基于理想Bode传递函数的分数阶PID频域设计方法及其应用

基于理想Bode传递函数,提出一种简便的分数阶PID控制器频域设计方法.采用传递函数模型匹配与辨识方法,将分数阶PID控制器5个参数的复杂设计问题转化为单个参数的一维搜索问题进行求解;结合短记忆法实现分数阶PID控制器数字化.该方法已成功应用于直流电机调速控制系统,能够达到期望的响应性能,具有强鲁棒性.实验结果验证了所提出设计方法的有效性.     

基于期望控制函数频率特征的解耦多变量控制

提出一种简单的解耦多变量系统比例积分微分(PID)控制器设计方法;首先,将多变量过程前馈解耦为多个独立单回路系统,利用解耦器对角环节保证解耦器的稳定性和可物理实现性;其次,针对每个已解耦单回路系统,提出同时考虑设定值跟踪、扰动抑制和鲁棒稳定性要求的期望闭环传递函数,由此得到期望控制函数,并基于期望控制函数的频率特征快速获取PID控制参数;最后,示例了解耦多变量控制器的设计过程;仿真结果表明该解耦PID设计法对一般多变量时滞过程的控制是有效的。     

达林算法的计算机程序实现

本文从分析带纯滞后控制系统的特性及PID算法的不足出发，说明了在离散城内当已知对象的准确传递函数为已知时，利用该闭环传递函数直接设计数字控制器的方法，针对带纯滞后的一阶和二阶控制系统，对达林算法的原理、数字控制器的模型、算法思想及程序实现进行了深入探讨。     

鲁棒 PID 设计在涡扇发动机中的应用

针对常规 PID 控制器参数镇定过程通常采用手工试凑方法费时费力,优化或理论设计方式算法结构复杂、不便于工程人员理解等局限,研究了一种基于闭环增益成形算法的鲁棒 PID 快速设计方法,以提高 PID 控制器设计的简洁性和鲁棒性.并分别针对当受控对象具有二阶或一阶传递函数形式,推导并给出了 PID 参数的相应计算格式.最后,应用于某型涡扇发动机控制器设计中.通过仿真结果表明,用以设计的 PID 控制器具有良好的控制性能和鲁棒性能,证明了此算法是值得应用和推广的.     

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。     

Bode 理想传递函数在分数阶控制中的应用

本文将Bode 理想传递函数应用于分数阶控制器的设计和分数阶PID 控制器参数整定中．所得控制器 可以在满足系统要求的截止频率和相角裕度的前提下,使补偿后系统Bode 图的相频特性曲线在截止频率附近有一 个水平区域,即闭环系统对增益的变化具有鲁棒性．它不仅适合于分数阶对象,也适用于整数阶对象,并能够提高 系统的控制品质．仿真结果证明了上述方法的有效性．     

自适应的时变比例增益的预测PID控制器

为了利用PID控制获得先进的控制性能,将广义预测控制(GPC)用于PID参数的实时优化,在此基础上提出了一种新的基于GPC的自适应PID控制器的设计方法.该PID控制器具有时变的比例增益,并且PID控制器的设计利用了GPC的未来参考输入.因此,GPC控制律能由设计的PID控制器精确实现.为使GPC控制器稳定地获得比例增益,采用了基于互质因子分解扩展的强稳定GPC,独立于利用标准GPC设计的闭环系统而重新设计GPC控制器,保证了闭环系统的稳定性.此外,利用递推最小二乘法对系统进行在线辨识,修正模型参数,增强了系统的抗扰性.以一阶时滞非最小相位系统为被控对象,在Matlab中对该设计方法进行了仿真,仿真结果验证了该方法的有效性.     

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.     

深海自持式智能浮标双闭环模糊PID定深控制

针对深海自持式智能浮标运动模型非线性、强耦合性的特点,提出了一种基于双闭环反馈回路的模糊比例-积分-微分（proportion-integral-derivative,PID）定深控制器.根据浮标的浮力调节机构,分析了浮标的运动过程,建立了非线性运动方程.针对外环深度反馈回路,设计了模糊控制器.基于内环速度反馈回路与模糊控制器,设计了联级模糊PID定深控制器.传统PID定深控制器超调量5.6%,最终在目标深度±30 m范围内震荡,而双闭环模糊PID定深控制器在相同的上升时间内,超调量2.0%,深度误差控制在1.0%以内.存在外界扰动的情况下,通过双闭环模糊PID定深控制器的调节,浮标仍可以稳定在目标深度内.仿真结果表明,所建立的双闭环模糊PID定深控制系统具有良好的控制效果和稳定性.     

低阶时滞过程的伪预测PI／PID控制

基于单位反馈控制结构,根据期望的闭环传递函数设计得到了一种伪预测PI/PID(ADQPI/ADQPID)控制器。这种控制器只有一个可调参数,可调参数与系统动态响应性能和鲁棒稳定性之间存在直接关系,只需单调的调节控制器参数,便可实现系统的动态响应性能与鲁棒稳定性之间的最佳折衷。仿真实例表明,这种控制器在扰动和模型失配的情况下仍然具有良好的控制性能和鲁棒稳定性,是一种值得在实际工程中推广运用的新型控制器。     

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.     

