基于PLC的PID参数自整定

PID控制在过程工业控制中应用广泛,但在实际工业现场运行的PID回路的控制性能差异较大,有许多系统长期置于手动控制。一部分由于系统过程特性使PID调节不能满足控制要求,还有一部分却是由于PID回路参数整定的不合理。针对控制系统现场实施中PID参数整定繁琐、整定质量差异大、经验不易移植的问题,采用了基于PLC的PID参数自整定方法。该方法概念清晰,实施方便,在某锅炉的恒压供水控制中应用效果良好。该方法基于继电器反馈自整定,具有一定的普适性,对工程实施人员要求低,易于推广。     

一种解析的模糊PI自整定方法

针对模糊PID控制器缺乏系统的整定方法的问题,提出了一种解析的基于增益裕度和相位裕度的模糊PI控制器的参数自整定方法。首先推导出模糊PI控制器的解析模型,该解析模型包括线性控制器和非线性补偿控制器2个部分。参数整定时,将非线性补偿控制器看作过程的扰动,由线性控制器和被控对象的一阶纯时滞模型,基于系统的增益裕度和相位裕度,导出模糊PI控制器的参数。仿真结果表明,对于时变高阶系统,和传统的PI控制器相比,模糊PI控制器具有鲁棒性强,超调小,调整时间短等优点。     

Integration of PSO and GA for optimum design of fuzzy PID controllers in a pendubot system

In this paper, a novel auto-tuning method is proposed to design fuzzy PID controllers for asymptotical stabilization of a pendubot system. In the proposed method, a fuzzy PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivatives, while the output variables are the PID gains. In this manner, the PID gains are adaptive and the fuzzy PID controller has more flexibility and capability than the conventional ones with fixed gains. To tune the fuzzy PID controller simultaneously, an evolutionary learning algorithm integrating particle swarm optimization (PSO) and genetic algorithm (GA) methods is proposed. The simulation results illustrate that the proposed method is indeed more efficient in improving the asymptotical stability of the pendubot system. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Use of neural networks for quick and accurate auto-tuning of PID controller

With reference to a real industrial application of process control, some considerations are discussed concerning the accuracy of methods for auto-tuning of proportional, integral and derivative factor (PID). In particular, a theoretical–experimental approach is described, that allows to evaluate the adequateness of new methods for auto-tuning of PID, able to significantly reduce the time duration for auto-tuning with respect to traditional ones. This result has been achieved by using suitable techniques of experimental data processing, based on neural-networks algorithms, set for this specific application. The effect on described methodology of environmental and operating disturbances is also described.     

Relay auto-tuning of PID controllers using iterative feedback tuning

In this paper, ideas from iterative feedback tuning (IFT) are incorporated into relay auto-tuning of the proportional-plus-integral-plus-derivative (PID) controller. The PID controller is auto-tuned to give specified phase margin and bandwidth. Good tuning performance according to the specified bandwidth and phase margin can be obtained and the limitation of the standard relay auto-tuning technique using a version of Ziegler-Nichols formula can be eliminated. Furthermore, by using common modelling assumptions for the relay system, some of the required derivatives in the IFT algorithm can be derived analytically. The algorithm was tested in the laboratory on a coupled tank and good tuning result was demonstrated.     

参数自调整PID模糊控制器及在数字随动系统中的应用

结合传统PID的控制原理，介绍一种参数自调整的PID模糊控制器。开发了一套能在线调整PID参数的模糊控制方法的软件，并分别将它和传统的PID控制器作用到数字随动系统中。对二者的控制结果进行了比较。实验结果表明，参数自调整PID模糊控制器使系统稳态性能优良，并能提高控制精度。     

An approximation technique to tune PID controllers

Advanced controller synthesis techniques often result in high order controllers whose order exceeds the order of the plant and it is impractical to implement. The main use of the advanced synthesis techniques is to find the possible optimal performance of the system and thus to check how a practical simpler controller comes close to achieving that optimum. PID controllers are the most found in industry and here we describe a novel technique, based on approximation, to tune the parameters of PID controllers.     

The hierarchical expert tuning of PID controllers using tools ofsoft computing

We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.     

