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。     

小型电加热反应器温度的模糊自适应整定PID控制

小型电加热反应器系统具有较大的纯滞后、惯性滞后、非线性和时变特性,参数固定不变的普通PID控制器难以进行精确温控.通过把操作人员积累的PID参数整定经验知识总结成模糊规则,利用模糊逻辑推理进行在线实时整定,设计了电加热反应器温度模糊自适应整定PID控制算法.通过Matlab与组态软件"组态王"KINGVIEW的动态数据交换,在Matlalb上编程实现了模糊自适应整定PID控制算法.进行了一般情况下和具有较强非线性和时变特性情况下温度控制实验,实验结果表明,模糊自适应整定PID控制取得了比普通PID更好的控制结果,模糊自适应整定PID控制对过程非线性和时变特性具有更强的适应性.     

A PI/PID controller for time delay systems with desired closed loop time response and guaranteed gain and phase margins

In this article we present a graphical tuning method of PI/PID controller for first order and second order plus time delay systems using dominant pole placement approach with guaranteed gain margin (GM) and phase margin (PM). The stability equation method and gain phase margin tester have been used to portray constant GM and PM boundaries. The PID controller parameters have been obtained for different dominant poles and plotted graphically in the parameters plane of controller within the specified GM and PM regions. To demonstrate the effectiveness and confirm the validity of the proposed methodology, three examples with numerical simulations are presented.     

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。     

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.     

Fault tolerant control of multivariable processes using auto-tuning PID controller.

Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.     

基于Maclaurin 展开的PID 设计与无模型自整定

针对自衡对象,提出一种基于期望模型的PID自整定方法,该方法无需被控对象的数学模型.利用Maclaurin展开技术,给出了PID控制器的整定公式;并通过开环阶跃响应,实现了PID控制器的无模型自整定.仿真结果表明,利用该自整定方法所得的PID能有效地提高高阶被控对象的系统性能;即使在噪声环境下,该方法仍具有很好的鲁棒性.     

Robust self-tuning PID controller for nonlinear systems

In this paper, we propose a robust self-tuning PID controller suitable for nonlinear systems. The control system employs a preload relay (P_Relay) in series with a PID controller. The P_Relay ensures a high gain to yield a robust performance. However, it also incurs a chattering phenomenon. In this paper, instead of viewing the chattering as an undesirable yet inevitable feature, we use it as a naturally occurring signal for tuning and re-tuning the PID controller as the operating regime digresses. No other explicit input signal is required. Once the PID controller is tuned for a particular operating point, the relay may be disabled and chattering ceases correspondingly. However, it is invoked when there is a change in setpoint to another operating regime. In this way, the approach is also applicable to time-varying systems as the PID tuning can be continuous, based on the latest set of chattering characteristics. 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 also presented.     

Automated Maximum Sensitivity And Phase Margin Specification Attainment In Pi Control

The prevailing industrial and academic autotune paradigm uses the relay experiment to find the ultimate data of an unknown system, followed by the use of this data in PI (D) tuning rules. This paper firstly reviews a novel method of obtaining desired frequency response data‐points of an unknown system which is more accurate and flexible than the relay experiment. The paper then demonstrates how this new identification module can be used in closed loop to automate PI controller tuning to achieve classical robustness specifications. The new algorithm is given along with details of MATLAB/SIMULINK simulation results. The non‐parametric identification method developed by the authors and used in this work is termed the Phase Locked Loop method (PLL). The classical robustness specification to be achieved by the PI controller is a pair of desired maximum sensitivity and phase margin specifications. Conclusions and future research directions close the paper.     

A Novel Robust Pid Controller Design By Fuzzy Neural Network

In this paper, we propose a robust PID controller tuning method for parametric uncertainty systems (or interval plant family) using fuzzy neural networks (FNNs). This robust controller is based on robust gain and phase margin (GM/PM) specifications that satisfy user requirements. Here, the FNN system is used to identify the relation between the PID controller parameters and robust GM/PM. We can use the trained FNN system to determine the parameters of the PID controllers in order to satisfy robust GM/PM specifications that guarantee robustness and performance. Simulation results are shown to illustrate the effectiveness of the robust controller scheme.     

