分数阶参数不确定系统的PI^λ控制器

利用求解分数阶参数不确定系统稳定域的方法,设计了使分数阶参数不确定系统具有鲁棒性的分数阶PIλ控制器.首先采用Kharitonov理论,将分数阶参数不确定系统分解成若干个参数确定的子系统,然后用D分解方法分别求出在PIλ控制器的控制下,使各个子系统都取得较大稳定域的参数λ值.再采用此λ值构建PIλ控制器并计算各个子系统的稳定域.各个子系统稳定域的交集即为参数不确定系统在PIλ控制器控制下的稳定域.同时证明了所构建的PIλ控制器能稳定整个参数不确定系统组.最后在稳定域内取控制器参数值,便构成了所设计的PIλ控制器.文中采用实例对此设计方法进行验证,并用所构建的PIλ控制器对参数不确定系统组的各个子系统进行阶跃响应分析,结果表明PIλ控制器对参数不确定系统具有较强的鲁棒性.     

二级倒立摆的参数自校正模糊PI控制

为了解决高阶次、多变量、非线性、强耦合的直线二级倒立摆的稳定控制问题,设计了一种参数自校正模糊PI控制器算法。结合线性二次型最优调节器(LQR)方法,设计了融合函数,降低了模糊控制器的维数、减少了控制器规则数、实现了参数在线自校正,进而提高了控制器的性能。借助固高科技倒立摆硬件平台,采用MATLAB仿真及实时控制,系统均能在较短时间内达到稳定,且控制效果较好,满足了稳定性和鲁棒性要求。     

精馏塔时滞过程的分数阶PIλDμ控制器设计

本文针对精馏塔不稳定时滞过程,提出一种基于设定值加权的分数阶PIλDμ控制器设计方法.首先采用比例环节构成内环反馈镇定不稳定时滞过程,然后基于等效的过程模型,依据设定值加权方法设计分数阶PIλDμ控制器,并进行了控制器参数整定.仿真结果表明:分数阶PIλDμ控制器可以使精馏塔不稳定时滞过程系统获得良好的动态响应特性,干扰抑制特性以及克服系统参数变化的鲁棒性.     

倒立摆的自适应积分反步控制策略

针对直线单级倒立摆在模型参数不确定和外部扰动情况下的稳定控制问题,提出一种自适应积分反步控制策略。采用拉格朗日方程建立倒立摆系统的运动学模型,为减少稳态误差,将误差积分项引入反步法,设计了倒立摆的控制器;对含有未知参数的系统非线性状态微分方程,设计适当的Lyapunov函数推导出系统未知参数的自适应更新律,削弱了参数不确定性的影响。将自适应积分反步控制与一般的反步法控制、模糊控制及神经网络控制的仿真结果进行了对比,并在LabVIEW开发环境下进行了实物实验。结果表明,自适应积分反步法可以较为迅速且精确地完成稳定控制,较好地克服系统参数不确定及外部扰动的影响,具有较强的鲁棒性。     

一种可自恢复的燃调数字控制器设计及实现

倒立摆系统具有多变量、非线性、强耦合和不确定的特点,常被用来验证控制算法的优劣性。H∞在干扰抑制和鲁棒性上均有较为突出的表现。在对倒立摆控制研究情况和 H∞控制理论发展情况进行简单介绍后,围绕一阶回旋式倒立摆的H∞控制进行研究。首先,基于拉格朗日方程对一阶倒立摆进行动力学分析,并近似地得到平衡点附近的线性方程;对倒立摆系统进行分析,得到倒立摆系统是能观能控系统、但平衡点不稳定的结论。其次,简单介绍基于里卡蒂方程的 H∞控制器求解方法,并证明该控制器能够保证系统的稳定性。最后,仿真确定加权矩阵各元素和 H∞性能指标的大小对系统性能的影响和对电机扭矩的要求,并最终确定一组相对合适的参数进行控制器设计。     

回旋式倒立摆的H∞控制

倒立摆系统具有多变量、非线性、强耦合和不确定的特点,常被用来验证控制算法的优劣性。H∞在干扰抑制和鲁棒性上均有较为突出的表现。在对倒立摆控制研究情况和 H∞控制理论发展情况进行简单介绍后,围绕一阶回旋式倒立摆的H∞控制进行研究。首先,基于拉格朗日方程对一阶倒立摆进行动力学分析,并近似地得到平衡点附近的线性方程;对倒立摆系统进行分析,得到倒立摆系统是能观能控系统、但平衡点不稳定的结论。其次,简单介绍基于里卡蒂方程的 H∞控制器求解方法,并证明该控制器能够保证系统的稳定性。最后,仿真确定加权矩阵各元素和 H∞性能指标的大小对系统性能的影响和对电机扭矩的要求,并最终确定一组相对合适的参数进行控制器设计。     

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.     

