Model Based Tuning of Humidifying Processes with Transportation Lag

Abstract

A humidifying system with varying transportation lag was studied experimentally. Various models were tried and the system fitted a first order plus dead time model with an error of ±5%. The humidity was measured using an on‐line Yokogawa hygrometer. From the model parameters, various controllers, such as PI, Smith predictor, IMC, and IMC PID were analyzed using Matlab. The closed loop performance was studied for both regulator and servo problems. Based on rise time, settling time, and overshoot, the present study concludes that the IMC controller is best suited for this process.     

Identification and Control of Bioreactor using Recurrent Networks

Abstract

A nonlinear model predictive control (NMPC) strategy based on recurrent neural networks (RNN) is proposed for a single‐input single‐output system (SISO) to control the uncertain nonlinear process. The automatic configuration and modeling of the networks is carried out using a recurrent Elman network using back propagation through time (BPTT) with MATLAB. Identification of the process is performed with a RNN based nonlinear autoregressive with exogenous input (NARX) model and the incorporation of the developed model in the formulation of NMPC is presented. Further, the results of the NMPC is compared with a well tuned IMC based PI controller, which shows a better performance based on the rise time and settling time of the proposed NMPC scheme for the control of an unstable bioreactor.     

Model Based Tuning of Controller for Non‐Linear Hemispherical Tank Processes

Abstract

A non linear liquid level process represented by a 5 liter hemispherical tank was subjected to dynamic analysis using a step response technique. The data fitted a first order plus dead time model with an error of less than 3 percent. The level was measured using an on‐line Honeywell capacitance sensor. From the model parameters, PI and fuzzy tuned PI controllers were designed using MATLAB. The closed loop performance was studied for both the servo and regulator problems. Based on the overshoot, rise time, settling time, and ISE, it is found that the Fuzzy tuned PI controller is better suited for this process.     

Adaptive Control of Neutralization Process Using Recurrent Neural Networks

Abstract

This paper presents Recurrent neural Network (RNN) based adaptive control scheme for a pH neutralization process which is difficult to control due to its nonlinear dynamics with uncertainties. The proposed design comprises of both RNN estimator which adapts online and a RNN controller. Desired performance of the system is ensured by the parallel operation of both. The estimator weights are updated recursively by back propagation algorithm and controller weights are modified by steepest descent approach. Stability and convergence of proposed controller is guaranteed by Lyapunov stability analysis. Servo and regulatory performance of the system thus obtained by simulation is compared with a model based IMC controller. The RNN based controller is exhibits better performance as shown by the control simulation of a nonlinear pH neutralization process.     

Design of PID controllers in double feedback loops for SISO systems with set-point filters

A PID controller is widely used to control industrial processes that are mostly open loop stable or unstable. Selection of proper feedback structure and controller tuning helps to improve the performance of the loop. In this paper a double-feedback loop/method is used to achieve stability and better performance of the process. The internal feedback is used for stabilizing the process and the outer loop is used for good setpoint tracking. An internal model controller (IMC) based PID method is used for tuning the outer loop controller. Autotuning based on relay feedback or the Ziegler-Nichols method can be used for tuning an inner loop controller. A tuning parameter (λ) that is used to tune IMC-PID is used as a time constant of a setpoint filter that is used for reducing the peak overshoot. The method has been tested successfully on many low order processes.     

Extension of IMC tuning correlations for non-self regulating (integrating) processes

The filter term of a PID with Filter controller reduces the impact of measurement noise on the derivative action of the controller. This impact is quantified by the controller output travel defined as the total movement of the controller output per unit time. Decreasing controller output travel is important to reduce wear in the final control element. Internal Model Control (IMC) tuning correlations are widely published for PI, PID, and PID with Filter controllers for self regulating processes. For non-self regulating (or integrating) processes, IMC tuning correlations are published for PI and PID controllers but not for PID with Filter controllers. The important contribution of this work is that it completes the set of IMC tuning correlations with an extension to the PID with Filter controller for non-self regulating processes. Other published correlations (not based upon the IMC framework) for PID with Filter controllers fix the filter time constant at one-tenth the derivative time regardless of the model of the process. In contrast, the novel IMC correlations presented in this paper calculate a filter time constant based upon the model of the process and the user's choice for the closed-loop time constant. The set point tracking and disturbance rejection performance of the proposed IMC tunings is demonstrated using simulation studies and a bench-scale experimental system. The proposed IMC tunings are shown to perform as well as various PID correlations (with and without a filter term) while requiring considerably less controller action.     