Multiple switching relays for the estimation of ultimate data

Sustained oscillations are obtained by putting relays in the feedback loop, which provide ultimate periods and gains of processes that can be used to tune PID controllers. The ultimate periods obtained by conventional relay autotuning have relative errors up to 5% for first order plus time delay processes. To improve the estimation of ultimate periods, modified relays such as a saturation relay and a relay with preload have been available. However, these modifications lose the binary (on-off) property of the conventional relay. Here relays with multiple switching which produce pulse-widthmodulation (PWM) signals are proposed. They retain the binary property and show improved identification accuracies of ultimate parameters.     

Auto-tune system using single-run relay feedback test and model-based controller design

In this paper, a systematic approach for auto-tune of PI/PID controller is proposed. A single run of the relay feedback experiment is carried out to characterize the dynamics including the type of damping behavior, the ultimate gain, and ultimate frequency. Then, according to the estimated damping behavior, the process is classified into two groups. For each group of processes, model-based rules for controller tuning are derived in terms of ultimate gains and ultimate frequencies. To classify the processes, the estimation of an apparent deadtime is required. Two artificial neural networks (ANNs) that characterize this apparent deadtime using the ATV data are thus included to facilitate this estimation of this apparent deadtime. The model-based design for this auto-tuning makes uses of parametric models of FOPDT (i.e. first-order-plus-dead-time) and of SOPDT (i.e. second-order-plus-dead-time) dynamics. The results from simulations show that the controllers thus tuned have satisfactory results compared with those from other methods.     

Non‐smooth structured control design with application to PID loop‐shaping of a process

Feedback controllers with specific structure arise frequently in applications because they are easily apprehended by design engineers and facilitate on‐board implementations and re‐tuning. This work is dedicated to H_∞ synthesis with structured controllers. In this context, straightforward application of traditional synthesis techniques fails, which explains why only a few ad hoc methods have been developed over the years. In response, we propose a more systematic way to design H_∞ optimal controllers with fixed structure using local optimization techniques. Our approach addresses in principle all those controller structures which can be built into mathematical programming constraints. We apply non‐smooth optimization techniques to compute locally optimal solutions, and provide practical tests for descent and optimality. In the experimental part we apply our technique to H_∞ loop‐shaping proportional integral derivative (PID) controllers for MIMO systems and demonstrate its use for PID control of a chemical process. Copyright © 2007 John Wiley & Sons, Ltd.     

参数自整定模糊PID控制器在转矩流变仪系统的应用研究

在参数自整定模糊PID控制器的基础上,利用模糊推理的方法实现了对PID参数的在线自动整定,并且将该控制软件在转矩流变仪中的应用进行了研究,实验结果表明,参数自整定模糊PID控制能使系统达到满意的控制效果,对进一步应用研究具有较大的参考价值.     

多变量PID控制器的在线自整定

本文研究具有ＰＩＤ结构反馈控制器的多变量控制系统的参数自整定，提出了具有校正因子的多变换ＰＩＤ控制算法及在线自动调整校正因子的专家自整定方法，将该方法用于火电单元机组负荷控制系统自整定仿真研究，结果表明系统具有好的完整性和鲁棒性。     

Relay feedback methods combining sub-relays to reduce harmonics

The relay feedback method is considered to be one of the easiest identification methods available for obtaining the ultimate information of the process. It has been widely used in industry to automatically tune the PID controller. Many applications of the method have been developed. In this research, a new framework has been proposed to reduce the harmonics of the relay feedback signal. It linearly combined several sub-relay signals, which had different frequencies and gains and resulted in a significant reduction of harmonic terms. Improved versions of several previous relay feedback methods have been successfully developed on the basis of the proposed framework.     

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.     

