Stability analysis of networked control systems with time-varying sampling periods

In this paper, we present an interval model of networked control systems with time-varying sampling periods and time-varying network-induced delays and discuss the problem of stability of networked control systems using Lyapunov stability theory. A sufficient stability condition is obtained by solving a set of linear matrix inequalities. In the end, the illustrative example demonstrates the correctness and effectiveness of the proposed approach.     

时变采样周期网络控制系统的鲁棒容错控制器设计

研究具有时变采样周期网络控制系统的执行器失效的完整性问题．假设系统任意两个连续采样间隔具有上界,利用输入时延法,将时变采样周期网络控制系统等价转化为连续时变时延网络控制系统．在此基础上,基于时延条件,应用Ｌｙａｐｕｎｏｖ稳定性理论和线性矩阵不等式（ＬＭＩｓ）方法证明了鲁棒容错控制律的存在条件,设计了鲁棒容错控制器,并给出了系统完整性条件下的最大允许时延的估计方法．仿真结果验证了所提方法的可行性和有效性．     

Frequency-domain estimates of the sampling interval in multirate nonlinear systems by time-delay approach

A class of nonlinear hybrid systems consisting of a continuous plant and a multirate sampled-data controller is considered. Applying the time-delay approach, the system is transformed to the system with a time-varying sawtooth delay. Then, the value of the sampling intervals ensuring stability of the closed-loop system is estimated based on the frequency-domain circle-like criterion for systems with time-varying delay. Such a criterion for multirate MIMO systems is established based on the previous result for SISO systems proposed by M.Churilova in 1995. Efficiency and advantages of the method are illustrated by numerical examples. The key advantage of the proposed approach is that it is applicable to multirate systems nonaffine in control. It allows one to use a nonlinear feedback for stabilisation. Particularly, the case of nonsmooth or discontinuous nonlinear systems can be treated.     

Improved data-driven optimal TILC using time-varying input signals

A new improved data-driven optimal TILC (DDOTILC) is proposed for a class of nonlinear discrete-time systems by using time-varying control input signals to enhance control performance. An equivalent dynamical linear presentation is developed in the iteration domain for the repeatable nonlinear system, where the time-varying partial derivatives of the system with respect to the time-varying control inputs reflect the dynamical characters of the plant. Both the time-varying input signals and time-varying partial derivatives over the entire finite time interval are updated in batches, respectively. The proposed approach is a data-driven control scheme and only the boundedness of the partial derivatives is needed for control system design and analysis. Both rigorous mathematical analysis and the simulation results are provide to verify the applicability and effectiveness of the proposed approach further.     

A synthesis of Lyapunov functions for non-linear time-varying control systems

The formulation of a class of Lyapunov functions for time-varying nonlinear control systems which occur in the stability analysis of control systems is considered. A new approach is presented, which is an extension of a generation technique for time-invariant non-linear systems. This approach, which uses by analogy the classical theory of Hamilton, permits stability and transient information to be obtained from system equations with time-varying damping as well as time-varying gain. A second and third-order example is used to illustrate the application of this new result.     

控制方向未知的时变非线性系统鲁棒控制

针对一类具有未知时变控制方向、不确定时变参数以及未知时变有界干扰的严反馈非线性系统,给出一种带有死区修正算法的鲁棒控制方法.在控制系数符号未知的情况下,通过在反步法中引入Nussbaum增益和死区修正技术,得到一种修正的鲁棒反步设计方法.该方法不需要未知时变控制系数的上下界先验知识以及不确定参数和外界干扰的上界信息.算法保证了闭环系统所有信号的有界性,同时使得跟踪误差收敛于零的任意小邻域内.     

未知时变时滞非线性参数化系统自适应迭代学习控制

针对含有未知时变参数和时变时滞的非线性参数化系统,提出了一种新的自适应迭代学习控制方法.该方法将参数分离技术与信号置换思想相结合,可以处理含有时变参数和时滞相关不确定性的非线性系统.设计了一种自适应控制策略,使跟踪误差的平方在一个有限区间上的积分渐近收敛于零.通过构造Lyapunov-Krasovskii型复合能量函数,给出了闭环系统收敛的一个充分条件.给出两个仿真例子验证了控制方法的有效性.     

Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.     

Distributed guaranteed cost control for aperiodic sampled-data networked interconnected systems: a switched system approach

This paper investigates the distributed guaranteed cost control problem for a class of networked interconnected control systems (NICSs) under aperiodic sampling. The NICSs with missing data and time-varying delay are modelled as an aperiodic sampled-data switched system with uncertainties. Then, sufficient conditions ensuring the exponential stability and guaranteed cost quadratic performance are presented by using the average dwell time approach. The distributed state feedback controller is designed by solving a set of LMIs. Finally, a simulation example is given to verify the effectiveness of the proposed method.     

控制增益符号未知的MIMO时滞系统自适应控制

针对一类带有死区模型并具有未知函数控制增益的不确定MIMO非线性时滞系统,基于滑模控制原理和Nussbaum函数的性质,提出了一种稳定的自适应神经网络控制方案.该方案放宽了对函数控制增益上界为未知常数的假设,并通过使用Lyapunov-Krasovskii泛函抵消了因未知时变时滞带来的系统不确定性.理论分析证明,闭环系统是半全局一致终结有界.仿真结果表明了该方法的有效性.     