Model Based IMC Controller for Processes with Dead Time

Abstract

A system with varying transportation lags has been experimentally studied for modeling. Modeling is performed using a step test. The tracer is sodium chloride solution whose conductivity is measured using an online conductivity analyzer. Based on the step response, the model parameters are determined and the lag processes are represented by a first order plus dead time (FOPDT) model. For the models developed, an internal model control (IMC) scheme is designed. Performance comparison, based on rise time, settling time, and overshoot, is done among the designed IMC controllers, conventional PID controllers, and Smith Predictor controllers. The present study depicts that IMC controllers outperform PID and Smith Predictor controllers.     

Enhancing the performance of parallel cascade control using Smith predictor

Parallel cascade controllers are used in chemical processing industries to improve the dynamic performance of a control system in the presence of disturbances. In the present work, a delay compensator has been incorporated in the primary loop of the parallel cascade control system. The secondary controller is designed using the internal model control (IMC) method. The primary controller is designed based on a direct synthesis method for the delay-free system. Design of controllers for slow (when the secondary loop dynamics is slow i.e. process contains poles sufficiently slower than the desired closed loop response) as well as fast dynamics (when the inner loop dynamics is fast i.e. process contains poles sufficiently faster than the desired closed loop response) of the secondary process is considered. The method provides robust control performances. Significant improvement in the closed loop performances are obtained with the delay compensator over that of a conventional parallel cascade control system. Several case studies are considered to show the advantage of the proposed method when compared to other recently reported methods.     

Optimal controller synthesis for second order time delay systems with at least one RHP pole

An optimal H₂ minimization framework is proposed in this paper for devising a controller of PID in nature, based on a refined IMC filter configuration. The tuning strategy is for controlling time delay system with at least one pole which falls on the right half of the s-plane. An underdamped model based filter is used in place of the unity damping ratio (critically damped) filter available in the literature to improve the reset action. The method has a single adjustable closed loop tuning parameter. Guidelines have been provided for choosing the pertinent tuning parameter based on the sensitivity function. Simulation work has been executed on diverse unstable models to support the advantages of the proposed scheme. The proposed controller yields improved performances over other recently reported tuning techniques in the literature. Experimental implementation is carried out on an inverted pendulum for demonstrating the practical applicability of the present method. The efficacy of the intended controller design is quantitatively analyzed using the time integral performance index.     

Design of a TRFN Controller for a Nonlinear Multivariable Process

Abstract

Feedback architecture is found to be more suitable for controlling dynamic processes, as it utilizes the past information of the process variables as against a controller designed using a feedforward structure that utilizes only the present information about the process variables. A comparative analysis of having a recurrent fuzzy controller over a conventional fuzzy controller in a control loop involving a non-linear dynamic system is enunciated using a laboratory two-tank heating process. A considerable improvement in performance is obtained by employing the recurrent structure in place of the conventional fuzzy controller. In addition, this proposed control strategy is numerically more efficient than the feedforward fuzzy structure. Results illustrate the effectiveness of the proposed structure.     

考虑延迟的线控转向二自由度内模控制

针对线控转向系统中由于信号传输、机械间隙和摩擦等因素引起的响应延迟问题，设计了二自由度内模控制策略以提高转角跟踪精度。将延迟模型与线控转向系统模型相结合，构建新的名义模型，为避免引入非最小相位项，采用全极点近似方法将延迟环节线性化，求解跟踪控制器和抗干扰控制器。与名义模型不含延迟环节的二自由度内模控制以及经典PID控制相比较，通过MATLAB/Simulink仿真给出了延迟量对三种方法跟踪性能的影响。比较了延迟量对采用全极点近似、Taylor近似和Padé近似的二自由度内模控制跟踪性能的影响。经线控转向台架试验验证，采用全极点近似的二自由度内模控制跟踪精度较高，对延迟的适应性较好。     