Bioreactor profile control by a nonlinear auto regressive moving average neuro and two degree of freedom PID controllers

This paper presents the use of nonlinear auto regressive moving average (NARMA) neuro controller for temperature control and two degree of freedom PID (2DOF-PID) for pH and dissolved oxygen (DO) of a biochemical reactor in comparison with the industry standard anti-windup PID (AWU-PID) controllers. The process model of yeast fermentation described in terms of temperature, pH and dissolved oxygen has been used in this study. Nonlinear auto regressive moving average (NARMA) neuro controller used for temperature control has been trained by Levenberg–Marquardt training algorithm. The 2DOF-PID controllers used for pH and dissolved oxygen have been tuned by MATLAB's auto tune feature along with manual tuning. Random training data with input varying from 0 to 100 l/h have been obtained by using NARMA graphical interface. The data samples used for training, validation and testing are 20,000, 10,000 and 10,000 respectively. Random profiles have been used for simulation. The NARMA neuro controller and the 2DOF-PID controllers have shown improvement in rise time, residual error and overshoot. The proposed controllers have been implemented on TMS320 Digital Signal Processing board using code composure studio. Arduino Mega board has been used for input/output interface.     

Auto-tuning of phase lead/lag compensators

In the tuning of phase lead/lag compensators, knowledge of specific points on the frequency response of the plant are required. Such points are specified by their frequency, gain and phase and are not readily available without an accurate model of the plant. Yet such information is important for any auto-tuning procedure to succeed. In this paper, relays with hysterisis are tuned to determine points on the frequency response of a plant with a user-specified gain, g₀ or phase, φ₀. On-line algorithms are developed to tune the operating point of the relay feedback system so that the resulting oscillations correspond to the frequency response of the plant with either gain, g₀ or phase, φ₀. Tuning involves setting either the amplitude of the relay or its hysterisis width. Improvement over the simple application of the describing function is also shown. The results are applied to the auto-tuning of phase lead and lag compensators. Simulations are presented to illustrate the auto-tuning procedures.     

Computational intelligence approach to PID controller design using the universal model

Despite the popularity of PID (Proportional-Integral-Derivative) controllers, their tuning aspect continues to present challenges for researches and plant operators. Various control design methodologies have been proposed in the literature, such as auto-tuning, self-tuning, and pattern recognition. The main drawback of these methodologies in the industrial environment is the number of tuning parameters to be selected. In this paper, the design of a PID controller, based on the universal model of the plant, is derived, in which there is only one parameter to be tuned. This is an attractive feature from the viewpoint of plant operators. Fuzzy and neural approaches - bio-inspired methods in the field of computational intelligence - are used to design and assess the efficiency of the PID controller design based on differential evolution optimization in nonlinear plants. The numerical results presented herein indicate that the proposed bio-inspired design is effective for the nonlinear control of nonlinear plants.     

A novel real-time fuzzy adaptive auto-tuning scheme for cascade PID controllers

This paper presents a novel fuzzy auto-tuning methodology to continuously adapt PID control actions without interrupting the normal process operation. New auto-tuning rules are introduced to schedule a gradual and guided activation of each individual P, I and D control mode in three adjustable functional control zones. An auto-scaling procedure has been incorporated to generalize the autotuning scheme to efficiently respond to any set-point change outside a pre-defined operating span. In contrast to existing auto-tuning algorithms, the proposed scheme is not an on-demand auto-tuning methodology and hence does not require alertness of an experienced engineer to initiate and supervise its initial operation in a separate commissioning identification pre-test. This interesting feature provides a new perspective on PID auto-tuning approaches. Performance of the proposed auto-tuning scheme is practically evaluated in a real pilot plant within a networked control system (NCS) configuration, realized by industrial Ethernet and Foundation Fieldbus technologies. An extensive series of test scenarios has been conducted to explore efficiency of the proposed auto-tuning methodology to cope with fixed and varying operating set-points under uncertain and variable network transmission time delays and external disturbance.     

智能PID参数自整定技术在伺服系统中的应用

针对常规PID控制参数整定困难,且受时变、非线性等因素影响而不能达到预期控制效果的实际情况,提出了RBF网络动态辨识的BP神经网络PID参数自整定算法.此算法可实现PID控制参数的在线自整定和优化;同时,将算法应用于伺服控制系统中,以VC++6.0和Matlab为开发和仿真工具,对动态辨识神经网络智能PID参数自整定方法进行仿真研究.仿真结果表明,控制算法鲁棒性强、响应速度快,可用于控制参数时变的非线性系统.