一类不确定切换模糊时滞系统的保性能控制

针对一类存在时滞的不确定切换模糊系统,研究系统的保性能控制问题.利用平行分布补偿算法(PDC)给出保性能控制器的设计方法,利用单Lyapunov函数方法和多Lyapunov函数方法,给出不确定切换模糊时滞系统保性能控制器存在的充分条件和切换律设计.使得闭环系统对所有允许的不确定,在所设计的控制器和切换律下实现保性能控制.仿真结果表明方法的有效性.     

一类时滞广义非线性系统H_∞可靠跟踪控制

讨论一类Lipschitz时滞非线性广义系统的H∞可靠跟踪控制问题.分别给出了执行器失效和传感器失效两种模型下可靠控制器存在的充分条件,使得闭环系统正则无脉冲并且指数稳定,同时系统输出跟踪预先给定的可测参考模型的输出,且满足H∞性能指标,并利用线性矩阵不等式技巧给出了可靠控制器的设计方法.最后给出了一个数值例子,说明了本文所给出方法的有效性.     

具有积分二次约束属性的网络控制系统H∞容错控制

针对一类具有积分二次约束属性的时滞网络控制系统,研究了系统在不等间隔采样下的H_∞容错控制.首先,分析并处理了网络控制系统中时滞与不等间隔采样之间的关系.以此为基础,建立了不等间隔采样下的不确定时滞网络控制系统的切换模型.通过构造Lyapunov函数,运用H_∞控制方法,以及设计具有积分二次约束属性的控制器,获得了基于LMI描述的系统时滞依赖稳定性判据.然后,建立了网络控制系统的传感器故障模型和传感器故障下的网络控制系统数学模型.通过把结论运用到传感器出现故障的网络控制系统,得到了系统在H_∞容错控制下的稳定性判据.最后,通过与其他文献介绍的方法进行比较的一个例子,说明了该方法的有效性.     

双率采样系统的基于观测器的网络化H∞控制

研究一类带有网络传输时滞和丢包的双率采样系统的网络化H∞控制问题. 假设对象状态变量被分成两个分向量, 同一分向量的状态变量由同一类传感器以相同周期采样, 且两类传感器的采样频率不同. 采样后的分向量分别通过非理想网络传输到控制器端. 考虑到双率采样、网络传输时滞和丢包现象, 引入同步观测器来估计对象状态并设计基于估计状态的控制器来镇定双率采样系统. 基于这个思路, 将双率采样的网络化控制系统建模为带有两个时变时滞的连续系统. 利用Lyapunov-Krasovskii泛函方法, 以矩阵不等式形式给出该系统的稳定性判据和控制器设计方法. 最后, 通过数值例子验证所提方法的有效性.     

基于动态模型库的多模型切换控制

针对含有有界扰动和模型参数跳变的离散时间系统,提出基于动态模型库的多模型切换控制方法.在模型参数范围未知情况下,利用在线学习的多模型自适应控制算法自动建立多模型,并对模型库中的子模型进行优化.采用具有积分特性的指标函数作为切换准则.在每一采样时刻根据其最小值来选择与实际系统最接近的模型,并将基于此模型的控制器切换为当前控制器.文中证明了该算法能够保证闭环系统的稳定性和跟踪误差的渐近收敛性.计算机仿真结果表明该算法的有效性.     

时滞纳米运动系统的多速率采样预测自抗扰控制

电容型纳米位置传感器在纳米伺服系统中得到了越来越多的应用.这类超高精度模拟传感器用于反馈信号时因较长的模数转换时间将带来明显的测量时滞.而这类数字纳米伺服系统也因硬件使其采样频率在处理高频干扰时受到带宽限制.本文针对测量时滞和高频干扰的挑战,提出一种带采样预测功能的多速率自抗扰控制器设计方法.首先建立了电容式位移传感器的纳米运动平台带有时滞的动力学模型.其次,基于该模型设计多率采样预测线性扩张状态观测器和多率反馈控制器.通过设计预测型观测器,适当选取观测器增益,消除时滞对状态观测的影响.另外,将输出预估器加入预测扩张状态观测器中重构采样点间系统输出值,从而在时滞系统中更好地估计和消除高频干扰,并给出了系统的稳定性分析.最后通过压电驱动纳米运动平台的实时控制实验验证本文提出控制器的有效性.     

