反坦克导弹最优一体化制导与控制

将导弹一目标相对运动信息引入到导弹控制模型中,对侧滑转弯（STT）反坦克导弹的俯仰和偏航推导得出了制导控制一体化数学模型,然后设计了基于最优控制理论的线性二次型（LQ）软终端约束控制器,最后进行了六自由度弹道仿真,结果表明最优一体化制导控制方法可有效地将导弹导向目标,且满足制导精度要求。     

一种非线性优化控制方法及其在鱼雷控制中的应用

提出了一种带优化修正函数的非线性ＰＩＤ控制器设计方法,通过对控制器参数离线寻优,并对修正函数在线优化调整,可用它设计出性能优良且易于工程实现的控制器,然后用地为某型鱼雷非线性系统设计了弹道深义控制器并在各种人水条件下进行了仿真研究,仿真表明,所设计的鱼雷非线笥弹道深度控制系统具有良好的动、静态特性,且对鱼雷人水条件的变化具有较强的适应性。     

An Optimal Control Strategy for Multi-UAVs Target Tracking and Cooperative Competition

An optimal control strategy of winner-take-all (WTA) model is proposed for target tracking and cooperative competition of multi-UAVs (unmanned aerial vehicles). In this model, firstly, based on the artificial potential field method, the artificial potential field function is improved and the fuzzy control decision is designed to realize the trajectory tracking of dynamic targets. Secondly, according to the finite-time convergence high-order differentiator, a double closed-loop UAV speed tracking the controller is designed to realize the speed control and tracking of the target tracking trajectory. Numerical simulation results show that the designed speed tracking controller has the advantages of fast tracking, high precision, strong stability and avoiding chattering. Finally, a cooperative competition scheme of multiple UAVs based on WTA is designed to find the minimum control energy from multiple UAVs and realize the optimal control strategy. Theoretical analysis and numerical simulation results show that the model has the fast convergence, high control accuracy, strong stability and good robustness.      

步进驱动系统大振荡机理与轨迹优化控制

为了解决步进驱动系统运动控制中的振荡、 丢步和失调等问题, 改善步进驱动系统的控制性能, 优化步进驱动系统的控制, 通过研究步进驱动系统的微步驱动控制过程, 建立了步进驱动系统的微步驱动数学模型, 提出了步进驱动系统的仿真建模方法, 通过仿真模型的数值模拟分析了大振荡、丢步及失调问题的产生原因并 建立了大振荡及丢步的机理模型, 在此基础上进一步提出了基于稳态截止频率的速度轨迹优化控制方法. 最后, 通过一个实例进行了实验验证. 结果表明: 该建模方法能够准确地描述步进驱动系统的特性, 速度轨迹优化控制方法能够有效地消除摆臂系统的大振荡、 丢步、失调等严重问题, 显著提高了摆臂系统运动平稳性及精密定位能力.     

基于IPC与运动控制卡的机器人运动控制系统

工控机(IPC)和运动控制卡组成的开放式机器人控制系统,具有可靠性高、信息处理能力强、开放程度高、运动轨迹准确等优点,利用其来进行六自由度关节机器人的运动控制系统的开发.IPC实现上位机功能,完成人机交互、运动学运算等任务.下位机采用PMAC运动控制卡,对各关节电机进行伺服控制.上位机基于Visual C++编程,通过调用PMAC的动态链接库编写上位机人机界面实现对PMAC卡的控制,另外介绍了伺服驱动器的设置以及PMAC的PID调节.实践证明这套系统工作可靠,完全满足要求.     

基于内模扩展LQ方法的WMR轨迹跟踪控制

针对现有非线性控制方案的一些瓶颈问题,从线性控制的角度出发,开展了一种用于WMR的线性二次型最优控制方法设计的研究.首先,基于WMR的运动学模型采用动态反馈线性化技术将非线性运动学模型转化为线性模型;然后,选取跟踪误差及误差收敛速度作为设计指标;同时考虑实现渐进跟踪,针对不同形式的参考轨迹,根据内模原理对控制器模态进行扩展,利用线性模型设计基于内模扩展LQ最优轨迹跟踪控制器;最后通过动态反馈反变换得到实际控制器.此外,通过将此方法的控制效果与几种经典方法进行仿真比对,说明了此方法对于跟踪的精确性和快速性上有较大优势.     

间歇过程最优迭代学习控制的发展:从基于模型到数据驱动

本文综述了间歇过程的基于模型的和数据驱动的最优迭代学习控制方法.基于模型的最优迭代学习控制方法需要已知被控对象精确的线性模型,其研究较为成熟和完善,有着系统的设计方法和分析工具.数据驱动的最优迭代学习控制系统设计和分析的关键是非线性重复系统的迭代动态线性化.本文简要综述了基于模型的最优迭代学习控制的研究进展,详细回顾了数据驱动的迭代动态线性化方法,包括其详细的推导过程和突出的特点.回顾和讨论了广义的数据驱动最优迭代学习控制方法,包括完整轨迹跟踪的数据驱动最优迭代学习控制方法,提出和讨论了多中间点跟踪的数据驱动最优点到点迭代学习控制方法,和终端输出跟踪的数据驱动最优终端迭代学习控制方法.进一步,迭代学习控制研究中的关键问题,如随机迭代变化初始条件、迭代变化参考轨迹、输入输出约束、高阶学习控制律、计算复杂性等.本文突出强调了基于模型的和数据驱动的最优迭代学习控制方法各自的特点与区别联系,以方便读者理解.最后,本文提出数据驱动的迭代学习控制方法已成为越来越复杂间歇过程控制发展的未来方向,一些开放的具有挑战性的问题还有待于进一步研究.     

