Integrating process and controller models for the design of self-optimizing control

The steady-state behavior of an existing plant depends on the independent input variables, process equipment and process controllers. This paper presents a method for formulating models that represent the effects of controllers when they are included within a steady-state process flowsheet. The method replaces the controller equations with the equivalent stationarity conditions representing the relationship between the controlled variables and the implemented manipulated variables at steady state. The method is demonstrated for the centralized multivariable Dynamic Matrix Control algorithm applied to two processes, binary distillation and gasoline blending. The integrated process and control system simulation is used to design controllers that improve the profitability of processes without extensive real-time calculations; this is sometimes termed self-optimizing control. For both processes, controllers were designed that yielded higher profit than standard control methods and that approached the highest possible profit achieved by frequent real-time optimization.     

Control structure selection of increased-pressure extractive distillation process for DMC-MeOH azeotropic mixture

Producing dimethyl carbonate (DMC) as a green chemical with the desired purity is important in the industry. Although studies on the steady-state design of energy-efficient extractive distillation processes are important for the purification of DMC-methanol (DMC-MeOH) azeotropic mixtures, the dynamic controllability of these processes is also critical in the case of feed condition changes, and it should be investigated carefully. Results of the limited studies in the literature show that changing the operating pressures in extractive distillation processes might have different effects on the dynamic controllability of different systems. Thus, in this study, alternative control strategies are developed for a recently proposed increased-pressure extractive distillation process to separate DMC-MeOH mixture. All control structures are designed using inferential temperature controllers, which have a general acceptance in industrial applications. Effects of different ratio controllers are investigated by evaluating the dynamic responses of control structures for disturbances in feed flowrate and composition. Two metrics including integral absolute error and steady-state deviation of purities are used in the evaluation of alternatives. Results of dynamic simulations show that a control structure including reflux ratio controller is not a suitable strategy for this process. It is demonstrated that a control structure including reflux to feed ratio controller for both distillation columns is necessary for the robust and efficient control of a pressure-increased extractive distillation process. These efficient dynamic results support the economic advantage of increased-pressure extractive distillation process separating DMC-MeOH azeotropic mixtures.     

Set point weighted modified Smith predictor with PID filter controllers for non-minimum-phase (NMP) integrating processes

A simple modified Smith predictor design for the control of non-minimum-phase integrating processes with/without a zero is proposed. The method consists of two controllers, one for set point tracking and the other for disturbance rejection. The controllers are designed based on direct synthesis approach. The set point tracking controller is designed as a proportional-integral-derivative (PID) with lag filter and the disturbance rejection controller is designed as a proportional-derivative (PD) with lead lag structure. Typical types of integrating processes with/without zero are considered and the controllers are designed in a unified approach for all the types of integrating processes. Extensive simulation studies have been carried out on various integrating processes with/without zero. The present method gives good disturbance rejection response and significant improvement when compared to the recently reported methods in the literature.     

Differential-geometric model-based control (DGMBC): A software package for controller design

This paper presents a new software package, called differential-geometric model-based control (DGMBC), which carries out symbolic manipulations to automatically generate differential-geometric, model-based controllers and subsequently tests the designed controller. This prototype software was developed to simplify the industrial implementation and testing of differential-geometric, model-based controllers on lumped-parameter processes. DGMBC has a user-friendly interface that allows a user to enter process model equations and parameters easily. The user interface was developed using Visual Basic and linked to MATHEMATICA using MathLink. The user enters the process model (set of ordinary differential equations), and the software generates an analytical model-based controller, if an analytical solution exists. The resulting analytical model-based controller (set of ordinary differential and algebraic equations) can be in FORTRAN, C, or MATLAB format. DGMBC can also simulate the closed-loop process responses. The application and implementation of DGMBC 1.0 are shown using three chemical and biochemical process examples with varying levels of complexity. An analytical model-based controller is designed for each of the processes, and simulation results showing the closed-loop process responses are presented.     

微结构注塑机注射速度控制及仿真研究

为了对注射速度进行精密控制,建立起一个液压控制系统,对该系统中影响注射速度的相关器件进行结构分析并且建立数学模型,针对注射速度非线性以及时变等特性,设计一种自适应模糊PID控制器,利用MATLAB软件建立仿真模型,对两种控制器下的注射速度曲线进行对比分析。结果表明,与传统PID控制器相比,自适应模糊PID控制器具有注射速度响应更迅速,稳态无误差和鲁棒性能好等优势。     

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.     

