模糊自适应PID控制器参数整定的研究

主要研究了模糊自适应PID控制器参数整定方法,给出了预估计PID参数值的经验公式和方法。用MATLAB软件对PID控制、模糊自适应PID控制的控制性能分别进行了仿真研究,结果表明参数模糊自整定PID控制具有良好的稳态精度和自适应能力。     

Research on Fuzzy Self Adaptive PID Controller with Parameters Tuning

主要研究了模糊自适应PID控制器参数整定方法,给出了预估计PID参数值的经验公式和方法.用MATLAB软件对PID控制、模糊自适应PID控制的控制性能分别进行了仿真研究,结果表明参数模糊自整定PID控制具有良好的稳态精度和自适应能力.     

模糊PID控制的中频电炉温控系统设计

针对中频电炉的结构,采用参数辨识方法,通过分析中频电炉的温升曲线获得相应的数学模型。针对该模型应用MTALAB仿真工具设计模糊PID控制器,该控制器根据误差及误差的变化率现场整定PID控制的参数。比较常规PID控制与模糊PID控制的仿真效果可以发现,采用模糊PID控制器根据误差与误差的变化率现场整定PID控制的参数,可以有效地提高PID控制器的控制效果。     

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.     

模糊逻辑在PID参数整定中的应用

PID控制是最早发展起来的控制策略之一,由于受到参数整定方法烦杂的困扰,常规PID控制器参数往往性能欠佳,对运行工作情况的适应性差。本设计将模糊控制和PID控制结合起来,构建自适应模糊PID控制器,实现PID参数的最佳调整。该模糊自整定PID控制器既具有PID控制器高精度的优点,又具有模糊控制器快速、稳态特性。     

模糊自整定PID的航空发动机转速控制研究

航空发动机具有强非线性和强时变性的特点,使用定参数PID方法的转速控制系统的性能在全飞行包线内难以保证.针对上述问题,提出设计模糊自整定PID控制器,利用输入误差及变化率建立一组PID参数在线调整规则,运用模糊推理方法实时进行参数自整定.结合某型航空发动机核心机非线性实时模型,进行转速串级控制硬件在回路仿真.结果表明,提出的模糊自整定PID控制方法实现了控制器参数在线调整,参数切换扰动小,满足全包线内转速控制的指标要求.     

改进PSO电液伺服系统的在线PID参数整定

针对传统的电液伺服系统PID控制器参数在线整定难以达到最优的问题,提出了一种解决方法。根据系统的动态模型,在系统时变参数的变化范围内取若干值,得到一组相应数目的定参数系统模型。针对这组模型,采用改进PSO整定PID参数,获得一组近似最优化的PID参数,拟合数据得到PID参数曲线,利用该曲线进行电液伺服系统的在线整定。该方法可实现近似最优的PID参数在线整定,控制系统的性能得到了明显的提高。仿真结果证明了该方法的有效性。     

基于虚拟模糊集的PID参数整定器的仿真研究

该文中给出的模糊整定器是在虚拟模糊集概念的基础上实现的。该方法首先根据Ｚ－ Ｎ 整规则,按照过程的开环阶跃响应设置初始参数,然后基于闭环控制系统的响应特性,利用模糊系统精确整定控制器参数。模糊控制规则知识库由整定知识和专家经验规则构成。其中整定知识可通过对一典型过程的参数整定来自动提取。最后给出的数字仿真结果证明该方法的有效性     

基于改进模糊神经网络的PID参数自整定

针对传统PID整定控制效果差且单纯神经网络整定存在参数学习和调整困难等问题,提出了一种基于改进模糊神经网络的PID参数整定方法。在该方法中,PID控制器的控制参数采用基于Mamdani模型的模糊神经网络进行自适应整定,模糊神经网络参数采用混沌遗传算法离线粗调和BP算法在线细调的方式进行学习和调整,仿真结果表明该整定策略动态响应快、误差控制精度高且网络中各节点及参数物理意义明确。最后分别从模糊规则数的变化及适应度函数的选取两方面提出两种优化方案,仿真结果表明增加模糊规则数或采用不同的适应度函数都有利于进一步减小控制误差。     

基于Matlab参数自整定PID控制器的设计与仿真

本文针对常规PID控制器不能在线进行参数自整定的问题,结合模糊控制技术,提出了一种模糊自整定PID参数的方法,并利用Matlab的模糊控制工具箱以及Simulink对其进行了仿真,结果表明设计的自整定PID模糊控制器具有控制精度高,超调小,动态性能好的特性.     

