环的PID控制器整定,同时提出采用稳定边界法整定三环的PID参数,给出了具体的整定步骤。以数控高速铣齿机床为实例,在不考虑机床机械部分的情况下,用MATLAB/S imu link模块建立其Z向进给位置伺服系统的仿真模型,采用稳定边界法在MATLAB中仿真整定。结果表明伺服系统无超调、响应快且具有较好的稳定性,能满足高速铣齿机床的性能要求。     

TUNING PID CONTROLLER FOR OPEN-LOOP UNSTABLE PROCESSES WITH TIME DELAY

A calculation method of PID controller tuning for the first- and the second-order open-loop unstable process models with time delay is presented in this study. Optimum PID controller tuning data based on the models and minimum IAE criterion were obtained via Powell searching technique, and these data were then empirically correlated into several multiple-regression equations by a least-squares method. Thus PID controller tuning based on the models can easily be obtained by the calculation of these correlated equations. Simulation with a reset-feedback PID control algorithm has demonstrated that the proposed tuning method based on the first-order model can provide better results than the latest studies. In addition, simulation has also unveiled that tuning results based on the second-order models are superior to the first-order model for a higher-order process.     

基于微粒群优化的鲁棒PID控制器参数整定方法研究

针对复杂工业过程中存在的一类模型不确定问题,提出一种新的鲁棒PID控制器参数整定方法.通过将鲁棒PID控制器的参数整定问题转化成一个max-min优化问题,利用微粒群优化(PSO)的协作算法对之进行求解,能获得某种鲁棒性能指标最优的PID控制器.对连续搅拌反应釜系统的实例仿真结果表明:与其它典型鲁棒PID控制器设计方法相比,本方法得到的PID控制器具有更强的鲁棒性和抗干扰能力,当过程操作范围发生大的变化时,利用本方法设计的鲁棒PID控制器能获得满意的结果.     

Model predictive control of condensate recycle process in a cogeneration power station: Controller design and numerical application

A model predictive control (MPC) system has been developed for application to the condensate recycle process of a 300 MW cogeneration power station of the East-West Power Plant, Gyeonggido, Korea. Unlike other industrial processes where MPC has been predominantly applied, the operation mode of the cogeneration power station changes continuously with weather and seasonal conditions. Such characteristic makes it difficult to find the process model for controller design through identification. To overcome the difficulty, process models for MPC design were derived for each operation mode from the material balance applied to the pipeline network around the concerned process. The MPC algorithm has been developed so that the controller tuning is easy with one tuning knob for each output and the constrained optimization is solved by an interior-point method. For verification of the MPC system before process implementation, a process simulator was also developed. Performance of the MPC was investigated first with a process simulator against various disturbance scenarios.     

A model predictive functional control based on proportional-integral-derivative (PID) and proportional-integral-proportional-derivative (PIPD) using extended non-minimal state space: Application to a molten carbonate fuel cell process

The performance of most controllers, including proportional-integral-derivative (PID) and proportional-integral-proportional-derivative (PIPD) controllers, depends upon tuning of control parameters. In this study, we propose a novel tuning strategy for PID and PIPD controllers whose control parameters are tuned using the extended non-minimal state space model predictive functional control (ENMSSPFC) scheme based on the auto-regressive moving average (ARMA) model. The proposed control method is applied numerically in the operation of the MCFC process with the parameters of PID and PIPD controllers being optimized by ENMSSPFC based on the ARMA model for the MCFC process. Numerical simulations were carried out to assess the set-point tracking performance and disturbance rejection performance both for the perfect plant model, which represents the ideal case, and for the imperfect plant model, which is usual in practical applications. When there exists uncertainty in the plant model, the PIPD controller exhibits better overall control performance compared to the PID controller.     

