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.     

基于鲁棒观测器的非线性系统滑模控制

针对一类非线性不确定时滞系统,分别考虑了观测器的设计和控制器的设计问题.首先,基于扩张状态方程,设计鲁棒观测器;其次,基于观测器估计的状态值,融合H∞控制技术,设计了滑模控制器,并且将滑模控制器增益系数的计算问题转化为线性矩阵不等式的求解问题,而且所设计的滑模控制器不要求系统不确定项满足匹配条件,使得控制器具有广泛的使用范围;最后,给出数值算例,将设计的观测器和控制器应用算例中,仿真表明该方法的有效性.     

导弹鲁棒分数阶PID自动驾驶仪设计

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,因此针对导弹飞行过程中变参数、受环境干扰及快速稳定的特点,设计了鲁棒分数阶PID自动驾驶仪.基于最优Oustaloup数字算法建立框图式分数阶控制系统模型,结合IAE时域性能指标寻优及鲁棒性能量度,综合考虑时域性能及频域性能来整定分数阶PID...     

基于群灰狼优化的光伏逆变器最优无源分数阶PID控制

针对并网光伏逆变器(PV)设计最优无源分数阶PID(PFoPID)控制,其可在不同天气条件下,通过扰动观测(P&O)技术实现最大功率追踪(MPPT).首先,基于跟踪误差构建储能函数,保留系统阻尼有益项以提高跟踪速率,并完全补偿其他的系统非线性以实现全局一致的控制性能.然后,引入分数阶PID(FoPID)控制作为附加控制输入,对储能函数进行能量重塑,并通过群灰狼优化算法(GGWO)获取最优控制参数.对3种算例进行研究,即光照强度变化、温度变化和电网电压跌落,仿真结果表明,与常规PID控制、Fo PID控制和无源控制(PBC)相比,PFoPID控制在各类工况下能够实现最大功率追踪并具有较好的动态特性.最后,基于dSpace的硬件在环(HIL)实验验证了所提出方法的硬件可行性.     

基于观测器的机器人鲁棒跟踪控制

基于滑模控制原理设计稳定的状态观测器，在此基础上。研究了仅有关节角位移可测量的机器人轨迹跟踪控制问题。运用反推设计方法提出一种机器人鲁棒跟踪控制新方案。通过引入用于抑制观测误差的阻尼项和调制参数。加快了输出跟踪误差的收敛速度。利用李亚普诺夫方法分析了闭环控制系统的全局稳定性，证明了系统所有状态信号有界，跟踪误差收敛到零。仿真结果进一步表明，提出的控制方案具有较强的鲁棒性和良好的跟踪性能。     

基于分数阶滑模控制的无人机轨迹跟踪控制器设计

四旋翼无人机在农业、工业和国防等领域广泛应用,但其复杂的系统特性和对扰动的敏感性使得控制变得困难。首先,考虑分数阶方法具有良好的鲁棒性以及调节灵活性的优点,将整数阶积分滑模面和改进的分数阶指数趋近律相结合,设计出了一种新的分数阶积分滑模控制器。然后,将所设计的分数阶积分滑模控制器应用于四旋翼无人机轨迹跟踪控制问题。仿真结果表明,所提控制器作用下的四旋翼无人机进行轨迹跟踪时响应速度快、无超调,且对外界干扰具有较强的鲁棒性。     

小功率光伏发电逆变器的设计

设计以TMS320LF2407型DSP为核心的小功率光伏发电逆变器。主电路采用全桥式逆变器,针对传统PI控制的不足,采用了PI控制和重复控制相结合的控制策略,以实现输出电流与电网电压可靠同步。采用了电导增量法实现了最大输出功率（MPPT）的快速、稳定跟踪。实验结果表明所设计的逆变器运行稳定可靠,可用于小型光伏发电系统。     

基于RBF神经网络的PMSM分数阶互补滑模控制

参数变化及外部不确定性干扰等因素对永磁同步电机(PMSM)驱动控制系统影响较大,针对这一问题,提出一种基于RBF神经网络的分数阶互补滑模控制方法。在建立PMSM数学模型的基础上,采用RBF神经网络对外部干扰进行逼近估计。设计基于饱和函数的分数阶互补滑模控制器,并将RBF神经网络估计的干扰引入控制器中,以抵消外部干扰对系统的影响。理论证明,该控制策略在对外部不确定性干扰进行有效抑制的同时保证系统跟踪误差收敛。通过仿真验证所提方法的有效性。     

