Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems

A filtered adaptive constrained sampled-data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed-loop system with the sampled-data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled-data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.     

Controlling aliased dynamics in motion systems? An identification for sampled-data control approach

Sampled-data control systems occasionally exhibit aliased resonance phenomena within the control bandwidth. The aim of this paper is to investigate the aspect of these aliased dynamics with application to a high performance industrial nano-positioning machine. This necessitates a full sampled-data control design approach, since these aliased dynamics endanger both the at-sample performance and the intersample behaviour. The proposed framework comprises both system identification and sampled-data control. In particular, the sampled-data control objective necessitates models that encompass the intersample behaviour, i.e., ideally continuous time models. Application of the proposed approach on an industrial wafer stage system provides a thorough insight and new control design guidelines for controlling aliased dynamics.     

Sampled-data based average consensus with measurement noises: convergence analysis and uncertainty principle

In this paper, sampled-data based average-consensus control is considered for networks consisting of continuous-time first-order integrator agents in a noisy distributed communication environment. The impact of the sampling size and the number of network nodes on the system performances is analyzed. The control input of each agent can only use information measured at the sampling instants from its neighborhood rather than the complete continuous process, and the measurements of its neighbors’ states are corrupted by random noises. By probability limit theory and the property of graph Laplacian matrix, it is shown that for a connected network, the static mean square error between the individual state and the average of the initial states of all agents can be made arbitrarily small, provided the sampling size is sufficiently small. Furthermore, by properly choosing the consensus gains, almost sure consensus can be achieved. It is worth pointing out that an uncertainty principle of Gaussian networks is obtained, which implies that in the case of white Gaussian noises, no matter what the sampling size is, the product of the steady-state and transient performance indices is always equal to or larger than a constant depending on the noise intensity, network topology and the number of network nodes.     

时滞系统方法的网络控制系统的研究

针对普遍存在的采样器和零阶保持器异步这一现象,研究了该类网络控制系统的状态反馈控制问题。首先,以事件驱动的零阶保持器的更新时刻为时间标识,并考虑到网络的诱导时延和数据丢包,建立网络控制系统的采样闭环模型,并转化为状态中连缀着两个时滞变量的时滞系统。然后,利用相应的时滞系统方法,对闭环网络控制系统进行了稳定性分析和控制器综合。最后,通过仿真实例验证了所得结果的正确性。     

一类不确定采样系统的鲁棒D控制研究

本文对一类范数有界不确定线性采样系统,提出了存在状态反馈控制律,使得闭环系统的所有极点均位于一给定的圆盘中且具有最优鲁棒H∞性能的一个充分条件。结合控制律反馈增益参数极小化的要求,建立一个具有线性矩阵不等式约束的凸优化问题,通过该问题的解决,可以构造一个具有较小反馈增益参数和给定要求的控制律,算例结果进一步表明,该控制器具有更好的扰动抑制性能。     

输出信号量化的双率采样系统参数辨识方法

针对双率采样和信号量化(signal quantization)[BFQB]的控制系统,采用随机重复性试验测量信息,提出基于辅助模型的双率采样量化控制系统辨识方法.分析了在随机重复试验和放松估计误差方差条件下,双率采样量化系统的模型特征并给出了分两步辨识的策略,推导了进行参数辨识所满足的持续激励条件,并给出了基于辅助模型的双率采样量化控制系统量化辨识递推算法;接着分析了所给出量化辨识递推算法的收敛性,得到了双率采样量化系统参数估计误差上界的计算式,最后数字仿真验证了该算法及结论的有效性.     

线性切换系统的采样数据输出调节问题

本文基于采样控制,解决了线性切换系统的输出调节问题.首先考虑了外部输入信号是常数的情况,给出了采样周期与平均驻留时间的关系.通过构造一类Lyapunov-Krasovskii泛函,使得闭环系统内部稳定且调节输出趋于零.其次考虑了外部输入信号是导数有界且时变的情况,给出了采样数据状态反馈控制器,并依据采样周期和平均驻留时间关系给出的切换条件得到了切换系统实用输出调节问题可解的充分条件.最后通过两个数值例子验证了方法的有效性.     

Data-driven dual-rate cascade control and application to pitch angle control of UAV

A data-driven design method for a cascade control system is proposed. The cascade control system consists of inner and outer loops, where the control interval of the outer loop is an integer multiple of the inner loop; hence, the system is a dual-rate system. In the proposed method, controllers in the inner and outer loops are designed based on one-shot data. In such a dual-rate cascade system, since the controllers are designed using different data-rate signals, the lifting technique is applied to align the dual-rate data. To show its effectiveness, the proposed method is compared with a conventional single-rate cascade control method, and numerical simulations and experiments are presented to examine servo and regulation performance.     

Fault-tolerant control for a class of nonlinear sampled-data systems via a Euler approximate observer

In this paper, a fault-tolerant control (FTC) scheme is developed for a class of nonlinear sampled-data systems. First, a Euler approximate discrete model is used to describe the plant under the sampling. Under this model, an observer-based fault estimation method is proposed. To guarantee the accuracy of both the state and fault estimation values, the conditions to make the approximate model consistent with the exact model are presented. Then, an active fault-tolerant controller, which has a constraint condition for the sampling time, is designed to make the faulty system stable. Finally, an inverted pendulum is used to show the efficiency of the proposed method.