模糊PID控制器的发展

将模糊控制技术和PID控制相结合，可克服常规PID控制器的不足，使PID控制器具有参数自适应能力。介绍了模糊控制器和PID控制器间的关系，从一维、二维及三维模糊控制器的输入－输出形式上，以及解析分析角度出发，可以说模糊控制器人本质上讲是一种非线性PID控制器。还总结了模糊PID控制器的结构。模糊PID控制器可分成两大类，一类由参数可变的PID控制器及一个模糊控制器共同构成，模糊控制器用于完成PID参数的在线整定，控制信号仍由PID控制器生成；另一类直接用模糊控制器来构造、实现PID控制功能。分别归纳了这两类控制器的多种结构形式。最后还对模糊PID控制器的发展进行了展望，提出了模糊PID 控制器结构的选择、控制器参数调整及控制器评价标准的确定这几方面是今后工作的重点。     

基于模型预测残差闭环潜能指标的MPC控制器实时性能监控

由于模型预测控制器对模型失配等不确定因素具有较强的鲁棒性,因此现有的多步预测误差方法不能及时显著地检测到由模型失配导致的MPC控制器性能潜能的变化。针对上述问题,提出一种改进的多步预测误差方法和实时性能监控策略。考虑到MPC控制器的模型预测残差能有效反映模型失配等信息,利用预测残差对现有多步预测误差方法进行改进,改进的方法能够更好地检测由模型失配引起的MPC控制器性能潜能的改变。在连续搅拌槽加热器(continuous stirred tank heater,CSTH)系统上的仿真实验验证了该方法的可行性与有效性。     

基于改进VRFT算法的PID控制器参数整定

分析虚拟参考反馈参数整定（VRFT）设计方法和内模控制（IMC）方法的内在关系,提出一种改进的VRFT—PID参数整定方法。该方法的基本思想是将运行一段时间的过程输入输出数据添加到原始数据序列中,用来更新传统VRFT设计方法中的离线数据。然后利用VRFT使性能指标最小时的参数即为控制器参数的设计思想来整定PID控制器。仿真结果表明,改进的VRFT-PID整定方法优于传统的VRFT-PID方法。     

A new predictive PID controller for the processes with time delay

A new proportional-integral-derivative (PID) controller is proposed based upon a simplified generalized predictive control (GPC) control law. The tuning parameters of the proposed predictive PID controller are obtained from the simplified GPC control law for the 1 ^st -order and 2 ^nd -order processes with time delays of integer and non-integer multiples of the sampling time. The internal model technique is employed to compensate the effect of time delay of the target process. The predictive PID controller is equivalent to the PI controller when the target process is 1 ^st -order and to the PID controller when the target process is an integrating process. The performance of the proposed predictive PID controller is almost the same as that of the simplified GPC. The main advantage of the proposed control scheme over other control methods is the ease of tuning and operation.     

An automatic pid controller tuning method by frequency response techniques

An alternative Ziegler-Nichols (1942) controller tuning technique was proposed in this study. Under the proportional control of a single-loop control system, an arbitrary pulse testing in the set point was introduced to the system. The ultimate frequency and gain could both be directly calculated from the transients by frequency response techniques without any trial and error procedures. PID controller settings were thus obtained according to the Ziegler and Nichols' rules. Furthermore, this technique was extended to the tuning of a cascade control system. A procedure for simultaneously tuning the primary and secondary controllers with both loops in proportional control from a single pulse testing also is presented.     

基于期望闭环系统响应的网络化串级控制系统PID整定

研究有常数网络诱导时延的一类典型网络化串级控制系统的PID控制器参数整定问题。系统中的网络诱导时延为常数,主对象和副对象均为一阶惯性加纯迟延环节(FOPDT)。主控制器是有超前滞后校正环节的PID,副控制器是带有滤波环节的PID。基于过程模型和期望闭环系统响应整定PID参数,采用一阶P偄de近似纯迟延环节,以解析的形式推导出了主控制器和副控制器整定参数的表达式,并采用双线性变换法得到离散时间PID控制器。提出了网络化串级控制系统的控制性能综合指标,并基于TrueTime工具箱在不同网络诱导时延时对网络化串级控制系统进行了仿真研究。仿真结果和性能指标计算结果均验证了所提算法的可行性和有效性。     

