Acrobot动态伺服控制及其对称虚约束方法研究

研究了Acrobot这一垂直平面欠驱动机械臂的动态伺服控制问题. 该问题期望驱动Acrobot到达构形空间中任意目标位置. 由于Acrobot不能稳定在除平衡点外的位置, 因此考虑将系统镇定到经过目标点的周期轨道上. 利用虚约束来描述这样的轨道, 进而给出了在所选虚约束作用下系统的零动态和积分曲线. 接着设计了级联形式的控制器, 内环控制器基于改进的反馈线性化方法, 引入了一个使内环呈现二阶系统特性的虚拟输入, 在该虚拟输入的基础上, 设计了基于Lyapunov稳定性理论的外环控制器. 最后通过数字仿真证明所提出的方法合理有效, 并且获得比基于能量的动态伺服方法更优的结果.     

有时延和数据包丢失的网络控制系统控制器设计

在同时考虑网络诱导时延和数据包丢失的基础上,研究了动态输出反馈网络控制系统指数稳定性和控制器设计问题.基于一定的数据包丢失率和不大于一个采样周期的时延,将系统建模为结构事件率约束的异步动态系统.利用线性矩阵不等式方法推导出网络接通率约束的系统指数稳定的充要条件,给出了确保系统稳定的控制器设计方法.Matlab数值算例说明了研究结果是有效可行的.     

带非同位干扰执行动态有限维系统的输出追踪

本文考虑了边界带有非同位干扰的波动方程和常微分方程串联系统的性能输出追踪问题. 边界带有非同位干扰的波动方程可以看作常微分方程控制系统的执行动态. 通过利用轨道规划方法将非同位干扰变换到控制通道, 于是克服了非同位干扰带来的困难. 与现有Backstepping方法不同, 文章利用动态补偿法给出了一个新的状态反馈控制器, 使得控制器设计以及所设计的控制器本身更加简单, 证明了闭环系统解的一致有界性与性能输出的指数追踪. 数值模拟表明, 所给的方法是非常有效的     

被动变采样周期网络控制系统的H∞控制器设计

本文研究了具有被动变采样周期网络控制系统的H∞控制器设计问题。提出了基于采样周期切换的方法（采样周期在有限集合内切换），并利用该方法将具有时变采样周期及时延的网络控制系统建模为切换系统。在此基础上，通过求解满足一组线性矩阵不等式约束的多目标优化问题，研究了网络控制系统的H∞控制器设计方法。仿真结果验证了基于采样周期切换的H∞控制器设计方法的有效性。     

具有时变采样周期的网络控制系统的H∞控制

研究了具有时变采样周期的网络控制系统的H∞鲁棒控制器设计问题．提出了基于变采样周期的切换方法（采样周期在有限集合内切换），并利用该方法将存在时变采样周期、长时延以及丢包的网络控制系统建模为切换系统．在此基础上，通过把一个非凸的可行性问题转化为受线性矩阵不等式约束的多目标优化问题，研究了网络控制系统的H∞控制器设计方法．仿真结果验证了基于采样周期切换的H∞控制器设计方法的有效性．     

基于非线性映射的约束系统自适应反推控制

针对基于障碍Lyapunov函数的非线性约束系统反推控制中, 控制器结构复杂、约束量初值选取区间小、会引入额外参数等问题, 提出了一种新的基于非线性映射的自适应反推控制方案. 该方法扩大约束量的初值选取区间为整个约束区间, 增加了系统初值选取和控制器设计的便易性. 约束量被映射至实数空间中, 因此映射后的新系统可以直接应用反推法设计控制器, 简化了控制器结构且不会引入额外参数. 证明了映射前后系统具有一致的收敛性, 保证闭环系统所有信号一致有界, 并且跟踪误差渐近收敛于零. 仿真结果进一步验证了本文方法的有效性.     

半潜式平台动力定位系统优化控制器设计

基于滚动优化机制,设计了随机波上的非线性半潜式平台动力定位系统控制器;基于最优预测机制,将每个控制周期内的半潜式平台动力定位系统控制器设计问题转化为一个带约束的非线性优化问题求解;基于系统演化方程的迭代公式,消去目标函数中状态变量,获得非线性优化问题的非线性约束表达式;给出示例说明了该控制器设计过程,仿真验证了该控制策略和控制器的有效性。     

控制输入受限的拦截卫星轨道鲁棒H2/H∞控制

针对拦截卫星在执行轨道拦截任务的过程中存在不确定参数和不同类型外界干扰的轨道控制问题,研究了基于鲁棒H2/H∞稳定的控制器设计方法.首先,考虑参数不确定性、外界干扰、系统的H2/H∞性能和有限时间性能、控制输入限幅和极点配置,建立了相对运动轨道模型和相应的约束条件,并由此提出了控制器设计目标.然后采用线性不等式技术提出并证明了控制器存在的充分条件,并将控制器的设计转化为一个凸优化问题进行求解.仿真结果表明,设计的控制器能够使系统稳定并满足各项约束,且对系统不确定性具有较好的鲁棒性以及对外界干扰有一定的抑制作用.     