空间机器人最优能耗捕获目标的自适应跟踪控制

提出了一种能够引导末端执行器以期望速度跟踪目标的轨迹规划方法。该方法可以实现避障并满足关节限制要求。基于轨迹规划方法,设计了一种利用自由飘浮空间机器人跟踪与捕获章动自旋卫星的自适应控制策略。此外,该控制策略还考虑了最优能耗、测量误差和优化误差。首先,为了使执行器的跟踪误差和机械臂的能耗最小,将空间机器人的控制策略描述为一个关于关节速度、力矩和避障距离的不等式约束优化问题。然后,推导出一个系数为下三角矩阵的显式状态方程,并对目标函数进行解耦和线性化。设计了一种关节速度和力矩分段优化方法去代替传统的凸二次规划方法求解最优问题,这种方法具有较高的计算效率。最后,利用李雅普诺夫稳定性理论验证了所提控制方法的收敛性。     

Neighboring optimal control for periodic tasks for systems with discontinuous dynamics

We propose a trajectory-based optimal control method for periodic tasks for systems with discontinuous dynamics. A general method, dynamic programming, suffers from the problem of dimensionality. We use local models of the optimal control law to construct a local controller. We combine a parametric trajectory optimization method and differential dynamic programming (DDP) to find the optimal periodic trajectory in a periodic task. By formulating the optimal control problem with an infinite time horizon, DDP ...     

基于故障程度的四旋翼无人机容错控制

针对四旋翼无人机执行机构部分失效故障,采用一组线性二次最优控制器,并且设计了可变因子二阶卡尔曼滤波器在线快速估计状态和检测故障。当故障被检测和诊断出来时,通过可变因子二阶卡尔曼滤波器调节,同时切换到相应的线性二次最优控制器使故障影响变小。最后,在Matlab实验平台上对所提方法的可行性和有效性进行仿真验证验证,结果表明四旋翼无人机执行机构在发生部分失效故障时,输出信号能够快速跟踪轨迹,实现了对执行机构部分失效故障的容错控制。     

Optimal Decoupling Control Method and Its Application to a Ball Mill Coal-pulverizing System

The conventional optimal tracking control method cannot realize decoupling control of linear systems with a strong coupling property. To solve this problem, in this paper, an optimal decoupling control method is proposed, which can simultaneously provide optimal performance. The optimal decoupling controller is composed of an inner-loop decoupling controller and an outer-loop optimal tracking controller. First, by introducing one virtual control variable, the original differential equation on state is converted to a generalized system on output. Then, by introducing the other virtual control variable, and viewing the coupling terms as the measurable disturbances, the generalized system is open-loop decoupled. Finally, for the decoupled system, the optimal tracking control method is used. It is proved that the decoupling control is optimal for a certain performance index. Simulations on a ball mill coal-pulverizing system are conducted. The results show the effectiveness and superiority of the proposed method as compared with the conventional optimal quadratic tracking (LQT) control method.      

Time-optimal reorientation for rigid satellite with reaction wheels

This article introduces a time-optimal reorientation manoeuvre controller with saturation constraints on both reaction wheels’ torques and angular momentum. The proposed control scheme consists of two parts. The first part is an open-loop time-minimum reorientation trajectory generated by the Legendre pseudospectral method. Actuator dynamics, saturations on control torques and angular momentums of reaction wheels are taken into account in generating the open-loop optimal trajectory. The second part is a closed-loop tracking control law to track the optimised reference trajectory based on attitude error dynamics with reaction wheel dynamics. Numerical simulations show that reaction wheel dynamics play an important role in attitude manoeuvres. The proposed controller performs better for rest-to-rest reorientation manoeuvre than other existing methods.     

A unified symplectic pseudospectral method for motion planning and tracking control of 3D underactuated overhead cranes

In this paper, a unified symplectic pseudospectral method for motion planning and tracking control of 3D underactuated overhead cranes is proposed. A feasible reference trajectory taking constraints into consideration is first generated offline by the symplectic pseudospectral optimal control method. Then, a trajectory tracking model predictive controller also based on the symplectic pseudospectral method is developed to track the reference trajectory. At each sampling instant, the trajectory tracking controller works by solving an open‐loop optimal control problem where linearized system dynamics is used instead to improve the computational efficiency. Since the symplectic pseudospectral optimal control method is the core algorithm for both offline trajectory planning and online trajectory tracking, constraints on state variables and control inputs can be easily imposed and hence theoretically guaranteed in solutions. By selecting proper weighted matrices on tracking error and control, the developed controller could achieve control objectives in both accurate trolley positioning and fast suppressing of residual swing angles. Simulations for 3D overhead crane systems in the presence of perturbations in initial conditions, an abrupt variation of system parameter, and various external disturbances demonstrate that the developed controller is robust and of excellent control performance.     

