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.     

PID controller design for integrating processes with time delay

A simple IMC-PID controller design technique is proposed on the basis of the IMC principle for two representative integrating processes with time delay. Further, it is extended to integrating processes with negative and positive zero as well. The proposed PID controller design method is mainly focused on the disturbance rejection, which causes the overshoot in the setpoint response, and a two-degree-of-freedom (2DOF) control structure is used to eliminate this overshoot. The simulation results show the superiority of the proposed tuning rule over other existing methods, when the controller is tuned to have the same robustness level by evaluating the peak of the maximum sensitivity (Ms). The closed loop time constant (λ) has only one user-defined tuning parameter in the proposed method. A guideline is suggested for the selection of λ for different robustness levels by evaluating the value of Ms over a wide range of θ/τ ratios.     

Analytical design of PID controller cascaded with a lead-lag filter for time-delay processes

An analytical method for the design of a proportional-integral-derivative (PID) controller cascaded with a second-order lead-lag filter is proposed for various types of time-delay process. The proposed design method is based on the IMC-PID method to obtain a desired, closed-loop response. The process dead time is approximated by using the appropriate Pade expansion to convert the ideal feedback controller to the proposed PID·filter structure with little loss of accuracy. The resulting PID·filter controller efficiently compensates for the dominant process poles and zeros and significantly improves the closed-loop performance. The simulation results demonstrate the superior performance of the proposed PID·filter controller over the conventional PID controllers. A guideline for the closed-loop time constant, λ, is also suggested for the FOPDT and SOPDT models.     

Closed-loop automatic tuning of PID controller for nonlinear systems

In this paper, a robust control system is first proposed which is suitable for the control of a class of nonlinear systems. A parallel connection of a relay to a proportional integral derivative (PID) controller collectively forms the robust controller. The relay ensures robust control by providing a high feedback gain, but it also induces a control chattering phenomenon. Instead of viewing chattering as an undesirable yet inevitable feature, the chattering signals are used as natural excitation signals for identifying an equivalent PID controller using the recursive least squares algorithm. No other explicit input signal is required. Analysis is provided on the stability properties of the control scheme. Simulation results for the level control of fluid in a spherical tank using the scheme are presented.     

Improved fourier transform to estimate frequency responses

For the automatic tuning of PID controllers, a new identification method is proposed to estimate the frequency responses of the process from the activated process input and output. It can extract many more frequency responses as well as guarantee better accuracy compared with the previous describing function analysis algorithm. Also, the proposed method can be applied to the case that the initial part of the activated process input and output is periodic (cyclic-steady-state), whereas the previous method using the modified Fourier transform cannot incorporate the case.     

Assessment of controller performance: a relay feedback approach

Assessment of control loop performance is one of the important tasks to be carried out in a plant, regardless of the control strategy. The present work utilizes the shape information from single relay feedback test to assess the performance of a feedback system. The process considered is a typical first-order plus dead time process and the controller used is PI type of controller. An ideal relay is introduced in the feedback loop before the controller. The shape of the relay output characterizes the performance of the controller. The mismatch in the integral time can also be observed from the shape. Based on the shape information, analytical expressions for relay feedback responses are derived and straightforward procedures are evolved to assess the performance of the controller. The proposed scheme assesses the controller performance and computes the new tuning parameters, in case retuning of the controller is necessary. The robustness of the method is also tested for second-order plus dead time as well as for higher order systems. More importantly the present approach employs only one relay test for (1) assessment and (2) retuning of the controller. It provides a reliable way that is compatible even to a non-expert operator to assess the controller performance.     

Multiloop PID controller design using partial least squares decoupling structure

The goal of this paper is to identify and control multi-input multi-output (MIMO) processes by means of the dynamic partial least squares (PLS) model, which consists of a memoryless PLS model connected in series with linear dynamic models. Unlike the traditional decoupling MIMO process, the dynamic PLS model can decompose the MIMO process into a multiloop control system in a reduced subspace. Without the decoupler design, the optimal tuning multiloop PID controller based on the concept of general minimum variance and the constrained criteria can be directly and separately applied to each control loop under the proposed PLS modeling structure. Several potential applications using this technique are demonstrated.     

Improved system identification method for Hammerstein-Wiener processes

We propose a new system identification method for Hammerstein-Wiener processes, in which an input static nonlinear block, a linear dynamic block, and an output static nonlinear block are connected in a series. The proposed method can estimate the model parameters in a very simple way without solving the full-dimensional nonlinear optimization problem by activating the process with a specially designed test signal, composed of a relay feedback signal, a binary signal and a multi-step signal. The proposed method analytically identifies the output nonlinear static function and the input nonlinear static function from the relay signal and the multi-step signal, respectively. The linear dynamic subsystem is identified from the relay feedback signal and the binary signal with existing well-established linear system identification methods. We demonstrate with a simple example that the proposed method can be successfully applied to identify the Hammerstein-Wiener-type nonlinear process.     

