Enhanced control of integrating cascade processes with time delays using modified Smith predictor

This paper presents a simple cascade controller in the enhanced modified Smith predictor structure for control of integrating processes. The proposed structure consists of two control loops, a secondary inner loop and a primary outer loop. The method has totally three controllers of which the secondary loop has one controller and the primary loop has two controllers. The secondary loop controller is designed using IMC technique. The primary loop set-point tracking and disturbance rejection controllers are designed using direct synthesis method. The primary set-point tracking controller is designed as a PID with lag filter and the primary disturbance rejection controller is designed as a PD with lead-lag filter. Simulation studies have been carried out on various cascade integrating processes with/without zero. The present method gives significant disturbance rejection both in the inner and outer loops and also shows significant improvement when compared to the recently reported methods.     

改进Smith预估控制器的解析设计

针对化工过程常见的积分和不稳定时滞对象,基于改进的史密斯预测控制提出了两自由度控制方案。首先根据鲁棒控制理论H2最优性能指标设计设定值跟踪控制器,然后在分析稳定性和抗扰性的基础上设计了扰动抑制控制器,设定值跟踪控制器和扰动抑制控制器可通过性能参数独立调节和优化。同时针对存在的乘性不确定性过程分析了系统的鲁棒稳定性。最后通过仿真实例验证了该控制方案的有效性。     

积分和不稳定时滞对象的改进内模控制

针对化工过程中一阶积分和不稳定时滞对象,基于内模控制提出了两自由度控制方案。首先根据鲁棒控制理论H2最优性能指标设计设定值跟踪控制器,然后采用期望闭环补灵敏度函数确定扰动抑制控制器。设定值跟踪控制器和扰动抑制控制器可通过性能参数独立调节而无需再取折衷,同时保证系统具有较好的鲁棒稳定性。最后通过仿真实例验证了该控制方案的有效性。     

Synthesis of PID controller for unstable and integrating processes

Properly designed controllers provide stable closed-loop response for open-loop unstable processes. Internal model controller equivalent PID tuning rules for low order unstable plus dead time systems are synthesized in this work. The controller is approximated near the vicinity of zero (origin). Controller parameters are derived by equating the closed-loop response to a control-signature (desired closed-loop response) involving a user defined tuning parameter, λ. Simulations are carried out to show the performance of the proposed tuning scheme for both set point and disturbance rejection cases.     

一种改进的Smith预估控制系统

提出一种改进的Smith预估器 ,在常规Smith预估器的基础上增加了两个控制器 ,内环控制器用来稳定积分和不稳定过程 ,反馈控制器对干扰进行抑制 ,并把主控制器设为设定值加权PI控制器。仿真结果表明 ,该方案不仅可行 ,而且在模型失配的条件下 ,控制品质比常规的Smith预估控制有很大的改善。     

A Critical Study of Decentralized Controllers for a Multivariable System

Industrial processes are naturally multivariable in nature. A comparison of multivariable decentralized controllers has been performed and a multivariable four interconnected water tank system, which exhibits a RHP (Right Half Plane) zero is considered for decentralized control. The characteristics of a four‐tank system are discussed and a decentralized PI (Proportional‐Integral) controller is designed for the system based on various control algorithms. The algorithms are simulated using MATLAB and the performances are compared for reference tracking, disturbance rejection and model uncertainty cases. The comparison of the results show that the controllers based on Gershgorin band and Ideal relay method are suitable for the control of a four‐tank system.     

Multi‐controller scheme for load rejection and set‐point tracking

To acheive complete compensation for loads, a novel multi‐controller scheme with feedforward control is proposed. This scheme has four controllers, a set‐point controller, two load controllers, and a feedforward controller. This results in the separation of the load response from the set‐point response in a closed‐loop system. These four controllers can then be designed independently to achieve good system performance for both set‐point tracking and load rejection. One of the load controllers can be chosen as a proportional controller; this guarantees physical realizability and provides excellent compensation. The results of simulation and real time control show that the proposed multi‐controller scheme is superior to a double‐controller system and a Smith predictor in the presence of large uncertainty in process dynamics especially for load disturbances.     