基于滑模变结构的柔性倒立摆控制研究

针对柔性倒立摆稳摆控制比较困难且传统指数趋近率的滑模变结构控制易对系统造成抖振,基于机理建模方法建立柔性倒立摆数学模型,提出变指数趋近率的滑模变结构控制方法,设计了滑模变结构控制器,使系统具有较好的稳摆控制和鲁棒性。仿真结果表明,基于变指数趋近率的滑模变结构控制方法能够更好的实现倒立摆稳定控制,相比于传统指数趋近率的滑模控制器输出更加平滑,进而减小了控制器的负担。     

基于BF-PSO的船舶电站柴油机分数阶控制器

针对船舶电力系统的频率稳定性问题,对船舶电站柴油机调速系统设计了分数阶PIλDμ控制器。采用细菌觅食-粒子群混合优化(BF-PSO)算法对分数阶PIλDμ控制器参数进行优化整定,解决了分数阶PIλDμ控制器整定参数多、设计复杂的问题。对分别采用分数阶PIλDμ控制器和传统整数阶PID控制器的柴油机调速系统进行了仿真和对比。结果表明,在同等条件下优化得到的分数阶PIλDμ控制器能够有效抑制模型参数摄动,鲁棒性更强,具有更好的控制效果。     

一类分数阶系统的分析及控制器设计

针对一类与传统一阶惯性环节传递函数结构类似的分数阶系统,推导出该类分数阶系统稳定的参数取值范围,并给出了不同时间响应与分数阶阶次的对应关系.然后基于该类分数阶系统同时设计了分数阶PIλ控制器和整数阶PI控制器,控制器参数采用粒子群优化算法得到.结果表明:在控制该类对象时两者均能取得很好的控制效果,证明了本文所提方法的有效性.但由于整数阶PI控制器比分数阶PIλ控制器简单且便于实现,因此在工程应用中针对该类分数阶对象选择PI控制器即可满足要求.     

Tuning fractional order proportional integral controllers for fractional order systems

In this paper, two fractional order proportional integral controllers are proposed and designed for a class of fractional order systems. For fair comparison, the proposed fractional order proportional integral (FOPI), fractional order [proportional integral] (FO[PI]) and the traditional integer order PID (IOPID) controllers are all designed following the same set of the imposed tuning constraints, which can guarantee the desired control performance and the robustness of the designed controllers to the loop gain variations. This proposed design scheme offers a practical and systematic way of the controllers design for the considered class of fractional order plants. From the simulation and experimental results presented, both of the two designed fractional order controllers work efficiently, with improved performance comparing with the designed stabilizing integer order PID controller by the observation. Moreover, it is interesting to observe that the designed FO[PI] controller outperforms the designed FOPI controller following the proposed design schemes for the class of fractional order systems considered.     

Design and Robust Performance Evaluation of a Fractional Order PID Controller Applied to a DC Motor

This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 23 factorial experimental design for a fractional order proportional integral and derivative controller (FOPID), integer order proportional integral and derivative controller (IOPID) and the Skogestad internal model control controller (SIMC). The factors assumed in experiment are the presence of random noise, external disturbances in the system input and variable load. As output variables, the experimental design employs the system step response and the controller action. Practical implementation of FOPID and IOPID controllers uses the MATLAB stateflow toolbox and a NI data acquisition system. Results of the robustness analysis show that the FOPID controller has a better performance and robust stability against the experiment factors.      

Pitch Loop Control of a VTOL UAV Using Fractional Order Controller

Pitch loop control is the fundamental tuning step for vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs), and has significant impact on the flight. In this paper, a fractional order strategy is designed to control the pitch loop of a VTOL UAV. First, an auto-regressive with exogenous input (ARX) model is acquired and converted to a first-order plus time delay (FOPTD) model. Next, based on the FOPTD model, a fractional order [proportional integral] (FO[PI]) controller is designed. Then, an integer order PI controller based on the modified Ziegler-Nichols (MZNs) tuning rule and a general integer order proportional integral derivative (PID) controller are also designed for comparison following three design specifications. Simulation results have shown that the proposed fractional order controller outperforms both the MZNs PI controller and the integer order PID controller in terms of robustness and disturbance rejection. At last, ARX model based system identification of AggieAir VTOL platform is achieved with experimental flight data.     