模糊PID控制在梭式窑控制系统中的应用研究

将模糊控制和普通的PID控制相结合,提出了一种基于模糊控制规则的模糊PID控制器的设计方法并将其应用于梭式窑温度控制系统中。试验表明,这种方法比普通的PID控制方法精度高,超调量减少,具有较强的可靠性。     

ADAPTIVE PID CONTROL WITH AN ADJUSTABLE IDENTIFICATION INTERVAL

Adaptive PID control with an adjustable identification interval is proposed. The difficulty of choosing a suitable sampling time for control systems is prevented. The identification algorithm depends on that the identification interval is different from the sampling interval. Tuning of the PID controller is based on an adaptive first-order plus dead time model at each identification step. The model is obtained directly from an identified second-order one. Two illustrative examples are presented to show the considerable promise that the method exhibits.     

Control of pH processes based on the genetic algorithm

In this work, we propose a PID control strategy based on the genetic algorithm coupled with cubic spline interpolation method for the control of pH processes. The control scheme proposed in the present work consists of closed-loop identification based on the genetic algorithm and cubic spline method. First, we compute the parameters (K_C, Τ_I, Τ_D) of the PID controller using relay feedback and apply these parameters to control the pH Process. Then approximate linear models corresponding to each pH range are obtained by the closed-loop identification based on closed-loop operation data. The optimal parameters of the PID controller at each pH region are then computed by using the genetic algorithm. From numerical simulations and control experiments we could achieve better control performance compared to the conventional fixed gain PID control method. This paper is dedicated to Professor Hyun-Ku Rhee on the occasion of his retirement from Seoul National University.     

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.     

OPTIMAL TUNING OF PID CONTROLLERS FOR SINGLE AND CASCADE CONTROL LOOPS

Design of one parameter tuning of three-mode PID controller was developed in this present study. The integral time and the derivative time of the controller were expressed in terms of the time constant and dead time of the process. Only the proportional gain was observed to be dependent on the implemented tunable parameter in which the stable region could be predetermined by the Routh test. Extension of the concept towards designing cascade PID controllers was straightforward such that only two parameters for the inner and outer PID controllers required to be tuned, respectively. The optimal tuning correlative formulas of the proportional gain for single and cascade control systems were obtained by the least square regression method.     

ADAPTIVE ACTUAL PID CONTROL WITH AN ADJUSTABLE IDENTIFICATION INTERVAL

A method of design for an adaptive PID controller in an “actual” form is developed. The controller is expressed as an ideal PID controller with a low-pass filter. The parameters of the controller are determined by using the ITAE criterion based on a first-order plus dead time model which is directly obtained from an identified second-order model. In comparison with the ideal PID controller, the actual one gives better results especially for systems with noises.     

New results on VRFT design of PID controller

Virtual reference feedback tuning (VRFT) design method can be applied to determine the parameters of a PID controller from the available process input and output data without resorting to the identification of a process model. Although it is an attractive alternative to the popular model-based controller design methods, the existing results are restricted to the linear systems. In this paper, an adaptive VRFT design method with application to the adaptive PID controller design is proposed. In addition, the relationship between the VRFT and IMC designs is analyzed as well. Simulation results are presented to illustrate the advantage of the adaptive VRFT design over the conventional VRFT design.     

Optimal PID controller tuning using stochastic programming techniques

We argue that stochastic programming provides a powerful framework to tune and analyze the performance limits of controllers. In particular, stochastic programming formulations can be used to identify controller settings that remain robust across diverse scenarios (disturbances, set‐points, and modeling errors) observed in real‐time operations. We also discuss how to use historical data and sampling techniques to construct operational scenarios and inference analysis techniques to provide statistical guarantees on limiting controller performance. Under the proposed framework, it is also possible to use risk metrics to handle extreme (rare) events and stochastic dominance concepts to conduct systematic benchmarking studies. We provide numerical studies to illustrate the concepts and to demonstrate that modern modeling and local/global optimization tools can tackle large‐scale applications. The proposed work also opens the door to data‐based controller tuning strategies that can be implemented in real‐time operations. © 2017 American Institute of Chemical Engineers AIChE J, 64: 2997–3010, 2018     

On-line identification of interacting two-tank system

In order to demonstrate the effectiveness of the process identification algorithm, on-line parameter estimator is evaluated experimentally by using two-tank system with interaction. On-line parameter estimator used in this paper is based on a recursive parameter estimation algorithm. MIMO linear, bilinear and quadratic models based on ARMA model are used to identify two-tank system. A quadratic model for two-tank system with interaction is developed to confirm the propriety of MIMO quadratic model used in identification of two-tank system. The results of on-line identification experiments on the two-tank system show that the estimated parameters of each model converge and the output tracking errors are bounded by disturbance bound. But, the quadratic model showed the best convergence.     

System identification and PID controller tuning using band-pass filters

An online recursive system identification technique using band-pass filters has been developed to estimate the continuous-time frequency response of any process control system at a number of discrete frequencies. Tuning of PID controllers employs a gradient optimization technique, based on the estimated discrete frequency response of the process rather than a transfer function model of the process. The performances of the identification technique and controller tuning algorithm are demonstrated by a simulation and by experimental results on a distillation column composition control.     

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.     

Simulink仿真在PID控制教学中的探索与设计

在“过程控制系统”的教学中,传统的理论教学往往使学生对教学内容缺乏感性认识,感觉枯燥,记忆不深刻。将Simulink仿真应用到PID控制部分教学中,采用建模仿真带动理论教学的方法,让学生对PID控制有更为直观的认识。教学实践表明,该方法增强了学生的学习积极性,提高了他们对过程控制系统的分析与设计能力,取得了良好的课堂教学效果。