Optimization‐Based Nonlinear Centralized Controller Tuning of Liquid‐Liquid Extraction Processes

Abstract

The control problem of an agitated contactor is considered in this work. A Scheibel extraction column is modeled using the non‐equilibrium backflow mixing cell model. Model dynamic analysis shows that this process is highly nonlinear, thus the control problem solution of such a system needs to tackle the process nonlinearity efficiently. The control problem of this process is solved by developing a multivariable nonlinear control system implemented in MATLAB?. In this control methodology, a new controller tuning method is adopted, in which the time‐domain control parameter‐tuning problem is solved as a constrained optimization problem. A MIMO (multi‐input multi‐output) PI controller structure is used in this strategy. The centralized controller uses a 2×2 transfer function and accounts for loops interaction. The controller parameters are tuned using an optimization‐based algorithm with constraints imposed on the process variables reference trajectories. Incremental tuning procedure is performed until the extractor output variables transient response satisfies a preset uncertainty which bounds around the reference trajectory. A decentralized model‐based IMC (internal model control) control strategy is compared with the newly developed centralized MIMO PI control one. Stability and robustness tests are applied to the two algorithms. The performance of the MIMO PI controller is found to be superior to that of the conventional IMC controller in terms of stability, robustness, loops interaction handling, and step‐change tracking characteristics.     

A model predictive control package for undergraduate education

Model predictive control (MPC) techniques are extremely profitable control strategies and are well accepted in the chemical processing industry so it is important that chemical engineering graduates have a fundamental understanding of MPC. This understanding will help them make contributions in industry where these control strategies abound. Without such knowledge, graduates would not understand a major part of the control structure present in modern manufacturing systems and would have difficulty understanding how to modify and improve those chemical manufacturing systems to take advantage of new technology.In this paper we describe a new software package developed and tested by the authors for teaching undergraduates the fundamentals of MPC including its suggested application in the classroom. The package is similar to existing industrial model predictive control packages in that the same steps are required to implement a model predictive controller as follows: model identification, controller configuration, controller simulation and tuning. We describe our experience using the package to introduce MPC to an advanced undergraduate process control II class. The package has also been used to provide an MPC laboratory experience for a graduate class on industrial process control.     

A one-step tuning method for PID controllers with robustness specification using plant step-response data

This paper presents a novel method for proportional-integral-derivative (PID) controller tuning directly using the step response data of the process without resorting to a process model. The required process data are collected from a one-shot step test that can be conducted under either closed-loop or open-loop conditions. The proposed method derives the PID parameters so that the resulting control system behaves as closely as possible to the prescribed reference model. Two structures of the reference model are considered for general design and improved disturbance rejection, respectively. A simple one-dimensional optimization problem is formulated to determine an appropriate reference model for the controlled process. Moreover, the proposed PID tuning method includes a robustness specification based on the maximum peak of sensitivity function that enables the user to explicitly address the trade-off between performance and robustness. Simulation examples are provided to illustrate the superiority of the proposed method over existing (model-based) tuning methods.     

SOME THEORETICAL INSIGHTS INTO RECENT CONTROL DESIGN ALGORITHMS

Internal Model Control (IMC) design procedure is known to offer valuable advantages over classical control methods, especially for robust controller design. The Perfect Controller is defined using the well-known classical PID algorithm and its equivalence to IMC. After the definition of the Perfect Controller the IMC filter tuning parameter, which is used to maintain robustness, is obtained as a result of reparametrization of the classical PID control algorithm and factorization of the model. Through factorization, invertible part of the model is used directly in defining the perfect controller and the noninvertibility effects of the model are lumped into the new IMC tuning parameter. Closed loop IMC controller design is obtained with appropriate plant parameter uncertainty representation. Theoretical foundation for the transition from classical PID design to IMC design is analyzed using simple common chemical process models.