基于迭代继电反馈的多变量PID控制器自整定

PID控制是工业过程中最常用的控制方法,但在实际生产过程中,被控过程往往是多变量、有耦合的,常规PID控制器参数往往整定不良、性能欠佳,对运行工况的适应性较差。为此,将迭代反馈理论和继电整定方法有机结合起来,提出一种适用于存在耦合的多变量系统PID控制器的参数整定方法。运用该方法整定PID参数,不需要被控对象的数学模型,而且具有速度快、效果好等优点。     

微型燃气轮机的新型神经网络控制的研究

燃机控制系统是一种多变量、非线性、时变的系统,对微型燃气轮机的转速控制器进行了深入研究.PID控制应用广泛,但在实际应用中,其参数整定仍未得到较好的解决.因此,设计了一种新的神经网络PID控制器作为主控制器,通过神经网络所具有的任意非线性表达能力,可以通过对系统性能的学习来实现具有最佳组合的PID控制,确保系统的稳定性、快速性和准确性.大量的仿真证明,该算法具有良好的控制效果.     

模糊PID控制在葡萄酒发酵过程中的应用

针对某葡萄酒厂的发酵过程进行研究,由于其特性随时间变化,需要适时地对PID控制器的参数进行整定.常规的PID控制器没有自适应能力,只能依靠人工重新整定参数,这很难适应参数连续变化的发酵过程.因此需要一种有自适应能力的控制器,经对发酵过程的常规PID控制和模糊PID控制进行仿真和对比,最终选用最优控制方案.     

可控受限多变量耦合系统的智能控制

针对可控受限多变量耦合系统,提出了一种基于对角递归神经网络(DRNN)整定的PID混合解耦控制。采用对角递归神经网络来辨识系统模型,进而对PID控制器参数进行整定,实现多变量解耦控制。通过对多变量耦合控制系统的设计和实时控制,实际控制结果达到了解耦控制的要求,并具有无超调、响应速度快、控制精度高等特点。     

智能自整定PID在药剂温度控制系统中的应用

针对一些工业控制对象中出现的纯时滞、大惯性、时变不确定性等问题, 提出了基于模糊逻辑来智能调整PID控制器参数的方法, 并且将其应用到了一类药剂温度控制系统当中. 另外, 还给出了此方法的硬件和软件实现. 最后, 实际系统的运行结果表明此方法能够降低被控量超调、提高控制精度并且增强系统的鲁棒性, 证明其在一类过程对象的应用中优于传统的PID控制方法.     

An alternative structure for next generation regulatory controllers: Part I: Basic theory for design, development and implementation

Even though employed widely in industrial practice, the popular PID controller has weaknesses that limit its achievable performance, and an intrinsic structure that makes tuning not only more complex than necessary, but also less transparent with respect to the key attributes of the overall controller performance, namely: robustness, set-point tracking, and disturbance rejection. In this paper, we propose an alternative control scheme that combines the simplicity of the PID controller with the versatility of model predictive control (MPC) while avoiding the tuning problems associated with both. The tuning parameters of the proposed control scheme are related directly to the controller performance attributes; they are normalized to lie between 0 and 1; and they arise naturally from the formulation in a manner that makes it possible to tune the controller directly for each performance attribute independently. The result is a controller that can be designed and implemented much more directly and transparently, and one that outperforms the classical PID controller both in set-point tracking and disturbance rejection while using precisely the same process reaction curve information required to tune PID controllers. The design, implementation and performance of the controller are demonstrated via simulation on a nonlinear polymerization process.     

Interval-model-based global optimization framework for robust stability and performance of PID controllers

PID controller structure is regarded as a standard in the control-engineering community and is supported by a vast range of automation hardware. Therefore, PID controllers are widely used in industrial practice. However, the problem of tuning the controller parameters has to be tackled by the control engineer and this is often not dealt with in an optimal way, resulting in poor control performance and even compromised safety. The paper proposes a framework, which involves using an interval model for describing the uncertain or variable dynamics of the process. The framework employs a particle swarm optimization algorithm for obtaining the best performing PID controller with regard to several possible criteria, but at the same time taking into account the complementary sensitivity function constraints, which ensure robustness within the bounds of the uncertain parameters’ intervals. Hence, the presented approach enables a simple, computationally tractable and efficient constrained optimization solution for tuning the parameters of the controller, while considering the eventual gain, pole, zero and time-delay uncertainties defined using an interval model of the controlled process. The results provide good control performance while assuring stability within the prescribed uncertainty constraints. Furthermore, the controller performance is adequate only if the relative system perturbations are considered, as proposed in the paper. The proposed approach has been tested on various examples. The results suggest that it is a useful framework for obtaining adequate controller parameters, which ensure robust stability and favorable control performance of the closed-loop, even when considerable process uncertainties are expected.     