采用内模控制理论的双馈感应风机鲁棒控制器设计

针对工程中双馈感应电机转子电流控制器参数整定的问题,提出一种利用内模控制理论设计转子电流控制器的鲁棒控制方法。首先定义内模控制的灵敏度函数和互补灵敏度函数,并推导双馈感应电机转子电流控制系统传递函数,建立了转子电流内环的内模数学模型。IMC控制器的设计以平方积分误差值和鲁棒稳定M值为准则,并与传统比例积分控制器进行比较。通过对1.5 MW双馈感应电机的MATLAB/SIMULINK仿真表明,本文方法稳态跟踪精度高、动态响应快、对模型误差和外界干扰具有较好的鲁棒性。最后在11 k W的双馈风机实验平台上验证了所提方法的有效性。     

Measurement and Control of Process using Soft Computing

Abstract

Control of process parameters is considered to be a critical problem in the process industry. The process considered for modeling is a liquid level system. The model identification and parameter selection are approximated to a First Order Plus Dead Time (FOPDT). Here, the controller design is based on a conventional Proportional–Integral (PI) controller and intelligent controller like Fuzzy Logic Controller (FLC). The objective of the current study is to design control strategies in real time using MATLAB software interfaced with Adam's data acquisition module. A comparative analysis based on FLC with a conventional controller is presented, with various time domain specifications. It is found that, under servo and regulatory changes, FLC shows an improved performance over its conventional techniques based on performance measures like peak time, settling time, overshoot, Integral Square Error (ISE) and Integral Absolute Error (IAE).     

Design of RTDA controller for industrial process using SOPDT model with minimum or non-minimum zero

This research paper focuses on the design and development of simplified RTDA control law computation formulae for SOPDT process with minimum or non-minimum zero. The design of RTDA control scheme consists of three main components namely process output prediction, model prediction update and control action computation. The systematic approach for computation of the above three components for SOPDT process with minimum or non-minimum zero is developed in this paper. The design, implementation and performance evaluation of the developed controller is demonstrated via simulation examples. The closed loop equation, block diagram representation and theoretical stability derivation for RTDA controller are developed. The performance of proposed controller is compared with IMC, SPC, MPC and PID controller and it is demonstrated on Industrial non-linear CSTR process.     

Modeling and controller performance assessment for a switched reluctance motor drive based on setpoint relay

This paper considers the implementation of a current control method for switched reluctance motors (SRMs) and presents a novel approach to the accurate on-line modeling of an SRM drive. A simple autotuning technique for the SRM drives using a PWM controller is considered. Furthermore, conventional PI control and Internal Model Control (IMC) are considered to validate this method and present corresponding robust control analysis for the process. The control structures are comparatively analyzed using standard robustness measures for stability and performance. The proposed PWM controller is simulated and a hardware prototype is then implemented using digital signal processor control to evaluate the method using a 12/8, three-phase SRM. The experimental results of the SRM drive model validates the performance of the current loop.     

线控转向系统的前轮转角跟踪策略研究

研究通过对线控转向系统进行主动控制,可靠并准确地得到期望的前轮转角。基于建立的线控转向系统数学模型,使用非线性自回归模型确定其系统参数,设计内模控制器跟踪车辆的期望运动状态。通过开环和闭环试验,对控制器在典型的驾驶工况下的有效性进行了验证。通过与PID控制器的结果对比,证明所设计的内模控制器能提供更好的控制性能。为减少驾驶员的操纵负担并确保车辆在不同行驶条件下的稳定性,根据不同工况下的测试结果提出基于增益不变的变角传动比控制策略,并设计了滑模控制器跟踪期望横摆角以实现主动转向。通过对内模和滑模控制器的联合仿真结果表明,所设计的控制器可实现期望横摆角度的精确跟踪,显著提高车辆的操纵灵活性和稳定性。     

Optimal solution,quantitative performance estimation,and robust tuning of the simplifying controller

Recently, a simplifying controller has been proposed based on the principal of simplification of the control system transfer functions, which offers improved control for processes with a large time delay. It is the purpose of this complementary paper to give a comprehensive analysis on the scheme. First, the relationship among the simplifying controller, the Smith predictor, and the internal model control are discussed. Second, an analytical design procedure is developed based on internal model control (IMC) and optimal solution is derived. Third, the problem of estimating the time domain performance of the closed loop system, quantitatively, is discussed. Fourth, a simple robust tuning procedure is presented. Numerical examples are provided to illustrate the proposed method.