基于观测器的一类连续非线性系统的采样控制

首先使用反演方法分别设计了系统的连续时间状态反馈控制器、连续时间观测器和基于连续时间观测器的连续时间控制器. 接下来, 利用零阶保持法对连续时间状态反馈控制器进行离散化, 获得了状态反馈采样控制器; 利用零阶保持法对基于连续时间观测器 的连续时间控制器离散化, 获得了基于连续时间观测器的采样控制器; 利用Euler法对连续时间观测器离散化, 同时利用零阶保持法对控制器离散化, 从而获得了采样观测器和基于采样观测器的采样控制器. 本文论证了上述状态反馈采样控制器和基于连续时间观测器的采样控制器可以保证闭环系统渐近稳定, 而基于采样观测器的采样控制器可以保证被控对象的状态是有界的, 其最终边界依赖于设计参数与采样周期. 最后, 通过选择适当的采样周期, 完成了闭环采样控制系统的设计. 一个船舶航向控制的例子表明应用本文 所提方法设计出的三种采样控制器具有良好的控制效果.     

基于性能指标约束的一类输入死区非线性系统最优控制

针对一类考虑指定性能和带有输入死区约束的严格反馈非线性系统,本文提出了一种自适应模糊最优控制方法.采用模糊逻辑系统逼近系统的未知非线性函数及代价函数,利用backstepping方法及命令滤波技术,设计前馈控制器.针对仿射形式的误差系统,结合自适应动态规划技术,设计最优反馈控制器.采用指定性能控制方法,将系统跟踪误差约束在指定范围内.利用死区斜率信息解决具有死区输入的非线性系统的控制问题.基于Lyapunov稳定性理论,证明闭环系统内所有信号是一致最终有界的.最后仿真结果验证了本文方法的可行性和有效性.     

Periodic Motion Planning and Control for Double Rotary Pendulum via Virtual Holonomic Constraints

Periodic motion planning for an under-actuated system is rather difficult due to differential dynamic constraints imposed by passive dynamics, and it becomes more difficult for a system with higher underactuation degree, that is with a higher difference between the number of degrees of freedom and the number of independent control inputs. However, from another point of view, these constraints also mean some relation between state variables and could be used in the motion planning.We consider a double rotary pendulum, which has an underactuation degree 2. A novel periodic motion planning is presented based on an optimization search. A necessary condition for existence of the whole periodic trajectory is given because of the higher underactuation degree of the system. Moreover this condition is given to make virtual holonomic constraint (VHC) based control design feasible. Therefore, an initial guess for the optimization of planning a feasible periodic motion is based on this necessary condition. Then, VHCs are used for the system transformation and transverse linearization is used to design a static state feedback controller with periodic matrix function gain. The controller gain is found through another optimization procedure. The effectiveness of initial guess and performance of the closed-loop system are illustrated through numerical simulations.      

The Spring Loaded Inverted Pendulum as the Hybrid Zero Dynamics of an Asymmetric Hopper

A hybrid controller that induces provably stable running gaits on an asymmetric spring loaded inverted pendulum (ASLIP) is developed. The controller acts on two levels. On the first level, continuous within-stride control asymptotically imposes a (virtual) holonomic constraint corresponding to a desired torso posture, and creates an invariant surface on which the two-degree-of-freedom restriction dynamics of the closed-loop system (i.e., the hybrid zero dynamics) is diffeomorphic to the center-of-mass dynamics of a spring loaded inverted pendulum (SLIP). On the second level, event-based control stabilizes the closed-loop hybrid system along a periodic orbit of the SLIP dynamics. The controller's performance is discussed through comparison with a second control law that creates a one-degree-of-freedom non-compliant hybrid zero dynamics. Both controllers induce identical steady-state behaviors (i.e., periodic solutions). Under transient conditions, however, the controller inducing a compliant hybrid zero dynamics based on the SLIP accommodates significantly larger disturbances, with less actuator effort, and without violation of the unilateral ground force constraints.     

A New Nonlinear Controller for Trajectory Tracking of the Longitudinal Dynamics of a Small Scale Helicopter

A nonlinear control scheme is proposed for the trajectory tracking problem of a small scale helicopter’s longitudinal dynamics. The control scheme is based on a control design procedure that constructs static feedback regulators for nonlinear systems which are linearizable by dynamic feedback. Besides, the flatness characteristics of the helicopter’s longitudinal dynamics are used to design the desired trajectory. The controller proposed is based on the longitudinal model of the small scale helicopter including the main rotor and stabilizer bar dynamics. Sufficient conditions are given to guarantee asymptotic convergence to zero of the tracking error and to keep the main rotor thrust always negative assuming that all the helicopter’s parameters are known and that all helicopter’s states are measured. Numerical simulations are given to show the performance of the controller in the presence of the main rotor and stabilizer bar dynamics.     