Tube-based robust MPC for linear time-varying systems with bounded disturbances

In this paper, a novel synthesis approach for tube-based robust MPC is proposed. A novel feature is the fact that the proposed tube-based robust MPC algorithm can deal with both time-varying parameter and bounded disturbance. The proposed control law is the linear combination of two components. The first component steers the state of the nominal linear time-varying system to the origin. The second component keeps the state at each time step of the linear time-varying system with bounded disturbance within a tube whose center is the state of the nominal linear time-varying system. Finally, the state of the linear time-varying system with bounded disturbance is kept within a tube whose center is at the origin so robust stability is guaranteed. Satisfaction of the state and control constraints is ensured by employing tighter constraint sets for the nominal linear time-varying system. The computational burdens are the same as those in the case of the nominal linear time-varying system.     

一种新的复杂动态网络学习控制的自适应同步算法

提出了一种新的具有未知时变参数复杂动态网络同步的自适应学习控制方法.运用重新参数化技术,设计周期时变参数的自适应学习律、常参数的更新律以及自适应控制策略确保同步误差渐近收敛.通过构造复合能量函数给出同步的一个充分条件.最后给出一个复杂网络的例子验证所提方法的有效性.     

New approach to analysis and optimal control of time-varying systems via Taylor series

A new approach with three novel operations is proposed to deal with analysis of linear and bilinear time-varying systems and optimal control of linear time-varying systems via the Taylor series. The use of the three operations: polynomial mapping, general multiplication and integral transformer can greatly simplify the algorithm derivations and computations. Recursive algorithms are obtained and several illustrative examples are given.     

Design of robust-optimal output feedback controllers for linear uncertain systems using LMI-based approach and genetic algorithm

This paper considers the robust-optimal design problems of output feedback controllers for linear systems with both time-varying elemental (structured) and norm-bounded (unstructured) parameter uncertainties. Two new sufficient conditions are proposed in terms of linear-matrix-inequalities (LMIs) for ensuring that the linear output feedback systems with both time-varying elemental and norm-bounded parameter uncertainties are asymptotically stable, where the mixed quadratically-coupled parameter uncertainties are directly considered in the problem formulation. A numerical example is given to show that the presented sufficient conditions are less conservative than existing ones reported recently. Then, by integrating the hybrid Taguchi-genetic algorithm (HTGA) and the proposed LMI-based sufficient conditions, a new integrative approach is presented to find the output feedback controllers of the linear systems with both time-varying elemental and norm-bounded parameter uncertainties such that the control objective of minimizing a quadratic integral performance criterion subject to the stability robustness constraint is achieved. A design example of the robust-optimal output feedback controller for the AFTI/F-16 aircraft control system with the time-varying elemental parameter uncertainties is given to demonstrate the applicability of the proposed new integrative approach.     

Adaptive iterative learning control for nonlinearly parameterized systems with unknown time-varying delay and unknown control direction

This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method.     

Stabilization of uncertain nonholonomic systems via time-varying sliding mode control

This note addresses the robust stabilization problem for a general class of nonholonomic systems in the presence of drift uncertainties. The control approach developed is based on the combined applications of the sliding mode control technique and nonlinear time-varying systems theory. First, some properties of nonlinear time-varying systems are introduced for the purpose of designing sliding mode controller. An explicit time-varying feedback form is provided to guarantee the existence and uniqueness of periodic time-varying solution for the corresponding linear periodic partial differential equation. Second, an explicit discontinuous feedback control law is presented to guarantee the existence of sliding mode. The first integrals obtained by the previous periodic partial differential equation are then directly used to determine the switching function. The uniform asymptotic stability of the closed loop system is proved via the invariance principle of nonlinear time-varying systems. Finally, an example is given to illustrate the proposed approach.     

控制方向未知的高次非线性系统的鲁棒自适应控制

研究了一类具有不可控不稳定线性化的非线性系统的自适应控制问题.该类系统的控制方向未知且含有不确定时变非线性参数.应用Nussbaum-type增益技术和adding a power integrator递推设计方法,设计了一种鲁棒自适应状态反馈控制器.所设计的控制器能够保证闭环系统的所有信号全局一致有界,且系统的状态渐近趋于零.除了假设未知参数及不确定性有界外,所设计的控制策略不需要控制系数的任何先验知识.仿真例子验证了算法的有效性.     

Robust adaptive tracking for time-varying uncertain nonlinear systems with unknown control coefficients

Presents a robust adaptive control approach for a class of time-varying uncertain nonlinear systems in the strict feedback form with completely unknown time-varying virtual control coefficients, uncertain time-varying parameters and unknown time-varying bounded disturbances. The proposed design method does not require any a priori knowledge of the unknown coefficients except for their bounds. It is proved that the proposed robust adaptive scheme can guarantee the global uniform ultimate boundedness of the closed-loop system signals and disturbance attenuation.     

A new periodic adaptive control approach for time-varying parameters with known periodicity

A new adaptive control approach is proposed to deal with nonlinear systems with a class of time-varying parametric uncertainties, which are in an unknown compact set, periodic, nonvanishing, rapid time-varying, and the only prior knowledge is the periodicity. Unlike most continuous time adaptation laws which are of differential types, in this work a periodic type adaptation law is introduced for continuous time systems. The new adaptive controller updates the parameters and the control signal periodically in a pointwise manner over one entire period, in the sequel achieves the asymptotic tracking convergence.     

一类非线性参数化系统自适应重复学习控制

针对一类高阶非线性参数化系统, 利用分段积分机制, 提出了一种新的自适应重复学习控制方法. 该方法结合反馈线性化, 可以处理参数在一个未知紧集内周期性快时变的非线性系统, 通过引进微分-差分混合型参数自适应律, 设计了一种自适应控制策略, 使广义跟踪误差在误差平方范数意义下渐近收敛于零, 通过构造Lyapunov泛函, 给出闭环系统收敛的一个充分条件. 实例仿真结果说明了该方法的可行性.