Robust preview control for a class of uncertain discrete-time systems with time-varying delay

This paper proposes a concept of robust preview tracking control for uncertain discrete-time systems with time-varying delay. Firstly, a model transformation is employed for an uncertain discrete system with time-varying delay. Then, the auxiliary variables related to the system state and input are introduced to derive an augmented error system that includes future information on the reference signal. This leads to the tracking problem being transformed into a regulator problem. Finally, for the augmented error system, a sufficient condition of asymptotic stability is derived and the preview controller design method is proposed based on the scaled small gain theorem and linear matrix inequality (LMI) technique. The method proposed in this paper not only solves the difficulty problem of applying the difference operator to the time-varying matrices but also simplifies the structure of the augmented error system. The numerical simulation example also illustrates the effectiveness of the results presented in the paper.     

Command filter based adaptive fuzzy bipartite output consensus tracking of nonlinear coopetition multi-agent systems with input saturation

This paper is concerned with the adaptive bipartite output consensus tracking problem of high-order nonlinear coopetition multi-agent systems with input saturation under a signed directed graph. A distributed fuzzy-based command filtered backstepping scheme is proposed, where the unknown nonlinear dynamics are approximated by the fuzzy logic system (FLS). The errors compensation mechanism is constructed to eliminate the errors caused by filters. Under the proposed control scheme, we only need to design one adaptive law for each agent, and it is proved that the bipartite output tracking errors converge into the desired neighborhood and all the closed-loop signals are bounded although the input saturation exists. Two numerical examples are included to verify the effectiveness of given scheme.     

自适应神经元实现的直线永磁同步电机伺服系统的预见前馈补偿

介绍了高精度微进给直线永磁同步电机伺服系统的IP位置控制，提出了对该系统的最优预见前馈补偿，以提高系统的跟踪性能。为了能适应系统参数的变化，采用自适应神经元来实现预见前馈补偿，自适应神经元的输入向量为预见步数，权值为预见前馈系数，权值具有明确的物理意义，而且权的初始值不是随机数，而是系统在额定情况下算出的预见前馈系数，从而加快了神经元的调整速度，提高了系统的跟踪能力，仿真实验结果证明了所提出方案的有效性。     

基于面积误差评价的轨迹跟踪数字式最优预见控制

研究在数字最优预见控制中以面积误差作为评价函数的轨迹跟踪最优预见控制方法。首先 ,分析了轨迹跟踪控制的特点和一些问题 ,依次建立了基于面积误差的轨迹跟踪性能评价函数 ,从而获得轨迹跟踪的最优预见控制算法 ;然后对一个简易工作平台系统的轨迹跟踪问题进行了仿真验证。结果表明基于面积误差评价的最优预见控制方法是能够提高路径控制精度的一种有效方法。     

基于协调误差的目标轨迹预见跟踪控制的研究

针对系统已知的空间目标轨迹，提出了一种基于协调误差的空间目标轨迹最优预见跟踪控制的方法，其核心是将轨迹的协调跟踪误差和轨迹的位置跟踪误差考虑成系统的状态变量，并实施最优反馈控制。仿真分析表明，该轨迹跟踪控制方法能够有效提高系统的轨迹跟踪控制精度。     

An application of sliding horizon control to an electro-hydraulic automotive seat simulator

The paper demonstrates the tracking performance of a sliding horizon feedback/feedforward preview optimal control when applied to a hydraulic motion simulator which has been built to provide a means of replicating the actual ride dynamics of an automobile seat/human system. The design was developed by solving an ordinary differential equation problem instead of a Ricatti equation. Simulation results indicate that the proposed technique has good performance improvement in phase tracking when compared to the classical design methods. It is also found that the controller can be adjusted more easily for robustness due to more turning parameters.     

无人驾驶车辆路径跟踪控制预瞄距离自适应优化

基于道路信息,使用驾驶员预瞄模型产生执行器输入是无人驾驶车辆在路径跟踪中使用的主要方法之一,但对于车速较高与转弯半径小等工况,模型误差会导致较差的驾驶舒适性,车辆甚至失去稳定性。为提高无人驾驶车辆路径的跟踪精度,同时兼顾转向频度和车辆稳定性,提出基于粒子群多目标优化（Particle swarm optimization,PSO）算法的预瞄距离自适应驾驶员模型,并将之应用于路径跟踪控制。首先,基于单点预瞄偏差模型,采用滑模变结构设计转向控制器;其次,以路径跟踪精度、转向频度和车辆稳定性为综合性能指标,设计了PSO优化算法,实现了驾驶员模型预瞄距离的自适应寻优。最后,在搭建的CarSim-Simulink联合仿真平台与台架试验上,对所提出的预瞄距离自适应驾驶员预瞄模型进行了仿真和硬件在环试验验证。结果表明,经优化后的预瞄距离能够适应不同车速和道路曲率,驾驶员预瞄模型能兼顾路径跟踪精度、转向频度和车辆稳定性等需求。预瞄距离自适应驾驶员模型结合道路与车速信息,增大对路况与车况适应性,为无人驾驶车辆路径跟踪控制提供可靠的输入。     