A unified approach to the design of advanced proportional-integral-derivative controllers for time-delay processes

A unified approach for the design of proportional-integral-derivative (PID) controllers cascaded with first-order lead-lag filters is proposed for various time-delay processes. The proposed controller’s tuning rules are directly derived using the Padé approximation on the basis of internal model control (IMC) for enhanced stability against disturbances. A two-degrees-of-freedom (2DOF) control scheme is employed to cope with both regulatory and servo problems. Simulation is conducted for a broad range of stable, integrating, and unstable processes with time delays. Each simulated controller is tuned to have the same degree of robustness in terms of maximum sensitivity (Ms). The results demonstrate that the proposed controller provides superior disturbance rejection and set-point tracking when compared with recently published PID-type controllers. Controllers’ robustness is investigated through the simultaneous introduction of perturbation uncertainties to all process parameters to obtain worst-case process-model mismatch. The process-model mismatch simulation results demonstrate that the proposed method consistently affords superior robustness.     

Disturbance rejection of dead-time processes using disturbance observer and model predictive control

This article mainly focuses on disturbance rejection of dead-time processes by integrating a modified disturbance observer (MDOB) with a model predictive controller (MPC). The effect caused by model mismatches is regarded as a part of the lumped disturbances. This means that the disturbances considered here include not only external disturbances, but also internal disturbances caused by model mismatches. Control structure of the proposed method includes two parts which can be designed separately. The MPC which acts as a prefilter, is employed to generate appropriate control actions such that a desired setpoint tracking response is achieved. The MDOB is employed to estimate the disturbances of the closed-loop system, and the estimation is used for feedforward compensation design to reject disturbances. Rigorous analysis of setpoint tracking and disturbance rejection properties of the closed-loop system are given in the presence of both model mismatches and external disturbances. The proposed scheme is applied to control the temperature of a simplified jacketed stirred tank heater (JSTH). Simulation results demonstrate that the proposed method possesses a better disturbance rejection performance than those of the MDOB-PI, MPC and PI methods in controlling such dead-time processes.     

一种新的整定方法用于参数不确定条件下二自由度内部模型控制(英文)

Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.     

基于二自由度PI控制器的吹塑机张力控制系统

吹塑机的张力控制系统是一个大时滞线性系统,实现其控制难度较大。针对张力控制系统的一阶积分时滞模型,提出一种改进的基于多主导极点配置方法的二自由度PI控制算法,假设存在正的、稳定的多主导极点,过程控制系统无振荡,并且非主导的极点和零点对控制过程无影响,为了提高伺服性能和降低超调量,在结构中设计了设定点滤波器。仿真案例实验结果表明,该方法在吹塑机张力控制中具有良好的追踪性能和扰动抑制性能。     

The 2-port control system

The 2-port control structure is introduced to develop a complete framework for the analysis and design of robust predictive controllers. It is particularly suited for the optimum resolution of controller design trade-offs, such as performance to set-point tracking vs. disturbance rejection, and performance at various frequencies. Furthermore, the 2-port control structure allows the transparent design of effective controllers for processes with non-minimum phase characteristics, or inherently unstable open-loop dynamics. Finally, it offers, the necessary and sufficient conditions for the design of effective adaptive control strategies. Various illustrations are also provided to demonstrate the relationship of the 2-port control structure to other design frameworks, such as internal model control (IMC), and conventional feedback with analytic predictors.     

Dynamics and Control of a Biodiesel Transesterification Reactor

Biodiesel transesterification reactors resemble the heart of any biodiesel manufacturing plant. These reactors involve a highly complex set of chemical reactions and heat transfer characteristics. The high nonlinearity inherent in the dynamics of these reactors requires an efficient process control algorithm to handle the variation of operational process parameters and the effect of process disturbances efficiently. In this work, a multi‐model adaptive control strategy is considered for achieving the goal mentioned above. In order to implement the adaptive controller, a rigorous mechanistic model of the biodiesel transesterification reactor was developed and validated with published experimental results. The validated model was analyzed for stability and nonlinearity. The analysis revealed that the system is stable. However, its high nonlinearity necessitates an advanced control strategy to be considered. The input‐output relationship between the effective process variables was studied and the control system synthesis revealed a two‐by‐two control system. Two adaptive control loops were then designed and tuned to optimize the performance of the controller. Finally, a comparison with conventional controllers revealed the superiority of the new control system in terms of set‐point tracking and disturbance rejection. The results of this work prove that an adequately designed adaptive control system can be used to improve the performance of the transesterification reactor.     