Two-level tuning of fuzzy PID controllers

Fuzzy PID tuning requires two stages of tuning; low level tuning followed by high level tuning. At the higher level, a nonlinear tuning is performed to determine the nonlinear characteristics of the fuzzy output. At the lower level, a linear tuning is performed to determine the linear characteristics of the fuzzy output for achieving overall performance of fuzzy control. First, different fuzzy systems are defined and then simplified for two-point control. Non-linearity tuning diagrams are constructed for fuzzy systems in order to perform high level tuning. The linear tuning parameters are deduced from the conventional PID tuning knowledge. Using the tuning diagrams, high level tuning heuristics are developed. Finally, different applications are demonstrated to show the validity of the proposed tuning method.     

微陀螺静电力调频的快速收敛算法研究

针对电容式微陀螺谐振结构,研究了静电力对谐振频率的影响规律,提出了一种快速收敛的静电力调频算法,建立了微陀螺调频实验系统,该系统采用扫频方法测量谐振频率,利用计算机控制调频收敛过程,并对微陀螺进行了调频实验,调频过程用时少于5分钟,实验结果表明该调频算法具有较快的收敛速度。     

On-line tuning strategy for model predictive controllers

This paper presents an intuitive on-line tuning strategy for linear model predictive control (MPC) algorithms. The tuning strategy is based on the linear approximation between the closed-loop predicted output and the MPC tuning parameters. By direct utilization of the sensitivity expressions for the closed-loop response with respect to the MPC tuning parameters, new values of the tuning parameters can be found to steer the MPC feedback response inside predefined time-domain performance specifications. Hence, the algorithm is cast as a simple constrained least squares optimization problem which has a straightforward solution. The simplicity of this strategy makes it more practical for on-line implementation. Effectiveness of the proposed strategy is tested on two simulated examples. One is a linear model for a three-product distillation column and the second is a non-linear model for a CSTR. The effectiveness of the proposed tuning method is compared to an exiting offline tuning method and showed superior performance.     

Robust IMC–PID tuning for cascade control systems with gain and phase margin specifications

In this article, an internal model control plus proportional-integral-derivative (IMC–PID) tuning procedure for cascade control systems is proposed based on the gain and phase margin specifications of the inner and outer loop. The internal model control parameters are adjusted according to the desired frequency response of each loop with a minimum interaction between the inner and outer PID controllers, obtaining a fine tuning and the desired gain and phase margins specifications due to an appropriate selection of the PID controller gains and constants. Given the design specifications for the inner and outer loop, this tuning procedure adjusts the IMC parameter of each controller independently, with no interference between the inner and outer loop obtaining a robust method for cascade controllers with better performance than sequential tuning or other frequency domain-based methods. This technique is accurate and simple, providing a convenient technique for the PID tuning of cascade control systems in different applications such as mechanical, electrical or chemical systems. The proposed tuning method explained in this article provides a flexible tuning procedure in comparison with other tuning procedures because each loop is tuned simultaneously without modifying the robustness characteristics of the inner and outer loop. Several experiments are shown to compare and validate the effectiveness of the proposed tuning procedure over other sequential or cascade tuning methods; some experiments under different conditions are done to test the performance of the proposed tuning technique. For these reasons, a robustness analysis based on sensitivity is shown in this article to analyze the disturbance rejection properties and the relations of the IMC parameters.     

Study of predictive controller tuning methods

Several tuning guidelines for model predictive control proposed in literature have been converted into suitable tuning rules and investigated with the help of simulations of two typical transfer functions and a nonlinear unstable chemical reactor as well as a real-time laboratory turbogenerator control application. A modified version of a supervisory performance tuning procedure has also been applied to explore the possibility of application of auto-tuning in model predictive control. A new tuning procedure is finally presented on the basis of the results obtained using several previously existing tuning guidelines.     