基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统设计

为了保证机器人能够在保持稳定的情况下,按照规划轨迹执行工作任务,从硬件和软件两个方面,设计了基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统。装设机器人传感器与状态观测器,改装机器人鲁棒滑模跟踪控制器,完成系统硬件设计;综合机器人结构、运动机理和动力机制3个方面,构建机器人数学模型;根据状态数据采集结果与规划轨迹之间的偏差,计算机器人跟踪控制量;依据滑模运动与切换方程,利用Sigmoid函数生成机器人鲁棒滑模控制律,将生成控制指令作用在机器人执行元件上,实现系统的鲁棒滑模跟踪控制功能;在系统测试与分析中,所设计控制系统的平均位置跟踪控制误差为0.93 mm,与设定轨迹目标基本重合,机器人姿态角跟踪控制误差为0.06 mm,具有较好的鲁棒滑模跟踪控制效果,能够有效提高机器人鲁棒滑模跟踪控制精度。     

基于扰动观测器的永磁同步发电机最大功率跟踪滑模控制

本文设计了一款基于扰动观测器的滑模控制(perturbation observer based sliding-mode control, POSMC)来实现永磁同步发电机(permanent magnetic synchronous generator, PMSG)的最大功率跟踪(maximum power point tracking, MPPT).首先,将发电机非线性、参数不确定、以及随机风速聚合成一个扰动,并通过扰动观测器对其进行在线估计.随后,采用滑模控制(sliding-mode control, SMC)对该扰动估计进行实时完全补偿,从而实现不同工况下的控制全局一致性以及各类不确定环境下的鲁棒控制.同时, POSMC采用扰动实时估计值进行补偿来代替传统SMC中所使用的扰动上限值进行补偿,因此可有效解决传统SMC过于保守的缺点,使得控制成本更为合理.最后, POSMC无需精确的PMSG模型,仅需测量d轴电流和机械转速,易于实现.本文进行了3个算例研究,即阶跃风速、随机风速和发电机参数不确定.仿真结果表明,与矢量控制(vector control, VC)和SMC相比, POSMC在各类工况下均可捕获最大风能并具有较强的鲁棒性.基于d Space的硬件在环实验(hardware-in-loop, HIL)验证了所提算法的可行性.     

新型MPPT算法在光伏并网系统中的应用

光伏并网系统在天气急剧变化时,采用传统的最大功率跟踪算法会产生较大误判,不仅造成电池板功率的损失,而且还会导致并网电流的畸变。针对这一问题,对传统扰动观察法进行了改进,提出了一种新型MPPT算法,有效地防止了功率误判。将此新型算法配合电压电流双环控制应用于光伏并网系统。从仿真结果看到,在光照突变和电网电压扰动时,并网电流均能够快速跟踪电网电压的相位和频率。表明了新型算法的正确性和有效性。     

基于模糊控制的最大功率点跟踪算法的研究

本文根据太阳能电池的特性方程进行优化得到其工程模型并建立MATLAB/SIMULINK仿真模型,同时对仿真结果进行简单分析,主要是分析太阳能电池在标准参数下的伏安特性和伏瓦特性,以及在不同温度和光照强度条件下的特性。介绍最大功率点跟踪(MPPT)的原理并采用扰动观察法进行了定步长的仿真并对其结果进行了分析,在其基础上进行改进,提出一种基于模糊控制的变步长扰动观察算法,应用MATLAB中的Fuzzy工具箱进行模糊控制器的设计。得出的仿真结果表明,本算法能够稳定在最大功率点,避免了定步长扰动观察法在最大功率点的震荡,在环境参数突变的情况下,能够快速寻找到新的最大功率点,具有良好的跟踪效果。     

Robust iterative learning control of single-phase grid-connected inverter

For the single phase inductance-capacitance-inductance (LCL) grid-connected inverter in micro-grid, a kind of robust iterative learning controller is designed. Based on the output power droop characteristics of inverter, the current sharing among the inverters is achieved. Iterative learning strategy is suitable for repeated tracking control and inhibiting periodic disturbance, and is designed using robust performance index, so that it has the ability to overcome the uncertainty of system parameters. Compared with the repetitive control, the robust iterative learning control can get high precision output waveform, and enhance the tracking ability for waveform, and the distortion problem of the output signal can be solved effectively.     

Unified MPPT controller for partially shaded panels in a photovoltaic array

The power output of the photovoltaic (PV) system having multiple arrays gets reduced to a great extent when it is partially shaded due to environmental hindrances. The maximum power trackers which are conventionally used may not be competent enough to find the maximum power point (MPP) during partially shaded conditions. The sensible reason for the failure of conventional trackers is during partial shaded conditions the PV arrays exhibit multi peak power curves, thereby making simple maximum power point tracking (MPPT) algorithms like perturb and observe (P&O) to get stuck with local maxima instead of capturing global maxima. Therefore, global search MPPT aided by evolutionary and swarm intelligence algorithms will be conducive to find global power point during partially shaded conditions. This work suggests a unified controller which feeds control signal to its power electronic conditioner placed at each module. The evolutionary algorithm which is taken into consideration in this work is differential evolution (DE). The performance of the proposed method is compared to the classical un-dimensional search controller and it is evident from the Matlab/Simulink results that the unified controller prevails over the distributed counterpart.     