A new direct-synthesis tuning method for pi-controllers

A new efficient tuning method for proportional-integral (PI) controllers is proposed using overdamped closed-loop dynamics of the system. In line with other direct-synthesis and IMC methods, this new approach uses the desired closed-loop response to satisfy usual control and tuning objectives, but unlike the most other tuning methods hitherto-reported for PID controllers, it does not require that a process model be identified. Yet this new direct-synthesis (NDS) method is capable of making the controller perform the dual control functions of both good set-point tracking and disturbance rejection. Furthermore, it turns out that the new tuning method works equally well for difficult cases like large time delay and nonminimum phase processes. Finally, it can be said that this NDS method can be easily implemented and understood by the plant operating personnel because it has been developed emphasizing its on-site utility.     

Molecular weight control of poly(ethylene terephthalate) in extrusion process

A control strategy is developed to control molecular weight of recycled poly(ethylene terephthalate), PET, to overcome its degradation through an extrusion process. To obtain dynamic model of a twin screw extruder, steady‐state, and unsteady‐state experiments were performed. Discrete convolution models between inputs and outputs were obtained. Process inputs were considered as screw speed (SS), feed rate, and barrel temperatures and the output was viscosity average molecular weight (M_v) of the extrudate. SS and molecular weight of the product were chosen as the manipulated, controlled variable pair by considering singular value decomposition (SVD) technique. Model based PID controller and model predictive controller were used in the designed control scheme. By the simulation studies, both controllers were found to be successful for set‐point tracking, disturbance rejection cases; and were proven to be robust under modeling errors. POLYM. ENG. SCI., 54:459–465, 2014. © 2013 Society of Plastics Engineers     

Input/output linearization with a two-degree-of-freedom scheme for uncertain nonlinear processes

This work presents a new method to control processes with unmeasured input disturbance and random noise parametric uncertainty. The developed method takes advantage of a two-degree-of-freedom control structure in which setpoint regulation and load disturbance rejection are integrated in the controller synthesis. Input/output linearization is selected to provide the setpoint tracking ability. For disturbance rejection, the high-gain technique is used to compensate for the effect of the uncertainty. The control performance of the method is evaluated through numerical simulation of continuous stirred tank reactors with uncertainty. The simulation results show that both unmeasured disturbance and parametric uncertainty can be effectively compensated for by the proposed control method.     

Model predictive control of an industrial pyrolysis gasoline hydrogenation reactor

This study focuses on the implementation of a nonlinear model predictive control (MPC) algorithm for controlling an industrial fixed-bed reactor where hydrogenations of raw pyrolysis gasoline occur. An orthogonal collocation method is employed to approximate the original reactor model consisting of a set of partial differential equations. The approximate model obtained is used in the synthesis of a MPC controller to control the temperature rising across a catalyst bed within the reactor. In the MPC algorithm, a sequential optimization approach is used to solve an open-loop optimal control problem. Feedback information is incorporated in the MPC to compensate for modeling error and unmeasured disturbances. The control studies are demonstrated in cases of set point tracking and disturbance rejection.     

SET POINT WEIGHTED PI/PID CONTROLLERS

A systematic method is given for selection of the set point weighting parameter (b) in the PI/PID controller for stable first order plus time delay systems. The parameter b is selected to minimize the over shoot for a servo problem. The responses of the PID controllers, designed by Ziegler-Nichols method or by pole placement method, without and with the set point weighting are compared. The present method significantly reduces the overshoot.     

NONLINEAR MODEL PREDICTIVE CONTROL

Nonlinear Model Predictive Control (NMPC), a strategy for constrained, feedback control of nonlinear processes, has been developed. The algorithm uses a simultaneous solution and optimization approach to determine the open-loop optimal manipulated variable trajectory at each sampling instant. Feedback is incorporated via an estimator, which uses process measurements to infer unmeasured state and disturbance values. These are used by the controller to determine the future optimal control policy. This scheme can be used to control processes described by different kinds of models, such as nonlinear ordinary differential/algebraic equations, partial differential/algebraic equations, integra-differential equations and delay equations. The advantages of the proposed NMPC scheme are demonstrated with the start-up of a non-isothermal, non-adiabatic CSTR with an irreversible, first-order reaction. The set-point corresponds to an open-loop unstable steady state. Comparisons have been made with controllers designed using (1) nonlinear variable transformations, (2) a linear controller tuned using the internal model control approach, and (3) open-loop optimal control. NMPC was able to bring the controlled variable to its set-point quickly and smoothly from a wide variety of initial conditions. Unlike the other controllers, NMPC dealt with constraints in an explicit manner without any degradation in the quality of control. NMPC also demonstrated superior performance in the presence of a moderate amount of error in the model parameters, and the process was brought to its set-point without steady-state offset.     

Performance analysis of three advanced controllers for polymerization batch reactor: An experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC.