基于模糊估计的可调分数阶PID控制器设计

可变分数阶微分环节直接影响分数阶PID控制器性能,设计分数阶PID控制器需要根据被控对象传递函数凭经验调整微分阶次。采用Oustaloup间接离散法数字实现分数阶微积分,再基于模糊估计由特定分数阶次近似得到任意分数阶次微积分环节,根据参数整定规则确立各环节系数,设计了一种可调分数阶次的PID控制器。仿真实验证明,此方法得到的微积分环节对控制系统性能没有影响,根据整数阶被控对象传递函数调节微分阶次,分数阶PID控制器有较好的控制效果。     

分数阶PD控制器在时滞伺服系统中的研究

分数阶微积分理论的发展推动了分数阶微积分在各个领域的广泛应用,分数阶控制算法的研究也成为近几年的研究热点.目前分数阶控制理论的研究主要集中在理论分析,对于目前所研究的这类工程性较强的控制对象,成熟的研究成果较少.针对实际工程中含有时滞的伺服系统模型,将Flat phase法和系统稳定性裕度条件相结合,设计了分数阶PD控制器.此PD控制器结构简单,对参数变化稳定性好,控制精度高.为了对比仿真实验,文章还设计了整数阶PID控制器.仿真结果表明,分数阶控制器比传统整数阶PID控制器的控制精度更高,鲁棒性更好.     

基于最优Oustaloup的分数阶PID参数整定

目前工程控制中大部分系统采用传统PID控制,由于分数阶PID继承了传统PID的优点,并且具有更好的控制品质及更强的鲁棒性,因此针对分数阶微积分的高精度数字实现及分数阶PID控制器在工程复杂系统中的实际应用,提出一种新的分数阶微积分高精度数字实现算法-最优Oustaloup数字实现,并建立控制系统的仿真模型,利用框图式模型结合最优ITAE性能指标来整定分数阶PID的参数。通过实例仿真验证,该方法能进一步优化控制器参数,提高控制精度及获得更好的控制效果,便于非线性系统及复杂系统的分数阶PID参数整定。     

分数阶鲁棒自适应控制

研究了分数阶模型参考自适应控制系统.引入了分数阶微积分的概念,利用系统的输入输出,通过构造辅助信号设计了分数阶的自适应控制器和一类新的有界干扰系统的变结构分数阶鲁棒自适应控制器.基于分数阶微积分和Lyapunov稳定性理论,证明了所设计的闭环系统的稳定性.最后,仿真实验验证了此方法的有效性.     

基于改进Oustaloup滤波器的分数阶PID控制器简化设计

针对分数阶微积分算子的直接和间接近似化方法所表现出来的形式复杂、运算量大的问题,对Oustaloup滤波器的结构进行改进,对常规分数阶PID控制器进行了简化设计,并采用自适应遗传算法对控制器的参数进行整定.选取两种代表性分数阶系统,在模型处于两种典型状态下,对简化型分数阶PID控制器、常规分数阶PID控制器和整数阶PID控制器的控制性能进行仿真实验对比.结果表明,在控制器性能基本相同的情况下,通过该方法设计的简化型分数阶PID控制器性具有结构简单,耗时量小的优点,提高了工程可实现性.     

分数阶PI^λD^μ控制器控制性能的研究

现实控制系统研究中存在很多分数阶系统,因此对系统提出了分数阶PI~λD~μ控制器,控制器将传统整数阶PID控制器的微分与积分阶数扩展到分数,增加了两个参数微分阶数μ和积分阶数λ.为了对比研究分数阶系统分别在分数阶PI~λD~μ控制器控制下和在整数阶PID控制器控制下的系统性能,针对一个典型的分数阶系统,分别设计两类控制器,再进行性能比较.实验仿真结果表明,与整数阶PID控制器相比,该系统在分数阶PI~λD~μ控制器控制下整个闭环系统具备较好的动、静态性能,并且鲁棒性较强,说明分数阶PI~λD~μ控制器控制性能的优越性以及当被控系统为分数阶系统时应该设计分数阶PI~λD~μ控制器.     

分数阶控制系统

随着基于分数阶次的数学理论日益完善,分数阶控制系统也越来越广泛地被研究和讨论。为了完善分数阶控制系统的理论体系,给出了分数阶系统的总体综述。介绍了分数微积分的定义,给出了分数阶线性定常系统的传递函数和状态空间描述,简要介绍了分数阶控制系统的复频域分析和分数阶控制器及控制器的设计方法,并分析了几种设计方法的优缺点。分数系统的研究必然能找到合适的切入点广泛地进入现代控制领域,为真正实现工业控制自动化提供强有力的理论依据。     

航空发动机分数阶PID控制器的参数自整定方法

控制器作为航空发动机的大脑,是保障发动机正常运行的核心部件,随着对发动机控制器精度和时效性的要求越来越高,传统PID控制器的性能亟需进一步提升.本文提出了改进的分数阶PID离线和在线参数整定方法,应用于涡扇发动机推力的控制中.首先,利用Caputo分数阶微积分定义建立分数阶PID模型,实现时域上的数值计算; 其次,基于对数正态分布提出了改进的布谷鸟算法,实现了分数阶PID离线参数整定; 然后,结合RBF网络设计参数线上整定方法,解决了参数在线整定问题; 最后将相关理论应用于发动机推力的控制中,结果表明,相比其他几种优化算法,改进的布谷鸟优化算法对分数阶PID控制参数整定效果最好; 利用RBF神经网络对分数阶PID进行在线整定时控制效果稳定,且分数阶PID的控制效果优于传统的PID控制,能提高对推力的控制能力.     

分数阶控制器在电机振动控制中的应用

对于一些复杂的控制系统,分数阶控制器的控制效果较于整数阶PID控制器的控制效果会更为优越.主要是通过对交流电机的振动抑制实验,从电机的转速和振动情况上分析,通过对参数的合理调节,分数阶控制器将获得比整数阶PID控制器更好的控制效果.     

一类分数阶非线性混沌系统的同步控制

在分数阶非线性系统同步控制的研究中,针对一类分数阶非线性混沌系统,研究了基于分数阶控制器的同步方法.利用状态反馈方法和分数阶微积分定义,设计了分数阶混沌系统同步控制器.进一步,根据分数阶非线性系统稳定性理论、Mittag-Leffler函数、Laplace变换以及Gronwall不等式,证明了同步控制器的有效性.最后,通过数值仿真,实现了初始值不同的两个分数阶非线性混沌系统同步.误差响应曲线表明研究的分数阶非线性系统同步响应速度快,控制精度高,验证了本文所设计的混沌同步控制方案的可行性.     

分数阶模糊免疫PID控制器的设计

为改善分数阶PID控制器的控制性能,借鉴整数阶模糊免疫PID控制器,把模糊免疫调节与分数阶PID控制器结合起来,设计了分数阶模糊免疫PID控制器。仿真结果表明了该方法的有效性,不但提高了分数阶PID控制器跟踪性能,而且还具有良好的鲁棒性和抗干扰性。     

Multi‐objective robust fuzzy fractional order proportional–integral–derivative controller design for nonlinear hydraulic turbine governing system using evolutionary computation techniques

The present paper proposes a novel multi‐objective robust fuzzy fractional order proportional–integral–derivative (PID) controller design for nonlinear hydraulic turbine governing system (HTGS) by using evolutionary computation techniques. The fuzzy fractional order PID (FOPID) controller takes closed loop error and its fractional derivative as inputs and performs fuzzy logic operations. Then, it produces the output through the fractional order integrator. The predominant advantages of the proposed controller are its capability to handle complex nonlinear processes like HTGS in heuristic manner, due to fuzzy incorporation and extending an additional flexibility in tuning the order of fractional derivative/integral terms to enhance the closed loop performance. The present work formulates the optimal tuning problem of fuzzy FOPID controller for HTGS as a multi‐objective one instead of a traditional single‐objective one towards satisfying the conflicting criteria such as less settling time and minimum damped oscillations simultaneously to ensure the improved dynamic performance of HTGS. The multi‐objective evolutionary computation techniques such as non‐dominated sorting genetic algorithm‐II (NSGA‐II) and modified NSGA‐II have been utilized to find the optimal input/output scaling factors of the proposed controller along with the order of fractional derivative/integral terms for HTGS system under no load and load turbulence conditions. The performance of the proposed fuzzy FOPID controller is compared with PID and FOPID controllers. The simulations have been conducted to test the tracking capability and robust performance of HTGS during dynamic set point changes for a wide range of operating conditions and model parameter variations, respectively. The proposed robust fuzzy FOPID controller has ensured better fitness value and better time domain specifications than the PID and FOPID controllers, during optimization towards satisfying the conflicting objectives such as less settling time and minimum damped oscillations simultaneously, due to its special inheritance of fuzzy and FOPID properties.     