Optimal automatic tuning of active damping PID regulators

An automatic tuning method for the PID controller in single-input-single-output control loops involving processes with conjugate complex poles is presented. The development of the method lies in the principle of the well known Magnitude Optimum criterion and considers two fundamental constraints met frequently in many industry applications; (1) the existence of a poor process model and (2) access to the output of the process and not to its states. The presentation of the method is carried out in two steps. Over the first step, the straightforward PID tuning via the Magnitude Optimum criterion in the ideal case of a known single input-single output linear process model reveals a feature of the method called ‘the preservation of the shape of the step and frequency response’ of the final closed-loop control system. This shape is characterized by specific performance in terms of overshoot (4.4%), settling and rise time of the closed-loop control system. Over the second step, the PID controller parameters are tuned automatically so that the aforementioned performance is achieved. In this case, the existence of a poor process model is adopted assuming access to its output and not to its states. For applying the method an open-loop experiment of the process is carried out which serves for (1) initializing the algorithm and (2) determining the two zeros of the proposed PID controller. The method starts with I-Lag control action to the process by tuning the integral gain. After this tuning is over, the parasitic time constant of the closed-loop system is estimated. I-Lag control is then turned into PID control and the integrator's time constant of the PID controller is tuned accordingly, so that the shape of the control loop's output exhibits the aforementioned performance. Since the tuning of the PID controller is based on the Magnitude Optimum criterion, optimal disturbance rejection is expected to be achieved at the output of the controlled process. The potential of the proposed method is justified via simulation examples for two benchmark process models met frequently in various industry applications.     

基于RBF网络自整定PID控制的应用研究

经典PID的控制参数难以精确整定，且依赖于对象的数学模型，故自适应性较差，很难适应具有非线性、时变不确定性的被控对象，控制精度难以保证。该文对纯滞后工业对象提出了一种基于RBF神经网络PID参数自整定的控制方法，采用将RLS算法和梯度法相融合的新型学习算法，并将这种控制方法与PID控制器相结合应用于纯滞后工业对象中，克服了不确定性对控制对象性能的不利影响，解决了传统PID控制鲁棒性差，及需要预先知道受控对象精确数学模型的问题。仿真结果表明了该方法的鲁棒性和跟踪性能均优于传统PID控制方法。     

Fuzzy IMC-PID控制器的设计及仿真研究

从IMC结构出发,提出了一种基于fuzzy、PID控制的Fuzzy IMC-PID控制器,对工业过程中时滞系统纯滞后环节一阶Pade近似后,由内模整定得到PID控制器的参数整定值,再依据合适的模糊控制规则,对其进行在线二次自整定。借助MATLAB工具箱进行仿真,结果表明,该控制器具有内模、模糊、PID控制器的优点,超调小、调节性能好、鲁棒性强。对于大纯滞后或非线性系统能够较好地工作,可以推广应用于一般工业过程控制中。     

PID controller design of TITO system based on ideal decoupler

The proposed method for designing multivariable controller is based on ideal decoupler D(s) and PID controller optimization under constraints on the robustness and sensitivity to measurement noise. The high closed-loop system performance and robustness are obtained using the same controller in all loops. The method is effective despite the values and positions of the right half plane zeros and dead-times in the process transfer function matrix G_p(s). The validity of the proposed multivariable control system design and tuning method is confirmed using a test batch consisting of Two-Input Two-Output (TITO) stable, integrating and unstable processes, and one Three-Input Three-Output (TITO) stable process.     

Optimal-tuning PID controller design in the frequency domain with application to a rotary hydraulic system

In this paper a new PID controller design scheme that uses optimisation in the frequency domain is proposed for industrial process control. An optimal-tuning PID controller is designed to satisfy a set of frequency-domain performance requirements: gain margin, phase margin, crossover frequency and steady-state error. Using an estimated process frequency response, the method can provide optimal PID parameters even in cases where the process dynamics are time variant. This scheme is demonstrated through its application to a rotary hydraulic system and its performance is compared with six alternative PID tuning rules.     

Analytical method of PID controller design for parallel cascade control

An analytical method of PID controller design is proposed for parallel cascade control. Firstly, a general structure for parallel cascade control is proposed that takes both setpoint and load disturbance responses into account. Analytical tuning rules for the PID controllers are then derived for the general process model by employing the IMC design procedure. The proposed method offers a simple and effective way to obtain the PID controller rules for parallel cascade control system which takes into account the interaction between primary and secondary control loops. The simulation results illustrate the application of the proposed method and demonstrate its superiority compared to several alternatives.     