A neural-network-based approach for post-fabrication circuit tuning

A hierarchical neural-network-based approach for circuit tuning at the post-fabrication stage is proposed. In this approach, measurements that characterize the behavior of the circuit under test are first selected. The best candidates of circuit parameters for tuning are also determined. A training set comprising the selected circuit measurements is then constructed. These measurements are calculated during simulations in which the circuit parameter values are uniformly distributed in a tolerance region around their nominal values. The training set is fed to a self organizing map neural network to cluster the measurements. The generated clusters are manipulated and classified via a hierarchical circuit tuning procedure. Based on this classification, tuning values for the tuning parameters are calculated. Situations in which the circuit cannot be tuned are also addressed. Experimental results indicate that the developed approach provides a robust and efficient technique for circuit tuning.     

高速高精度平面并联机器人模糊自调整PID控制方法的研究

针对推力波动、负载变化等非线性因素对高速高精度平面并联机器人系统稳定时间的影响，本文设计了一种新颖的模糊自调整PID控制器：系统的位置偏差较大时，采用PI控制器，保证系统的平滑、稳定；当系统发出停止命令后，引入模糊增益参数自调整机构，加快静差消除．模糊增益参数调整机构采用“一维输入-二维输出”的推理结构，消除了参数调整中的“耦合影响”；为缩短整定时间，减少整定参数的数量，不同增益，误差E的模糊论域划分各不相同．经实验验证：引入该模糊自校正PID控制器后，机器人系统的稳定时间有显著改善．     

Robust tuning for machine-directional predictive control of MIMO paper-making processes

This paper solves the controller tuning problem of machine-directional predictive control for multiple-input–multiple-output (MIMO) paper-making processes represented as superposition of first-order-plus-dead-time (FOPDT) components with uncertain model parameters. A user-friendly multi-variable tuning problem is formulated based on user-specified time domain specifications and then simplified based on the structure of the closed-loop system. Based on the simplified tuning problem and a proposed performance evaluation technique, a fast multi-variable tuning technique is developed by ignoring the constraints of the MPC. In addition, a technique to predict the computation time of the tuning algorithm is proposed. The efficiency of the proposed method is verified through Honeywell real time simulator platform with a MIMO paper-making process obtained from real data from an industrial site.     

PID auto-tuning using new model reduction method and explicit PID tuning rule for a fractional order plus time delay model

In this paper, a new model reduction method and an explicit PID tuning rule for the purpose of PID auto-tuning on the basis of a fractional order plus time delay model are proposed. The model reduction method directly fits the fractional order plus time delay model to frequency response data by solving a simple single-variable optimization problem. In addition, the optimal tuning parameters of the PID controller are obtained by solving the Integral of the Time weighted Absolute Error (ITAE) minimization problem and then, the proposed PID tuning rule in the form of an explicit formula is developed by fitting the parameters of the formula to the obtained optimal tuning parameters. The proposed tuning method provides almost the same performance as the optimal tuning parameters. Simulation study confirms that the auto-tuning strategy based on the proposed model reduction method and the PID tuning rule can successfully incorporate various types of process dynamics.     

Micromachined widely tunable vertical cavity laser diodes

Wavelength tunable vertical-cavity surface-emitting lasers (VCSELs) are potentially useful for future optical communications. Traditionally, the emission wavelength of a vertical cavity laser was tuned by modulating the active region temperature. However, thermal tuning is slow, and the realized tuning range is quite limited. Micromachined tunable VCSELs (Mi-T-VCSELs) combine the traditional vertical cavity laser structure with a monolithically micromachined deformable membrane, enabling continuous wavelength tuning without mode hopping. In addition to a large wavelength tuning range, this technique does not suffer from the shortcomings of the thermal tuning technique. This paper presents the background theory, processing sequence, and experimental results for Mi-T-VCSELs