Robust backstepping output tracking control for SISO uncertain nonlinear systems with unknown virtual control coefficients

The output tracking controller design problem is dealt with for a class of nonlinear strict-feedback form systems in the presence of nonlinear uncertainties, external disturbance, unmodelled dynamics and unknown time-varying virtual control coefficients. A new method based on signal compensation is proposed to design a linear time-invariant robust controller, which consists of a nominal controller and a robust compensator. It is shown that the closed-loop control system with a controller designed by the proposed method has robust asymptotical practical tracking property for any bounded initial conditions and robust tracking transient property if all initial states are zero.     

An Adaptive Controller Dominant-Type Hybrid Adaptive and Learning Controller for Trajectory Tracking of Robot Manipulators

This paper proposes a new hybrid adaptive and learning control method based on combining model-based adaptive control, repetitive learning control (RLC) and proportional–derivative control to consider the periodic trajectory tracking problem of robot manipulators. The aim of this study is to obtain a high-accuracy trajectory tracking controller by developing a simpler adaptive dominant-type hybrid controller by using only one vector for estimation of the unknown dynamical parameters in the control law. The RLC input is adopted using the original learning control law, adding a forgetting factor to achieve the convergence of the learning control input to zero. We will improve and prove that the adaptive dominant-type controller could be applied for tracking a periodic desired trajectory in which adaptive control input increases and becomes dominant of the control input, whereas the other control inputs decrease close to zero. The domination of the adaptive control input gives the advantage that the proposed controller could adjust the feed-forward control input immediately and it does not spend much time relearning the learning control input when the periodic desired trajectory is switched over from the first trajectory to another trajectory. We utilize the Lyapunovlike method to prove the stability of the proposed controller and computer simulation results to validate the effectiveness of the proposed controller in achieving the accurate tracking to the periodic desired trajectory.     

受限机器人神经形态的变结构位置/力控制

本文基于Ｊｅａｎ和Ｆｕ（１９９３）建立的受限机器人模型的降型阶形式，利用变结构系统理论，设计了具有未知动态的受限机器人轨道／力追踪控制，提出的学习方法仅仅利用了机器人动态模型的一般结构，不需要其精确信息，计算迅速，易于实现，仿真结果验证了提出的方法的有效性。     

Predictor‐based repetitive learning control for a class of remote control nonlinear systems

In this paper, a repetitive learning control (RLC) approach is proposed for a class of remote control nonlinear systems satisfying the global Lipschitz condition. The proposed approach is to deal with the remote tracking control problem when the environment is periodic or repeatable over infinite time domain. Since there exist time delays in the two transmission channels: from the controller to the actuator and from the sensor to the controller, tracking a desired trajectory through a remote controller is not an easy task. In order to solve the problem caused by time delays, a predictor is designed on the controller side to predict the future state of the nonlinear system based on the delayed measurements from the sensor. The convergence of the estimation error of the predictor is ensured. The gain design of the predictor applies linear matrix inequality (LMI) techniques developed by Lyapunov Kravoskii method for time delay systems. The RLC law is constructed based on the feedback error from the predicted state. The overall tracking error tends to zero asymptotically over iterations. The proof of the stability is based on a constructed Lyapunov function related to the Lyapunov Kravoskii functional used for the proof of the predictor's convergence. By well incorporating the predictor and the RLC controller, the system state tracks the desired trajectory independent of the influence of time delays. A numerical simulation example is shown to verify the effectiveness of the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd.     

The bio-inspired model based hybrid sliding-mode tracking control for unmanned underwater vehicles

In this paper a novel hybrid control strategy is developed for trajectory tracking control of unmanned underwater vehicle (UUV). The proposed hybrid control strategy consists of two subsystems: a virtual velocity controller and a sliding-mode controller. The tracking errors are shown to asymptotically converge to zero by Lyapunov stability theory using the new approach, whereas in the traditional backstepping method, speed jump occurs if the tracking error changes suddenly. The biologically inspired model is designed to smooth the virtual velocity controller output, avoid speed jumps of underwater vehicles and satisfy the thruster control constraint. The effectiveness and efficiency of the proposed control strategy are demonstrated through simulations and comparison studies.     

Distributed adaptive output consensus control of second-order systems containing unknown non-linear control gains

In this paper, we address the output consensus problem of tracking a desired trajectory for a group of second-order agents on a directed graph with a fixed topology. Each agent is modelled by a second-order non-linear system with unknown non-linear dynamics and unknown non-linear control gains. Only a subset of the agents is given access to the desired trajectory information directly. A distributed adaptive consensus protocol driving all agents to track the desired trajectory is presented using the backstepping technique and approximation technique of Fourier series (FSs). The FS structure is taken not only for tracking the non-linear dynamics but also the unknown portion in the controller design procedure, which can avoid virtual controllers containing the uncertain terms. Stability analysis and parameter convergence of the proposed algorithm are conducted based on the Lyapunov theory and the algebraic graph theory. It is also demonstrated that arbitrary small tracking errors can be achieved by appropriately choosing design parameters. Though the proposed work is applicable for second-order non-linear systems containing unknown non-linear control gains, the proposed controller design can be easily extended to higher-order non-linear systems containing unknown non-linear control gains. Simulation results show the effectiveness of the proposed schemes.