一类参数不确定性系统的鲁棒控制

讨论了带有分母多项式摄动的参数不确定性系统的鲁棒镇定问题 ,给出了这类参数不确定性系统存在鲁棒控制器的一个充分条件 ,并且当这个条件被满足时 ,得到了部分鲁棒控制器的一个参数化公式 .

一类不确定性参数系统的自动跟踪控制融合策略

针对不确定性参数系统难以采用常规的PID控制的问题,提出了一种融合控制策略。分析了不确定性参数系统的控制难点与控制模型,基于仿人智能控制思路,设计了融合控制算法。以二阶滞后系统模型控制为例,仿真结果验证了所探讨智能融合控制策略的良好控制品质与强鲁棒性能。研究结果表明:融合策略是可行和有效的。

参数不确定性混沌系统的自适应控制

混沌系统的镇定是混沌系统控制的重要研究方向。文中给出了一类具有参数不确定性的混沌系统的无源化自适应控制器 ,通过面向无源性的设计方法 ,使系统稳定在零平衡点。并通过仿真实例 ,验证了该控制器的有效性。

基于自适应反步滑模与死区逆补偿的闭式泵控系统位置输出控制策略

为了解决电液伺服闭式泵控系统位置控制过程中系统参数不确定性和系统死区问题,提出了一种自适应反步滑模控制与死区逆补偿控制相结合的串联控制策略。首先,阐述了电液伺服闭式泵控系统的原理,在此基础上构建了电液伺服闭式泵控系统的数学模型和仿真模型;其次,基于自适应反步控制与滑模控制消除了系统非匹配不确定性及避免参数嵌套,设计了自适应反步滑模控制器;接着,利用平滑连续指标函数构造了光滑死区逆函数,设计了死区逆补偿控制器,并将两者组成串联控制器;最后,利用MATLAB/Simulink软件构建了系统仿真模型,并进行了相应的分析。研究结果表明:采用串联控制器的系统位移跟随精度可以达到±0.6μm,稳态精度则可以达到±0.3μm,系统在0.6 s左右时到达稳态;同时,参数自适应律在系统位置控制过程中可对系统不确定性参数进行实时调整,提高系统稳态控制精度;仿真结果验证了所提串联控制策略的有效性。

参数鲁棒镇定问题的可解性必要条件

给定对象族P(s,δ),其参数是向量P范数有界的不确定参数δ的仿射函数.用根轨迹法证明,P(s,δ)的任意两个元素的可同时镇定性等价于P(s,δ)的每个元素的可镇定性.结果表明,P(s,δ)的可镇定性可作为一个有效的判断条件以排除那些鲁棒镇定问题肯定无解的情况,从而更加有效的应用棱边和顶点等已知结果寻找鲁棒镇定问题的解.

Robust admissibility analysis of uncertain switched singular systems:a switched Lyapunov function approach

The robust admissibility analysis of a class of uncertain discrete-time switched linear singular（SLS） systems for arbitrary switching laws is addressed. The parameter uncertainty is assumed to be norm-bounded. First, by using the switched Lyapunov function approach, some new sufficient conditions ensuring the nominal discrete-time SLS system to be regular, casual and asymptotically stable for arbitrary switching laws are derived in terms of linear matrix inequalities. Then, the robust admissibility condition for the uncertain discrete-time SLS systems is presented. The obtained results can be viewed as an extension of previous works on the switched Lyapunov function approach from the regular switched linear systems to the switched linear singular cases. Numerical examples show the reduced conservatism and effectiveness of the proposed conditions.

ROBUST CONTROL OF A CLASS OF NONLINEAR SYSTEM WITH TIME-VARYING PAR AMETRIC UNCERTAINTIES

A class of triangular non li near system with disturbances which has unknown multiplicative time varying par ametric uncertainties in each virtual control is treated by a backstepping techn ique. The controller designed for all admissible uncertainties can guarantee tha t all states of its closed loop system are uniformly bounded. The robust contro ller design algorithm and a sufficient condition of the system stability are giv en. In addition, the closed loop system has an ISS property when the multiplica tive time varying parametric uncertainties are viewed as inputs to the system. Thus, this design provides a way to prevent a destabilizing effect of the multip licative time varying parametric uncertainties. Finally, simulational example i s given and simulational result shows that the controller exhibits effectiveness and excellent robustness.

Probabilistic model and analysis of coupled train-ballasted track-subgrade system with uncertain structural parameters

Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.

Direct adaptive control for lane keeping in intelligent vehicle systems

In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slid angle are fast.

Guaranteed cost sampled-data control for uncertain nonlinear time-varying delay system

The robust guaranteed cost sampled-data control was studied for a class of uncertain nonlinear systems with time-varying delay. The parameter uncertainties are time-varying norm-bounded and appear in both the state and the input control matrices. By applying an input delay approach, the system was transformed into a continuous time-delay system. Attention was focused on the design of a robust guaranteed cost sampled-data control law which guarantees that the closed-loop system is asymptotically stable and the quadratic performance index is less than a certain bound for all admissible uncertainties. By applying Lyapunov stability theory, the theorems were derived to provide sufficient conditions for the existence of robust guaranteed cost sampled-data control law in the form of linear matrix inequalities (LMIs), especially an optimal state-feedback guaranteed cost sampled-data control law which ensures the minimization of the guaranteed cost was given. The effectiveness of the proposed method was illustrated by a simulation example with the asymptotically stable curves of system state under the initial condition of x(0)=[0.679 6 0].