切换非线性系统的分布式模型预测控制

针对一类具有预先指定切换序列的切换非线性系统,研究了具有通信信道干扰和时滞测量的分布式模型预测控制问题.在每个子系统都存在镇定控制器的假设下,利用基于Lyapunov函数的模型预测控制器设计了分布式模型预测控制器,并给出了闭环切换非线性系统最终有界的充分条件.最后,通过仿真结果表明了分布式模型预测控制策略的有效性.     

一类受扰旋转单摆系统的建模与跟踪控制设计

本文考虑一类受扰旋转单摆系统的建模与跟踪控制问题. 首先, 利用动静法和相对运动原理建立受扰情形下空间旋转摆系统的动力学模型. 然后, 分别以实际跟踪和渐近跟踪为控制目标, 给出相应的控制设计方法. 具体地,利用向量式的反推控制设计方法与不确定性动态补偿机制, 给出自适应实际跟踪控制器, 保证闭环系统所有状态都有界且在有限时间内系统输出到达并保持在参考信号给定的邻域内. 利用反推设计方法, 并结合扰动的学习、切换补偿机制设计自适应切换渐近跟踪控制器, 通过在线调节控制器参数, 保证闭环系统所有状态都有界且系统输出渐近跟踪到给定的参考信号. 最后, 仿真实验验证所提理论结果的有效性. 值得指出的是, 与相关文献相比, 本文所给出的控制设计方法允许系统同时含有未知参数和扰动, 并且扰动不必有已知上界, 因而具有更强的抑制不确定性的能力.     

基于不同加权因子的随机多模型自适应控制

针对一类噪声方差未知的随机系统,基于不同加权因子设计多个参数辨识器辨识模型参数,在此基础上,构成多模型自适应控制器.在每个采样时刻基于指标切换函数选择最佳辨识模型.并将基于此最佳模型设计的控制器切换为当前控制器.同时,证明了多个模型控制器之间相互切换时整个闭环系统是全局收敛的.仿真结果表明,同单一自适应模型控制器相比,这种基于多个不同加权因子的多模型自适应控制器在模型参数发生跳变时可很好地改善被控对象的控制品质.     

不确定Delta算子系统的滑模软切换控制

针对一类带有内部参数摄动和外部扰动的快速采样控制系统,基于sigmoid函数提出了一种Delta算子S-变速趋近律方法,并设计了不确定Delta算子系统的滑模软切换控制器。基于Delta算子采样原理,将连续时间系统和离散时间系统的软切换控制器设计统一到Delta算子系统。基于Delta算子S-变速趋近律方法设计的闭环快速采样滑模软切换控制器能够在限制时刻内到达切换面,削弱了系统颤振。从仿真实例可以看出,该滑模软切换控制器的稳定性和平稳性优于传统指数趋近律情形,整个动态过程具有良好的完全鲁棒性。     

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.     

State unilateral tracking control of positive switched systems via designing a switching law

This paper focuses on the model reference state unilateral tracking control problem of positive switched systems. The state unilateral tracking means that the state always keeps in the same direction of the reference objective, either above or below. This feature makes unilateral tracking play a role of avoiding the overshoot. Via the dual design of both the controller and the switching signal, the state unilateral tracking control problem with L₁-gain performance for positive switched systems is solved through adopting multiple linear co-positive Lyapunov functions technique. The design method is applicable to the case that the unilateral tracking control problem is unsolvable for any subsystem of a positive switched system. Moreover, two techniques are presented in order to deal with the state unilateral tracking problem. Finally, a practical example demonstrates the validity of the presented result.     

Trajectory tracking control of bimodal piecewise affine systems

This paper deals with a trajectory tracking problem for a class of bimodal piecewise affine systems, which is inherently difficult because of the discontinuous changes of their vector fields. First, we introduce an error variable and an error system as a generalization of the tracking error and its system. As an error variable, a function switched by the mode of a piecewise affine system is adopted to overcome the inherent difficulty in trajectory tracking control of piecewise affine systems. Next, we design a tracking controller which stabilizes the error system using a Lyapunov-like function, which can be applied to systems including state jumps. Furthermore, the feasibility condition of tracking for SISO piecewise linear systems is simplified. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.     