一种分数阶预测控制器的研究与实现

本论文研究了一种新型预测控制器RTD-A的分数阶实现方法及应用. 与常规控制器比较, RTD-A控制器具有参数意义明确, 易于整定和实施的优点. 论文将RTD-A控制器扩展到分数阶形式, 并与经Z-N法整定的分数阶PI?D1控制器和Wang-Juang-Chan法整定的PID控制器进行了比较. 所提出的分数阶预测控制器在设定值跟踪, 克服负荷扰动, 鲁棒性等方面都有较理想的控制性能. 仿真结果验证了这种分数阶预测控制器的有效性.     

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.     

Fractional order [proportional derivative] controller for a class of fractional order systems

Recently, fractional order systems (FOS) have attracted more and more attention in various fields. But the control design techniques available for the FOS suffer from the lack of direct systematic approaches. In this paper, we focus on a given type of simple model of FOS. A fractional order [proportional derivative] (FO-[PD]) controller is proposed for this class of FOS, and a practical and systematic tuning procedure has been developed for the proposed FO-[PD] controller synthesis. The fairness issue in comparing with other controllers such as the traditional integer order PID (IO-PID) controller and the fractional order proportional derivative (FO-PD) controller has been addressed under the same number of design parameters and the same specifications. Fair comparisons of the three controllers (i.e., IO-PID, FO-PD and FO-[PD]) via the simulation tests illustrate that, the IO-PID controller designed may not always be stabilizing to achieve flat-phase specification while both FO-PD and FO-[PD] controllers designed are always stabilizing. Furthermore, the proposed FO-[PD] controller outperforms FO-PD controller for the class of fractional order systems.     

Optimum Design of Fractional Order Pid Controller Using Chaotic Firefly Algorithms for a Control CSTR System

A fractional‐order PID controller is a generalization of a standard PID controller using fractional calculus. Compared with the standard PID controller, two adjustable variables, “differential order” and “integral order”, are added to the PID controller. Fractional‐order PID is more flexible, has better responses, and the precise adjustment closed‐loop system stability region is larger than that of a classic PID controller. But the design and stability analysis is more complicated than for the PID controller. Therefore, the optimal setting of parameters is very important. A firefly algorithm in standard mode has only local optimization and accuracy is low. In order to fix this flaw an improved chaotic algorithm firefly is proposed for a design controller FOPID. To evaluate the performance of the proposed controller, it has been used in the control of a CSTR system with a variety of fitness functions. Simulations confirm the optimal performance of the proposed controller.     

基于分数阶内模控制的风力机叶片颤振研究

针对风力机叶片颤振系统,提出了一种结合分数阶(Fractional Order)控制与内模控制(Internal Model Control,IMC)的新型颤振控制方法.利用分数阶滤波器设计了分数阶内模控制器,基于闭环动态特性指标,如相位裕量和截止频率,实现对控制器参数的自整定.通过仿真实验对比证明,针对风力机叶片颤振控制,所设计的控制方法优于传统PID、内模PID控制方法,不仅减少了控制参数,而且提高了动态特性和鲁棒性.     

Design of internal model control based fractional order PID controller

This article presents a design of the internal model control(IMC)based single degree of freedom(SDF) fractional order(FO)PID controller with a desired bandwidth specification for a class of fractional order system(FOS). The drawbacks of the SDF FO-IMC are eliminated with the help of the two-degree of freedom(TDF)FO PID controller. The robust stability and robust performance of the designed controller are analyzed using an example.     

基于RandW-SecPSO的四旋翼飞行器分数阶PID控制器参数优化

为了提高四旋翼飞行器姿态控制的控制性能,将分数阶PID控制器运用到四旋翼飞行器的控制系统中.提出了一种带随机权重平均值的二阶粒子群算法(RandW-SecPSO)去优化分数阶PID控制器的参数.将随机权重平均值与二阶粒子群算法相结合,对粒子群进行二阶初始化,同时加入随机权重用以平衡全局搜索能力和局部开发能力,这样提高了算法的收敛精度,并将其与PID控制器进行仿真分析.通过搭建仿真平台,验证了该算法的可行性.仿真结果表明:RandW-SecPSO算法在优化四旋翼飞行器分数阶控制器的参数上要好于粒子群算法(PSO),与PSO算法相比调节时间缩短了0.7s,上升时间减少了0.2s,超调量减小了8％,具有收敛速度快、超调量小、稳定性好等优点.总之RandW-SecPSO算法优化分数阶PID动态响应特性比PID要好很多.