A tuning of the nonlinear PI controller and its experimental application

Many industrial chemical process control systems consist of conventional PID and nonlinear controllers, even though many advanced control strategies have been proposed. In addition, nonlinear control methods are widely used even for linear processes to achieve better control performance compared with linear PID controllers. However, there are few tuning methods for these nonlinear controllers. In this work, we suggest new controller tuning methods for the error square type of nonlinear PI controller. These control methods can be applied to a large number of linear and nonlinear processes without changing control structures. We also propose new tuning rules for integrating processes. In addition, we suggest application guidelines for performing the proposed tuning rules at the pilot scale multistage level control system. Finally, in this work we confirmed good control performances of the proposed tuning methods through both simulation studies and experimental studies.     

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.     

Modeling, simulation and control of a methanol synthesis fixed-bed reactor

In this paper, the dynamic behavior and control of the low pressure methanol synthesis fixed bed reactor have been investigated. For simulation purpose, a heterogeneous one-dimensional model has been developed. First, the reactor simulation is carried out under steady-state condition and the effects of several parameters such as shell temperature, feed composition (especially CO₂ concentration) and recycle ratio on the methanol productivity and reactor temperature profile are investigated. Using the steady state model and a trained feedforward neural network that calculates the effectiveness factor, an optimizer which maximizes the reactor yield has been developed. Through the dynamic simulation, the system open loop response has been obtained and the process dynamic is approximated by a simple model. This model is used for the PID controller tuning and the performances of fixed and adaptive PID controllers are compared for load rejection and set point tracking. Finally the proposed optimizer is coupled with a controller for online optimization and hot spot temperature protection.     

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.     

模糊自适应PI控制在空调系统中的研究

以空气焓差法试验台空调系统的温度控制系统为具体仿真对象建立了数学模型,该空调系统可以看作是一阶惯性加纯滞后的环节,而且对象的过程参数和时延时间是时变的,传统的PID控制无法获得理想的控制效果。提出了一种无需辨识环节的具有智能的模糊自适应PI的控制算法并将其应用在该空调系统中,该算法对模糊控制和PI控制进行有机结合,根据实际控制经验,通过模糊控制规则对控制回路中PI控制器的参数进行实时整定,并将该控制算法和经过良好整定的PI控制器在空调系统中的控制性能进行比较。仿真结果表明,模糊自适应PI控制提高了系统的鲁棒性、减小了超调量、提高了抗干扰能力、缩短了调整时间。     

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.     

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.     

Control structure comparison for three-product Petlyuk column

The focus of this paper is to investigate different control structures (single-loop PI control) for a dividing wall (Petlyuk) column for separating ethanol, n-propanol and n-butanol. Four control structures are studied. All the results are simulations based on Aspen Plus. Control structure 1 (CS1) is stabilizing control structure with only temperature controllers. CS2, CS3 and CS4, containing also composition controllers, are introduced to reduce the steady state composition deviations. CS2 adds a distillate composition controller (CCDB) on top of CS1. CS3 is much more complicated with three temperature-composition cascade controllers and in addition a selector to the reboiler duty to control the maximum controller output of light impurity composition control in side stream and bottom impurity control in the prefractionator. CS4 adds another high selector to control the light impurity in the sidestream. Surprisingly, when considering the dynamic and even steady state performance of the proposed control structures, CS1 proves to be the best control structure to handle feed disturbances inserted into the three-product Petlyuk column.     

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。     

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。     

ADAPTIVE DOMINANT POLE DESIGN OF PID CONTROLLERS BASED ON A SINGLE CLOSED-LOOP TEST

A novel method, based on a single experimental test under proportional feedback, has been developed to tune PID controllers on-line. The tuning method involving an identification scheme and a dominant pole design technique is ideal for automatic tuning. It also provides an adaptive algorithm to adjust the controller settings to achieve the desirable control performance satisfying the prescribed decay ratio and stability margin. A simulation study demonstrates that the method is valid for processes with large dead-times as well as open-loop underdamped processes.     

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.     

Expert control of DO in the aerobic reactor of an activated sludge process

An expert control structure is proposed for the control of dissolved oxygen (DO) in a Nitrification Denitrification Biological Excess Phosphorus Removal (NDBEPR) plant to account for the several processes that are influenced by the DO concentration in the aerator. In the scheme a supervisory fuzzy controller determines the set point of an inner DO control loop where an Adaptive Robust Generic Model Control (ARGMC) controller is used. The fuzzy supervisory control has a hierarchical structure. Off-line measurements of biological parameters of influent and effluent streams can be used to periodically update the set points of the fuzzy controllers. The complete control scheme has been designed for an actual plant and tested by a simulation programme based on the n. 2 IAWQ model for the biological reactors and on separate models of the clarification and thickening phases for the settler. Simulation and experimental results show that good operation conditions can be obtained.     

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。