An iterative learning controller with reduced sampling rate for plants with variations of initial states

In this paper a discrete-time iterative learning controller for single input single output systems is presented. The iterative learning controller works with a reduced sampling rate that ensures the reduction of an appropriate norm of the error trajectory from cycle to cycle and can cope with initial state error. Initial state error occurs when the initial state of the system is different from the initial state that is implicitly given by the reference trajectory. If the initial state changes for every learning iteration, then the controller cannot achieve ideal tracking but the error trajectory is bounded. Using two different sample times together with a potentially time variant learning gain improves the controller performance for dealing with initial state error. Simulation examples are presented to show the results of the proposed iterative learning controller with reduced sampling rate.     

An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot

We present an iterative linear quadratic regulator(ILQR) method for trajectory tracking control of a wheeled mobile robot system.The proposed scheme involves a kinematic model linearization technique,a global trajectory generation algorithm,and trajectory tracking controller design.A lattice planner,which searches over a 3D(x,y,θ) configuration space,is adopted to generate the global trajectory.The ILQR method is used to design a local trajectory tracking controller.The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot.The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator(LQR) method.According to the experiments,the new controller improves the control sequences(v,ω) iteratively and produces slightly better results.Specifically,two trajectories,’S’ and ’8’ courses,are followed with sufficient accuracy using the proposed controller.     

移动机器人轨迹跟踪快速终端滑模自抗扰控制

针对移动机器人动力学模型难以精确建立、运动过程中各种干扰对高精度轨迹跟踪造成偏航等问题,构造出一种快速终端滑模自抗扰控制器,实现了高速高精度轨迹跟踪控制目标。首先建立非完整移动机器人的干扰控制模型;然后运用扩张状态观测器实时监测系统未建模动态与各种干扰;同时将扩张状态量和系统反馈量作为快速终端滑模算法的系统变量;最后设计出一种快速终端滑模控制律,代替传统自抗扰算法中的非线性控制律,从而实现位姿的快速精确跟踪。该算法既克服了非线性误差控制律中参数繁杂不易整定的缺陷,又增强了系统鲁棒性和轨迹跟踪的动态品质。对比仿真实验验证了该控制算法的有效性和先进性。     

基于啤酒发酵过程的时变轨迹输出反馈鲁棒模糊预测控制

考虑到实际生产中状态不易测量和设定值变化的情况以及系统本身的非线性特性,针对啤酒发酵过程温度控制系统提出了一种时变轨迹下输出反馈鲁棒模糊预测控制方法。在啤酒发酵罐温度系统的机理模型的基础上,建立包括不确定性和未知干扰的状态空间模型;通过设计模糊集,建立为具有加权系数的T-S模糊状态空间模型;并在状态变量的中引入输出跟踪误差,建立新型多自由度状态空间模型;并运用鲁棒模型预测控制方法优化参数不确定性问题,结合李雅普诺夫稳定性理论推导出线性矩阵不等式形式的稳定性条件,通过求解线性矩阵不等式中参数来计算对应子模型控制律,并对所设计的输出反馈控制器给定权值。通过仿真结果验证了提出方法的有效性和可行性。     

有源电力滤波器切换跟踪与优化控制

为了提高有源电力滤波器的动态性能, 基于切换系统理论研究其电流跟踪控制问题. 首先, 建立系统的切换动态模型, 根据切换系统理论和空间电压矢量法证明二次稳定性, 并设计相应的切换控制序列. 考虑到控制器的数字化实现, 建立系统的离散切换系统模型, 提出在采样周期内使系统性能最优的切换控制策略. 仿真结果表明, 该控制策略能实现对指令电流的精确跟踪, 降低功率器件的开关频率, 从而有效地提高系统的动态性能.

     

Robust switched predictive control for multi-phase batch processes with uncertainties and unknown disturbances

A robust switched predictive control method is designed to deal with the multi-phase batch processes with the inevitable uncertainties, time-varying delay and unknown disturbances. Firstly, the output tracking errors are augmented into the state variables and then the improved robust switched predictive control law is established using the new augmented state variables. To this end, the novel switched system is built to represent the different phases of multi-phase batch processes. Secondly, making full use of the robust predictive control theory, Lyapunov function theory, switched system theory, linear matrix inequality (LMI) theory and mode-dependent average dwell time method, the sufficient conditions in terms of LMI constraints are derived to ensure that the switching system is asymptotically controllable and stable. During the process of derivation, based on the traditional performance indicators, the H-infinite performance index is introduced, so that the system in different phases can still operate stably under the uncertainty and external interference. The average dwell time and the control law gain of each phase are thus calculated by solving these LMI constrains. Ultimately, the simulation results on the injection molding process show that the proposed method can make the controlled system run stably.