PI-PD控制器的应用研究

自动控制系统的前向通道采用PI控制,而反馈环内加入PD控制,由此构成了PIPD控制器。PI—PD控制器不仅具有与PID控制相似的功能,并且对于含有积分、振荡或不稳定环节的控制对象,可以实现较好的闭环控制。本文介绍了PI—PD控制器的结构和参数计算方法,将该控制器应用于一个随动系统中,通过仿真分析,表明了PI—PD控制器的特点和优越性。     

A closed-loop data based test for robust performance improvement in iterative identification and control redesigns

In robust iterative identification and control redesign techniques, a stabilizing controller connected in a closed loop is normally replaced by an alternative attractive stabilizing controller to improve robustness and performance of the closed-loop system. In this paper, novel test methods are proposed to check whether a new stabilizing controller improves performance or not when the existing controller is replaced by this new controller in the closed loop. The proposed tests are based on closed-loop data and no plant model, and can be used for both the SISO and MIMO linear time-invariant systems. For the proposed tests, the plant dynamics is assumed to be unknown whereas the existing and new controller transfer function matrices are known to the designer. These assumptions are common in iterative identification and control redesign techniques. The performance improvement test methods proposed in this paper build on the experimental set-up proposed in Dehghani, Lecchini, Lanzon, and Anderson (2009) which was used to only check whether controllers ensure internal stability of a feedback interconnection or not. In this paper, new test methods are proposed to ascertain robust performance improvement that cannot be obtained from test results of Dehghani et al. (2009). A numerical example is illustrated to show effectiveness of the proposed test methods.     

Performance preserving controller reduction via additiveperturbation of the closed-loop transfer function

An H_∞ performance preserving controller order reduction method is proposed. Here performance preservation indicates that the H_∞ norm bound of the closed loop transfer function with reduced-order controller is not greater than the H_∞ norm bound of the closed loop transfer function with full order controller. We assume additive perturbations to the closed-loop transfer function and obtain a sufficient condition for performance preservation. Two kinds of useful weightings are derived, and the controller reduction problem is solved via a frequency weighted model reduction problem     

基于PID和LQR的四旋翼无人机控制系统研究

为提高四旋翼无人机的飞行稳定性、无人飞行器控制系统的鲁棒性和控制精度,以建立的四旋翼无人机飞行控制系统模型为基础,采用现代控制理论与传统控制论相结合的方法,针对姿态角速率、姿态角分别设计内环LQR(线性二次型调节器)控制器,及外环PID控制的双回路闲环控制器.充分利用PID控制器易于掌握且对模型要求精度低、LQR控制器能改善内回路的动态特性和稳态性能的特点,完成四旋翼无人机的飞行控制.通过实验遴选该双闭环控制器相关参数并进行优化,实验结果表明所设计的双回路控制器控制性能指标良好.     

Sampled-data controller reduction procedure

The problem of controller order reduction aimed at preserving the closed-loop performance of a sampled-data closed-loop system is investigated. Past sampling of the system at a multiple of the sampling frequency followed by lifting allows capturing of the system's intersample behavior and yields a time-invariant single-rate system; this then permits standard order-reduction ideas to be applied. Special weighting functions aimed at preserving the closed-loop transfer function are obtained, and weighted balanced truncation is used to reduce the controller, An example shows that without the use of fast-sampling, an unstable closed loop can result from the reduction     

PID控制器的性能监控与评估

为了解决目前工业系统中普遍使用的PID控制器由于工况变化等原因引起的系统发生时变而导致所在回路PID控制器性能可能下降的问题,本文提出了一种专门针对PID控制器进行性能评估、优化及监控的方法,即:PID循环评估优化算法。该算法利用系统闭环输入输出数据,使用基于MVC(minimum variance control)的PID最小方差准则,来对PID控制器的性能进行评估,并且计算出在最小方差意义下最优PID控制器参数;评估过程结果与现实系统输出方差进行比较,做为PID参数在线优化的判断依据,当现实系统性能低于某一标准的时候对控制器进行优化处理。在整个算法中,通过输入输出数据的处理与判断,利用评估优化后的PID参数对系统进行控制,并再次回到最初的输入输出数据的处理和判断过程,实现在控制过程中的系统性能监控。本文的计算机仿真试验验证了该方法的有效性,由图可看出,系统发生渐变和突变后,当输出方差超过了程序限定的标准时,在1 300秒内系统能自动评估并施行优化而达到稳定。该循环评估优化算法现实了在对系统进行性能评估监控的同时,能按照一定条件作为标准对系统的PID参数进行优化,最终使得系统具有自我监控评估和自我优化的能力...     

Robust Constrained Model Predictive Control for Discrete‐Time Uncertain System in Takagi‐Sugeno's Form

In this paper, we investigate a robust constrained model predictive control synthesis approach for discrete‐time Takagi‐Sugeno's (T‐S) fuzzy system with structured uncertainty. The key idea is to determine, at each sampling time, a state feedback fuzzy predictive controller that minimizes the performance objective function in the infinite time horizon by solving a class of linear matrix inequalities (LMIs) optimization problem. To do this, the fuzzy predictive controller is designed on the basis of non‐parallel distributed compensation (non‐PDC) control law, relaxed stability conditions of the closed‐loop fuzzy system are developed by employing an extended nonquadratic Lyapunov function and introducing additional slack and collection matrices. In addition, the presented approach is capable of ensuring the robust asymptotic stability as well as the recursive feasibility of the closed‐loop fuzzy system. Simulations on a highly nonlinear continuous stirred tank reactor (CSTR) are eventually presented to demonstrate the effectiveness of the developed theoretical approach.