执行器约束下基于数据驱动的参数化前馈控制器设计

针对执行器约束下非重复性点到点运动的轨迹跟踪问题, 提出了一种在执行器约束下基于数据驱动的参数化输入整形滤波器和前馈控制器优化设计算法. 首先对输入整形滤波器以及前馈控制器进行参数化, 然后在目标函数中加入控制信号变化量与控制信号能量的约束, 再采用基于数据驱动的迭代寻优算法得到最优参数, 在该参数下可以实现满足执行器约束条件下的运动控制系统轨迹最优跟踪性能. 并且由于采用了前馈参数化设计方法, 在点到点轨迹发生变化时所提出算法依然能够保持良好的轨迹跟踪性能. 仿真与实验结果表明在执行器约束下所提出算法能够实现最优点到点轨迹跟踪性能, 并且对非重复性点到点轨迹跟踪具有一定的鲁棒性.     

A trivial and efficient learning method for motion and force control

The feedback produced by the linear controller of a manipulator executing a trajectory corresponds approximately to the inverse dynamics necessary to drive this trajectory. When a single movement is repeated, the feedback measured in one run can therefore be used as feedforward for the next runs. The learning position–force controller introduced in this paper is based on this idea and a parallel control of force and position. Experiments on 2- and 3-degree-of-freedom parallel manipulators show the simplicity of its implementation and its efficiency for gradually improving trajectory control in repeated movements. The control is robust to high level of noise and the performance is superior than with a parametric controller based on the rigid-body dynamic model. Simulations suggest that these properties also hold when the force is controlled simultaneously to the position.     

两轮自平衡机器人控制系统的设计

针对自行设计的两轮自平衡机器人Opyanbot建立了动力学模型,应用最优控制和两轮差动等控制方法设计了控制器,提出了针对两轮自平衡机器人平衡和行进的新策略。为了提高两轮自平衡机器人的控制效果,利用基于DSP数字电路的全数字智能伺服驱动单元IPM100分别精确控制左右轮电机,并利用上位机实时控制机器人的运动状态,提高了控制精度、可靠度和集成度,得到了很好的控制效果。     

Distributed Secondary Control and Optimal Power Sharing in Microgrids

We address the control problem of microgrids and present a fully distributed control system which consists of primary controller, secondary controller, and optimal active power sharing controller. Different from the existing control structure in microgrids, all these controllers are implemented as local controllers at each distributed generator. Thus, the requirement for a central controller is obviated. The performance analysis of the proposed control systems is provided, and the finite-time convergence properties for distributed secondary frequency and voltage controllers are achieved. Moreover, the distributed control system possesses the optimal active power sharing property. In the end, a microgrid test system is investigated to validate the effectiveness of the proposed control strategies.      

基于初次控制信号提取的迭代学习控制方法

在同一迭代学习控制(Iterative learning control, ILC)系统中,选取一个合适的初次迭代控制信号相对于从零开始学习达到目标跟踪精度的迭代次数更少.本文针对线性系统研究从历次轨迹跟踪控制信息中通过期望轨迹匹配提取初次迭代控制信号的方法.首先提出了一种轨迹基元优化匹配算法,在满足一定相似度的情况下,通过轨迹分割、平移与旋转变换,在轨迹基元库中寻找与当前期望轨迹叠合的轨迹基元组合轨迹;进而,依据线性叠加原理和轨迹叠合的平移矢量与旋转变换矩阵,获取与期望轨迹叠合的轨迹基元控制信号;在此基础上,通过轨迹基元控制信号串联组合和时间尺度变换,提取出当前期望轨迹的初次迭代控制信号.对于初次迭代控制信号在拼接处由边界条件差异引起的干扰,给出了一种H∞反馈辅助ILC方法.最后,在XYZ三轴运动平台实现所提算法,实验结果表明本文所提方法的有效性.     

基于模糊控制的嵌入式智能轮椅控制研究

设计了一种新的智能轮椅,该轮椅的控制器应用了嵌入式技术和模糊控制技术,运用了先进的传感设备,使之能够感知环境信息,具有实时避障功能.时智能轮椅的避障过程进行了仿真,得到比较好的控制效果,并证明用模糊控制策略实现实时避障功能的可行性.     

基于SPCE061A的智能轮椅语音控制系统

应用语音识别技术实现了普通轮椅运动的语音控制系统,介绍了该系统的硬件和软件设计,通过语音识别和轮椅电机的驱动模块实现了轮椅的前进、后退、左拐、右拐、停止、加速、减速运动,根据运动要求通过语音实现轮椅的变速运动。基于SPCE061A的语音控制系统结构简单,性价比高,易于功能扩展和移植。