Robust stabilization and disturbance attenuation for a class of underactuated mechanical systems

The robust control problem for a class of underactuated mechanical systems called acrobots is addressed. The goal is to drive the acrobots away from the straight-down position and balance them at the straight-up unstable equilibrium position in the presence of parametric uncertainties and external disturbance. First, in the swing-up area, it is shown that the time derivative of energy is independent of the parameter uncertainties, but exogenous disturbance may destroy the characteristic of increase in mechanical energy. So, a swing-up controller with compensator is designed to suppress the influence of the disturbance. Then, in the attractive area, the control problem is formulated into a H~ control framework by introducing a proper error signal, and a sufficient condition of the existence of Hoo state feedback control law based on linear matrix inequality （LMI） is proposed to guarantee the quadratic stability of the control system. Finally, the simulation results show that the proposed control approach can simultaneously handle a maximum ±10% parameter perturbation and a big disturbance simultaneously.

Design for robust stabilization of nonlinear systems with uncertain parameters

Based on Lyapunov stability theory, a design method for the robust stabilization problem of a class of nonlinear systems with uncertain parameters is presented. The design procedure is divided into two steps: the first is to design controllers for the nominal system and make the system asymptotically stabi1ize at the expected equilibrium point; the second is to construct closed-loop nominal system based on the first step, then design robust controller to make the error of state between the origina1 system and the nominal system converge to zero, thereby a dynamic controller with the constructed closed-loop nominal system served as interior dynamic is obtained. A numerical simulation verifies the correctness of the design method.

Consistency and Asymptotic Property of a Weighted Least Squares Method for Networked Control Systems

In this paper, we study the problems related to parameter estimation of a single-input and single-output networked control system, which contains possible network-induced delays and packet dropout in both of sensor-to-controller path and controller-to-actuator path. A weighted least squares(WLS) method is designed to estimate the parameters of plant, which could overcome the data uncertainty problem caused by delays and dropout. This WLS method is proved to be consistent and has a good asymptotic property. Simulation examples are given to validate the results.

Synchronization of hyperchaotic Rossler system with uncertain parameters via nonlinear control

Based on the Lyapunov stability theory,a new method for synchronization of hyperchaotic Rossler system with uncertain parameters is proposed. By this method, choosing appropriate control law and adaptive update law of uncertain parameters, all the errors of system variable synchronization and of uncertain param- eter track are asymptotically stable. The theoretical analysis and the numerical simulations prove the efffectiveness of the oroDosed method.

Stabilization of a class of nonlinear discrete time systems with time varying delay

The stability and stabilization of a class of nonlinear discrete time delayed systems(NDTDS) with time-varying delay and norm-bounded nonlinearity are investigated. Based on discrete time Lyapunov–Krasovskii functional method, a sufficient delaydependent condition for asymptotic stability of nonlinear systems is offered. Then, this condition is used to design a new efficient delayed state feedback controller(DSFC) for stabilization of such systems. These conditions are in the linear matrix inequality(LMI) framework. Illustrative examples confirm the improvement of the proposed approach over the similar cases. Furthermore, the obtained stability and stabilization conditions will be extended to uncertain discrete time delayed systems(UDTDS) with polytopic parameter uncertainties and also with norm-bounded parameter uncertainties.

GROUP CONSENSUS FOR MULTIPLE NETWORKED EULER-LAGRANGE SYSTEMS WITH PARAMETRIC UNCERTAINTIES

In this paper,a group consensus problem is investigated for multiple networked agents with parametric uncertainties where all the agents are governed by the Euler-Lagrange system with uncertain parameters.In the group consensus problem,the agents asymptotically reach several different states rather than one consistent state.A novel group consensus protocol and a time-varying estimator of the uncertain parameters are proposed for each agent in order to solve the couple-group consensus problem.It is shown that the group consensus is reachable even when the system contains the uncertain parameters.Furthermore,the multi-group consensus is discussed as an extension of the couple-group consensus,and then the group consensus with switching topology is considered.Simulation results are finally provided to validate the effectiveness of the theoretical analysis.

Using the BirdTree.org website to obtain robust phylogenies for avian comparative studies： A primer

Comparative studies of trait evolution require accounting for the shared evolutionary history. This is done by includ- ing phylogenetic hypotheses into statistical analyses of species＇ traits, for which birds often serve as excellent models. The online publication of the most complete molecular phylogeny of extant bird species （www.birdtree.org, BirdTree hereafter） now allows evolutionary biologists to rapidly obtain sets of equally plausible phylogenetic trees for any set of species to be incorporated as a phylogenetic hypothesis in comparative analyses. We discuss methods to use BirdTree tree sets for comparative studies, either by building a consensus tree that can be incorporated into standard comparative analyses, or by using tree sets to account for the ef- fect of phylogenetie uncertainty. Methods accounting for phylogenetic uncertainty should be preferred whenever possible because they should provide more reliable parameter estimates and realistic confidence intervals around them. Based on a real compara- tive dataset, we ran simulations to investigate the effect of variation in the size of the random tree sets downloaded from BirdTree on the variability of parameter estimates from a bivariate relationship between mass-specific productivity and body mass. Irre- spective of the method of analysis, using at least 1,000 trees allows obtaining parameter estimates with very small （〈 0.15%） co- efficients of variation. We argue that BirdTree, due to the ease of use and the major advantages over previous ＇traditional＇ meth- ods to obtain phylogenetic hypotheses of bird species （e.g. supertrees or manual coding of published phylogenies）, will become the standard reference in avian comparative studies for years to come.