一种IAE指标触发的继电反馈PID参数自校正方法

针对实际工业过程中固定PID参数不能适应系统特征变化的问题,提出了一种在线控制器参数自动校正方法。首先,以内模控制为基础,由系统工作数据估计得到设定值阶跃变化下系统可获得的最优累积绝对误差值(IAE),并以此建立评价当前控制器优劣的性能指标。若性能不满足要求,则触发PID参数校正算法工作,通过引入继电反馈环节使控制回路振荡,获得控制系统临界信息,再根据改进的Z-N规则计算新的PID控制器参数。最后,分别用仿真和实际液位控制系统验证所提方法的有效性。     

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.     

基于模糊自整定PID 四旋翼无人机悬停控制

四旋翼无人直升机是一种多输入、强耦合、多变量、欠驱动的系统,其可以应用到航拍、考古、边境巡逻、反恐侦查等多个领域,具有广阔的前景。根据欧拉定理以及牛顿定律建立四旋翼无人直升机的动力学模型,并且考虑了空气阻力、转动力矩对于桨叶的影响,而后基于经典PID 算法设计了双环控制系统,之后在此基础上结合模糊控制技术设计了模糊自整定PID 控制器。通过Matlab /Simulink 对两种控制算法设计的控制器进行仿真比较,从仿真结果可以看出两种控制算法均可使四旋翼无人直升机到达指定位置并且保持悬停状态,但模糊自整定PID 算法设计的控制系统在响应时间以及稳定性方面优于经典PID 下的控制系统的控制效果。     

基于半导体制冷片的超速离心机温度控制模块设计

设计了超速离心机的温度控制模块,采用了模糊PID算法,通过PID参数的自动整定,对半导体制冷片的电压进行调整,从而控制半导体制冷片的制冷或制热效率,能对超速离心机离心室内的温度进行精确并且快速的控制.在MATLAB的simulink环境下进行仿真后分析可知,模糊PID算法兼具常规PID算法和模糊控制的优点,能够有效提高...     

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。     

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.     

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.     

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.     

Robust tuning of Two-Degree-of-Freedom (2-DoF) PI/PID based cascade control systems

A design approach for Two-Degree-of-Freedom (2-DoF) PID controllers within a cascade control configuration that guarantees robust and smooth control is presented in this paper. The use of a cascade control configuration comes into place when the use of an additional (intermediate) sensor provides the possibility for a compensation of a load-disturbance before it affects the output variable. The rationale of operation associated to both the inner and outer controllers determines the need of good performance for disturbance attenuation (regulation) as well as set-point following (tracking). Therefore, the use of 2-DoF controllers is introduced. However, the use of 2-DoF controllers, introduces additional parameters that need to be tuned appropriately. Specially for the case of PI/PID controllers there are not known clear auto-tuning guidelines for such situation. The approach undertaken in this paper provides the complete set of tuning parameters for the inner (2-DoF PI) controller and the outer (2-DoF PID) controller. The trade-off among control system performance (measured in terms of closed-loop response speed) and robustness allows to derive a recommendation for the design-parameter lower limit. The design equations are formulated in such a way that a non-oscillatory response is specified for both the inner and outer loop. A side advantage of providing the complete set of parameters is that it avoids the need for the usual identification experiment for the tuning of the outer controller.     

Fractional Order Modeling And Nonlinear Fractional Order Pi‐Type Control For PMLSM System

In this paper, firstly a fractional order (FO) model is proposed for the speed control of a permanent magnet linear synchronous motor (PMLSM) servo system. To identify the parameters of the FO model, a practical modeling algorithm is presented. The algorithm is based on a pattern search method and its effectiveness is verified by real experimental results. Second, a new fractional order proportional integral type controller, that is, (PI^μ)^λ or FO[FOPI], is introduced. Then a tuning methodology is presented for the FO[FOPI] controller. In this tuning method, the controller is designed to satisfy four design specifications: stability requirement, specified gain crossover frequency, specified phase margin, flat phase constraint, and minimum integral absolute error. Both set point tracking and load disturbance rejection cases are considered. The advantages of the tuning method are that it fully considers the stability requirement and avoids solving a complex nonlinear optimization problem. Simulations are conducted to verify the effectiveness of the proposed FO[FOPI] controller over classical FOPI and FO[PI] controllers.