Distributed multiparametric model predictive control design for a quadruple tank process

Distributed control for plant wide control has received attention lately. In this paper, multiparametric quadratic programming based controllers have been developed for a benchmark quadruple tank problem. A centralized control strategy is developed by partitioning its six dimensional vector space based on constraint satisfaction, stability and optimality. Control design is simplified using its decentralized version after a relative gain array analysis of the benchmark. A cooperative game theory based distributed model predictive controller and decentralized proportional integral (PI) controller are also designed for the same system. A decoupling based cooperative distributed multiparametric model predictive controller (mpMPC) is proposed. The controllers are subjected to reference tracking and disturbance rejection and the performance measures are compared. Also, the robustness of cooperative mpMPC to parameter uncertainties is discussed. Distributed design approach is a natural fit for the vector space partitioning based mpMPC design. Simulations results are analyzed and the performance of the five controllers is discussed.     

Bipartite output consensus of heterogeneous linear multi-agent systems by dynamic triggering observer

In this paper, the bipartite output consensus problem of heterogeneous linear multi-agent systems (HL-MASs) is investigated. Compared with related works, both the cooperative interactions and antagonistic interactions between agents exist. First, a novel distributed dynamic triggering observer is designed to recover the leader’s state. In order to avoid verifying the dynamic triggering condition continuously, a monitoring scheme is proposed. Then, the communication cost can be reduced. Next, we solve the bipartite output consensus problem of HL-MASs by both state feedback and output feedback control laws. Moreover, detailed analysis on the dynamic event triggering condition is conducted. It is shown that the lower bound of inter-execution time is larger than zero, so Zeno behaviour is excluded. The choice of parameters involved in the dynamic event triggering condition is also analysed. Finally, examples are given for demonstration.     

轮式移动机器人路径跟踪控制方法研究

针对轮式移动机器人的路径跟踪问题,提出了一种基于动态预瞄的移动机器人路径跟踪控制方法。根据差速轮式移动机器人运动学模型和实时位置信息,建立路径跟踪偏差模型,并采用构建虚拟运动路径的方式设计移动机器人路径跟踪控制方法,结合路径跟踪偏差模型,实时调整移动机器人的运动状态,不断缩小运动过程中的偏差,最终实现路径跟踪。实验结果表明,所设计的移动机器人路径跟踪控制方法能够实现高精度的路径跟踪控制,同时具有良好的可靠性,平稳性。     

Distributed ESO based cooperative tracking control for high-order nonlinear multiagent systems with lumped disturbance and application in multi flight simulators systems

Based on extended state observer, a novel and practical design method is developed to solve the distributed cooperative tracking problem of higher-order nonlinear multiagent systems with lumped disturbance in a fixed communication topology directed graph. The proposed method is designed to guarantee all the follower nodes ultimately and uniformly converge to the leader node with bounded residual errors. The leader node, modeled as a higher-order non-autonomous nonlinear system, acts as a command generator giving commands only to a small portion of the networked follower nodes. Extended state observer is used to estimate the local states and lumped disturbance of each follower node. Moreover, each distributed controller can work independently only requiring the relative states and/or the estimated relative states information between itself and its neighbors. Finally an engineering application of multi flight simulators systems is demonstrated to test and verify the effectiveness of the proposed algorithm.     

基于三坐标测量机的分布式CAIP系统多智能主体知识模型框架的实现

ＤＩＫＦ是基于分布式并行处理智能检测规划集成开发平台中中用于多智能主体协同求解的分布式检测规划知识模型框架。主要论述了ＤＩＫＦ的系统组织原则和组成ＤＩＫＦ的智能主体的内部结构和功能模块，并依据其内部结构说明分布式检测规划的协同求解方法和策略。     

基于期望横摆角速度的视觉导航智能车辆横向控制

针对采用传统位置偏差控制方法的车道保持系统横向控制精度不高以及鲁棒性差等问题,提出一种跟踪期望横摆角速度的车辆横向控制方法。在车辆当前行驶位置和道路预瞄点之间实时规划逼近目标路径的虚拟路径,同时分析当前时刻车辆以无偏差形式沿此虚拟路径行驶时决定车辆行驶位置的横摆角速度及速度之间的关系。结合车辆道路相对位置及车身状态信息,设计期望横摆角速度生成器。基于7自由度非线性车辆动力学模型,设计滑模控制器跟踪期望横摆角速度,使得车辆稳定地跟踪目标路径。根据车道线宽度和边缘点数量统计进行边缘检测,能有效识别模糊车道边缘和抑制噪声,并通过对消失点的检测来有效去除非车道线的干扰。仿真及试验结果表明,与传统的位置偏差控制方法相比,期望横摆角速度法不仅能提高车辆横向控制的精确性且跟随偏差随车辆速度及道路曲率的变化波动范围小,具有很好的鲁棒性和自适应性。     