基于模糊自适应PID的随动系统设计与仿真

研究随动控制系统优化问题,常规PID控制器参数调试凭经验,导致系统性能不高。为了提高系统快速性和稳定性,提出并设计了模糊自适应PID控制器,可以对参数进行在线修正以使系统性能最优。可采用经验法调试的常规PID参数为初值,再用模糊化和近似推理等对参数进行在线修正,从而使系统性能达到最优。既具有模糊控制灵活性和适应性强的优点,又具有PID控制精度高的优势。通过设计模糊自适应PID控制器,以某二维随动转台系统为对象,在MATLAB环境中进行了仿真,并与常规PID控制器的性能进行了对比,结果表明模糊自适应PID控制器的响应特性优于传统的PID控制器,响应速度更快,稳态精度更高,为随动系统优化设计提供了依据。     

Simultaneous closed-loop tuning of cascade controllers based directly on set-point step-response data

This study presents a novel closed-loop tuning method for cascade control systems, in which both primary and secondary controllers are tuned simultaneously by directly using set-point step-response data without resorting to process models. The tuning method can be applied on-line to improve the performance of existing underperforming cascade controllers by retuning controller parameters, using routine operating data. The goal of the proposed design is to obtain the parameters of two proportional-integral-derivative (PID)-type controllers, so that the resulting inner and outer loops behave as similarly as possible to the appropriately specified reference models. The tuning rule and optimization problem related to the proposed design are derived. Based on the rationale behind cascade control, the secondary controller is designed based on disturbance rejection to quickly attenuate disturbances. The primary controller is designed to accurately account for the inner-loop dynamics, without requiring an additional test. In addition, robustness considerations are included in the proposed tuning method, which enable the designer to explicitly address the trade-off between performance and robustness for inner and outer loops independently. Simulation examples show that the proposed method exhibits superior control performance compared with the previous (model-based) tuning methods, confirming the effectiveness of this novel tuning method for cascade control systems.     

An Intelligent Design for a PID Controller for Nonlinear Systems

The proportional integral derivative (PID) controller is the most frequently used controller design for industrial applications because of its favorable response and simplicity of adjustment. However, PID manual tuning is traditionally based on engineering experience, and adjusting nonlinear or unknown systems is extremely difficult. In promoting an intelligent controller design theory that can be applied to the control of various systems, this paper proposes a nonlinear control design method that involves determining the optimal solution and obtaining the transfer function of an unknown system by using sequential quadratic programming. In addition, this paper presents a case study of an induction motor V/F speed control to demonstrate the effectiveness of the proposed method based on MATLAB simulation. The results prove that the design of the proposed intelligent PID controller is more robust than traditional controller designs.     

基于PID参数整定的线性自抗扰控制参数整定

线性自抗扰控制(linear active disturbance rejection control,LADRC)是不依赖于被控对象的数学模型,在工业过程中具有极大的应用前景,LADRC参数整定是其在工业过程中能否应用的重要环节.鉴于实际工业控制中大都采用PID控制器,通过对二阶LADRC结构与其状态观测器的传递函数...     

Maximum sensitivity based fractional IMC–PID controller design for non-integer order system with time delay

A simple approach with a small number of tuning parameters is a key goal in fractional order controller design. Recently there have been a number of limited attempts to bring about improvements in these areas. In this paper, a new design method for a fractional order PID controller based on internal model control (IMC) is proposed to handle non-integer order systems with time delay. In order to reduce the number of tuning parameters and mitigate the impact of time delay, the fractional order internal model control scheme is used. Considering the robustness of the control system with respect to process variations and model uncertainty, maximum sensitivity is applied to the tuning of the parameters. The resulting controller has the structure of a fractional order PID which is cascaded with a filter. This is named a fractional IMC–PID controller. Numerical results are given to show the efficiency of the proposed controller.     

Design and implementation of a fuzzy supervisor for on-line compensation of nonlinearities: An instability avoidance module

Unstable behavior of a control loop is the most feared situation in control engineering. Since PID controllers are linear in nature, but still used in 90% of control loops in the process industry, their use in nonlinear processes increases the risk of closed-loop unstable response. This paper presents the design of an instability avoidance module for SISO PID control loops to automatically adjust the controller's tuning parameters when undesired oscillatory behavior is monitored. This module is a Fuzzy-based Supervisor composed of a dynamic parameter identification module that operates on-line, and a Fuzzy Inference System (FIS) with fuzzy rules to modify PID tuning. Tests in nonlinear process models are performed, demonstrating that this Fuzzy Supervisor—Type 1 (non-intrusive) provides the PID controller the ability to adapt its tuning to eliminate observed oscillatory behavior.     

Stabilising PID tuning for a class of fourth-order integrating nonminimum-phase systems

Fed-batch fermentation processes are commonly used in bioprocessing industry. A fed-batch fermentation process often exhibits integrating/unstable type of dynamics with multiple right-half plane zeros. A class of fourth-order integrating model can be used to adequately represent such a complex dynamics of the fed-batch fermentation process. In this paper, rigorous stability analysis of proportional-integral-derivative (PID) controller based on the Routh-Hurwitz criteria for the fourth-order integrating system is presented. A set of all stabilising PID controller parameter regions is established. Based on these stabilising regions, a general PID controller tuning procedure is proposed for the fourth-order integrating system with two right-half plane zeros. Numerical study shows that based on the proposed tuning procedure, a low-order PID controller can outperform a fifth-order optimal LQG controller in terms of servo and regulatory controls.