Stabilizing and robust fractional order PI controller synthesis for first order plus time delay systems

For all the stable first order plus time delay (FOPTD) systems, a fractional order proportional integral (FOPI) or a traditional integer order proportional integral derivative (IOPID) controller can be designed to fulfill a flat phase constraint and two design specifications simultaneously: gain crossover frequency and phase margin. In this paper, a guideline for choosing two feasible or achievable specifications, and a new FOPI/IOPID controller synthesis are proposed for all the stable FOPTD systems. Using this synthesis scheme, the complete feasible region of two specifications can be obtained and visualized in the plane. With this region as the prior knowledge, all combinations of two specifications can be verified before the controller design. Especially, it is interesting to compare the areas of these two feasible regions for the IOPID and FOPI controllers. This area comparison reveals, for the first time, the potential advantages of one controller over the other in terms of achievable performances. A simulation illustration is presented to show the effectiveness and the performance of the designed FOPI controller compared with the optimized integer order PI controller and the IOPID controller designed following the same synthesis for the FOPI in this paper.     

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.     

Optimal fractional order PIλDμ controller for stabilization of cart‐inverted pendulum system: Experimental results

The cart‐inverted pendulum is a non‐minimum phase system having right half s‐plane pole and zero in close vicinity to each other. Linear time invariant (LTI) classical controllers cannot achieve satisfactory loop robustness for such systems. Therefore, in the present work the fractional order PI^λD^μ (FOPID) controller is addressed for robust stabilization of the system, since fractional order controller design allows more degrees of freedom compared to its integer order counterparts by virtue of its two parameters λ and μ. The controller parameters are tuned by three evolutionary optimization techniques. In order to select the controller parameters optimally, a novel non‐linear fitness function using integral time square error (ITSE), settling‐time, and rise time is proposed here. The control algorithm is implemented successfully in real‐time. Moreover, stability analysis of the system compensated with a fractional order controller is presented using Riemann surface. Robustness of the physical cart‐inverted pendulum system towards multiplicative gain variations and plant parameter variations is verified. In this regard, it is shown that the fractional order controller provides satisfactory robust performance in both simulation and real‐time system.     

基于强化学习的倒立摆分数阶梯度下降RBF控制

为了提高强化学习的控制性能,提出一种基于分数梯度下降RBF神经网络的强化学习算法.通过评价神经网络和执行神经网络组成强化学习系统,利用神经网络记忆和联想,学会控制倒立摆,提高控制精度,使误差趋于零,直至学习成功,并证明闭环系统的稳定性.通过倒立摆的物理实验发现,当分数阶阶数较大,微分的作用更显著,对角速度和速度的控制效果更好,角速度和速度的均方误差和平均绝对误差较小;当分数阶阶数较小,积分的作用更显著,对倾斜角和位移的控制效果更好,因此倾斜角和位移的均方误差和平均绝对误差较小.仿真实验的结果表明,所提算法动态响应好,超调量小,调整时间短,精度高,泛化性能好.它优于基于RBF神经网络的强化学习算法和传统强化学习算法,能有效地加快梯度下降法的收敛速度,提高其控制性能.在引入适当的干扰后,所提算法能够快速地自我调节并恢复稳定状态,控制器的鲁棒性和动态性能满足实际要求.     

倒立摆系统自适应高阶微分反馈控制

利用提取的系统高阶微分信息,提出了自适应高阶微分反馈控制器.某种程度上该控制器不依赖于单输入单输出(SISO)非线性仿射系统的模型.并且分析了闭环系统的稳定性和鲁棒性.通过将摆角方程的位移加速度看作是控制输入,将倒立摆系统转化成相互影响的两个SISO仿射系统,从而用两个串级高阶微分反馈控制器成功地实现了倒立摆系统的镇定与调节.数字仿真表明,控制器对摆的基准模型实现了较为满意的控制,而且该控制方法对非线性摩擦项,对摆长、摆质量、小车质量等参数变化以及外扰动具有强鲁棒性.