视觉导航智能车辆横向运动的自适应预瞄控制

车道保持系统中车辆横向运动控制应模拟驾驶员的横向操纵行为,驾驶员根据前方道路曲率及车辆速度适时调节预瞄距离,以获得理想的路径跟踪性能。首先,以车辆二自由度动力学模型及车辆道路几何位置关系为基础,建立车-路横向动力学模型。其次,基于单点预瞄最优曲率模型设计侧向加速度PD跟踪控制器,联立车-路横向动力学模型构建横向控制闭环系统,分析预瞄距离、车速、道路曲率的变化对系统响应的影响。最后,设计模糊控制器对预瞄距离进行模糊选择以提高车辆横向控制精度和减小侧向加速度,采用遗传算法对模糊规则进行优化以使横向控制系统性能达到最优。试验表明,相对固定预瞄控制方法,自适应预瞄减小了车辆侧向加速度,且道路跟踪的方向偏差和距离偏差均得到减小。     

多移动微小型机器人编队控制与协作避碰研究

针对多移动微小型机器人系统的协作避碰和队形保持,给出了一种分布式的编队控制方法。结合移动微小型机器人的运动控制模型,提出了一种路径规划方法,使其在运动中实时避免碰撞。在此基础上利用李雅普诺夫(Lyapunov)法设计了一种编队控制器。在有界误差范围内,该控制器能够保证多机器人的轨迹跟踪和协作避碰。通过将编队控制转化为跟踪整个队形质心的轨迹,降低了控制的复杂度,从而可以较好地应用到计算资源有限的多移动微小型机器人中。通过仿真、分析和对比,对以上控制方法的稳定性和可行性进行了验证,并进行了实际的编队和避碰控制实验。实验结果表明该方法可有效地应用于多移动微小型机器人的协作避碰和编队控制。     

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach.     

基于状态反馈的H∞重复控制逆变技术研究

针对提高逆变器的动态特性和跟踪精度,提出了融合H∞控制、重复控制以及状态反馈控制的PWM电压源型逆变器电压控制策略。该策略先引入了电感电流状态反馈,能有效增加逆变器系统阻尼比,改善系统的动态性能,然后加入了重复控制环节,能提高系统的电压跟踪精度,最后将重复控制器的设计通过解决一个标准H∞问题来实现,减少了反复调节参数的过程,兼顾了系统的稳定性与跟踪精度。仿真结果表明,该策略能保证逆变器系统具有良好的动态特性和高稳态精度,克服了突加负载的"瞬态"电压跌落问题,在加入整流负载后仍能输出高质量的正弦电压波形。     

Relative position finite-time coordinated tracking control of spacecraft formation without velocity measurements

This paper investigates finite-time relative position coordinated tracking problem by output feedback for spacecraft formation flying without velocity measurement. By employing homogeneous system theory, a finite-time relative position coordinated tracking controller by state feedback is firstly developed, where the desired time-varying trajectory given in advance can be tracked by the formation. Then, to address the problem of lack of velocity measurements, a finite-time output feedback controller is proposed by involving a novel filter to recover unknown velocity information in a finite time. Rigorous proof shows that the proposed control law ensures global stability and guarantees the position of spacecraft formation to track a time-varying reference in finite time. Finally, simulation results are presented to illustrate the performance of the proposed controller.     

Performance limitations of networked control systems with quantization and packet dropouts

This paper investigates the problem of optimal tracking performance of networked control systems (NCSs) with quantization and packet-dropouts. The system under consideration is linear time-invariant (LTI), multi-input multi-output (MIMO), where an H₂ norm of error signal between the reference input and the system output is used as the tracking performance index. The impacts of packet-dropouts in the communication channel and the quantized input and output are studied. The goal is to obtain the minimal error in tracking a random signal, by searching through all possible stabilizing two-parameter controllers. It is shown that, the minimum value of tracking error is closely related to the reference input signal direction, the non-minimum phase zeros and unstable poles of the given plant, including the locations and directions. We also demonstrated the quantization error and the packet-dropouts may degrade the tracking performance. A typical example is given to evaluate the theoretical results.     

Robust adaptive cruise control of high speed trains

The cruise control problem of high speed trains in the presence of unknown parameters and external disturbances is considered. In particular a Lyapunov-based robust adaptive controller is presented to achieve asymptotic tracking and disturbance rejection. The system under consideration is nonlinear, MIMO and non-minimum phase. To deal with the limitations arising from the unstable zero-dynamics we do an output redefinition such that the zero-dynamics with respect to new outputs becomes stable. Rigorous stability analyses are presented which establish the boundedness of all the internal states and simultaneously asymptotic stability of the tracking error dynamics. The results are presented for two common configurations of high speed trains, i.e. the DD and PPD designs, based on the multi-body model and are verified by several numerical simulations.