基于TMS320F2812的25kW光伏并网变流器

文章介绍了基于TMS320F2812的25kW三相光伏并网变流器。该光伏并网变流器采用双级结构,能实现最大功率点跟踪以及反孤岛效应的功能,控制策略采用基于TMS320F2812型DSP的空间矢量脉冲宽度调制技术,能实现与电网同步的正弦电流输出。     

Fractional-order sliding mode load following control via disturbance observer for modular high-temperature gas-cooled reactor system with disturbances

Load-following control of the modular high-temperature gas-cooled reactor (MHTGR) system is one of the essential control problems in practical applications. In this paper, a fractional-order sliding mode control strategy via a disturbance observer (FOSMCS-DO) is presented for load following of the MHTGR system with model uncertainties and external disturbances. First of all, the mathematical model of the MHTGR system is constructed by taking neutronics and thermodynamics as well as disturbances into account. Then, based on the MHTGR model, a DO is designed to estimate the lumped disturbances that are composed of model uncertainties, external disturbances, and unmeasured states. Meanwhile, by adopting the Lyapunov stability theory, a FOSMCS is developed to guarantee all the signals of the closed-loop load-following control system tend to be stable, where in the control framework, the adverse effects of the lumped disturbances are alleviated by means of the feedforward compensation and the DO. This implies that the proposed overall control strategy possesses strong robustness against model uncertainties and external disturbances. Finally, comparative simulation results with some existing control approaches are provided to illustrate the superiority of the proposed control strategy.     

反步自适应滑模变结构的小卫星姿态鲁棒容错控制

针对小卫星在轨运行中存在输入饱和、干扰力矩与执行器故障的姿态跟踪控制问题,提出了一种反步自适应滑模变结构鲁棒容错控制方法。该方法将反步控制和滑模控制相结合,利用自适应算法估计执行器有效因子最小值和干扰上界,避免了对故障的检测与隔离,实现了输入饱和、干扰和故障对系统稳定性影响的抑制。基于Lyapunov方法从理论上证明了闭环系统的稳定性;将该方法用于小卫星的状态跟踪控制,仿真结果表明该控制器能有效处理姿态控制时输入饱和受限的约束,对部分失效和偏差型故障具有较强的容错能力,并具有一定鲁棒性。     

Robust sliding-mode observer-based multiple-fault diagnosis scheme

In this study, we simultaneously evaluate the multiple-fault diagnosis problem of a class of Lipschitz nonlinear systems with actuator and sensor faults and unknown input disturbances. A nonsingular system transformation is used to transform the original system into two subsystems for multiple-fault diagnosis: subsystems 1 and 2. At the system level, two robust sliding-mode observers (RSMOs) are proposed. An RSMO is designed for subsystem 1 to detect actuator faults subjected to unknown input disturbances, and another RSMO is designed for subsystem 2 to detect sensor faults subjected to actuator faults. At the component level, a bank of RSMOs is proposed to detect and isolate actuators (sensors) with faults using a dedicated observer scheme. The reachability of RSMOs is comprehensively investigated in the estimation error space. Accordingly, the proposed observer parameters are designed as an optimization problem and solved using the linear matrix inequality (LMI) optimization technique. The effectiveness of the proposed multiple-fault diagnosis scheme was validated through simulations of a modified seventh-order aircraft system.     

Finite-time containment control of perturbed multi-agent systems based on sliding-mode control

Aimed at faster convergence rate, this paper investigates finite-time containment control problem for second-order multi-agent systems with norm-bounded non-linear perturbation. When topology between the followers are strongly connected, the nonsingular fast terminal sliding-mode error is defined, corresponding discontinuous control protocol is designed and the appropriate value range of control parameter is obtained by applying finite-time stability analysis, so that the followers converge to and move along the desired trajectories within the convex hull formed by the leaders in finite time. Furthermore, on the basis of the sliding-mode error defined, the corresponding distributed continuous control protocols are investigated with fast exponential reaching law and double exponential reaching law, so as to make the followers move to the small neighbourhoods of their desired locations and keep within the dynamic convex hull formed by the leaders in finite time to achieve practical finite-time containment control. Meanwhile, we develop the faster control scheme according to comparison of the convergence rate of these two different reaching laws. Simulation examples are given to verify the correctness of theoretical results.