非线性互质分解方法中的系统核表示

主要介绍了非线性互质分解理论的最新研究动态—系统核表示 .从系统核表示与右互质分解的关系、概念提出之背景及其在 Youla参数的控制器构造方面所起的作用强调了其在非线性互质分解理论中的重要性 .同时也从互质分解的存在性、系统的稳定鲁棒性、系统辨识及观测器设计等各方面介绍了非线性互质分解方法在控制理论中的应用     

非线性系统的反馈镇定和右互质分解

本文在一种很广泛的框架中讨论因果的非线性输入-输出算子的右互质分解问题,给出了 在不同稳定性定义下的反馈镇定和存在右互质分解之间的关系.     

基于鲁棒右互质分解的直流伺服系统精确跟踪控制

对含有不确定性的直流伺服控制系统,通过应用鲁棒右互质分解方法,设计了一种基于鲁棒右互质分解的精确跟踪控制系统;通常情况下,直流伺服系统中存在诸如非线性特性及参数辨识引起的模型误差和外界扰动,在设计的控制系统中,未知模型误差和外界扰动对系统性能的影响都被看作直流伺服系统的不确定性;在考虑到这些不确定性情况下,设计了一种基于鲁棒右互质分解理论的精确跟踪控制;首先在考虑未知的不确定模型影响系统性能指标的情况下,设计了一种基于演算子理论的反馈控制结构,此结构可以消除不确定模型的影响,在此基础上,设计了基于鲁棒右互质分解的鲁棒精确跟踪控制系统,得出精确跟踪条件;仿真结果表明使用提出的方法可以有效地消除不确定性,使得伺服系统具有很强的鲁棒性和精确跟踪能力。     

基于降阶观测控制器的一般真系统的双互质分解

推广了严格真系统的结果,给出了基于降阶观测控制器的一般真系统双互质分解的状态空间实现,并分析了相应控制器参数化的物理意义。最后,揭示了带有和没有辅助稳定矩阵的两种双互质分解的有趣的联系,得出了简单的计算公式。     

一类非最小相位多变量系统的自适应控制设计

利用一种有界输入计算方法,根据对象的左互质分解（ＬＣＦ） 特性,对一类多变量离散时间模型跟踪控制系统（ ＭＦＣＳ） 进行设计,进而给出相应的非最小相位系统自适应控制器的设计方法。     

基于演算子理论的液位控制系统应用研究

为了模拟工业锅炉液位过程控制,以水箱过程控制实验装置为基础进行了液位控制的实验研究。首先提出了基于演算子理论的右互质分解方法实现非线性控制系统的设计;接着以PCL-812PG数据采集卡为基础进行了数据采集与驱动设计;然后利用设计好的控制器在Visual C++开发环境下对该液位系统进行了实验研究;实验中液位设定值为300mm,结果显示液位控制系统上升时间小于260s,系统超调低于5%,满足要求的性能指标;实验结果表明了控制系统设计的有效性。     

利用位置和加速度反馈的矩阵二阶系统特征结构配置

考虑一类利用位置和加速度反馈二阶线性系统的特征结构配置问题．在允许闭环系统的特征值是未知的前提下,结合矩阵多项式的右互质分解提出二阶线性系统特征结构配置的参数化方法,建立反馈增益阵和特征向量矩阵的显示参数化表达式．本文涉及的参数化方法直接将二阶系统模型转化为一阶状态空间形式,从而降低了系统设计中的计算工作量,并且提出的算法简单,无“返回”步骤．最后,数值算例表明了该算法的有效性．     

自适应的时变比例增益的预测PID控制器

为了利用PID控制获得先进的控制性能,将广义预测控制(GPC)用于PID参数的实时优化,在此基础上提出了一种新的基于GPC的自适应PID控制器的设计方法.该PID控制器具有时变的比例增益,并且PID控制器的设计利用了GPC的未来参考输入.因此,GPC控制律能由设计的PID控制器精确实现.为使GPC控制器稳定地获得比例增益,采用了基于互质因子分解扩展的强稳定GPC,独立于利用标准GPC设计的闭环系统而重新设计GPC控制器,保证了闭环系统的稳定性.此外,利用递推最小二乘法对系统进行在线辨识,修正模型参数,增强了系统的抗扰性.以一阶时滞非最小相位系统为被控对象,在Matlab中对该设计方法进行了仿真,仿真结果验证了该方法的有效性.     

一类新非线性控制方法:基于演算子理论的控制方法综述

以基于演算子理论的鲁棒右互质分解 (Operator-based robust right coprime factorization, RRCF) 为基础, 提出了一种较新的非线性鲁棒控制方法.本文将简述此方法的概念、 基本理论及其应用. 具体地说, 本文首先介绍此方法的起源与基本概念; 然后,讨论此方法在系统的鲁棒稳定性、 输出跟踪与故障检测方面的设计等问题;最后,介绍此方法的实际应用从而进一步证明其有效性.     

H∞控制中Youla稳定补偿器参数的新算法

为使H∞控制频域方法更加便于应用,对H∞控制中Youla稳定补偿器的设计方法进行研究,基于传递函数矩阵互质分解和多项式矩阵最大公因子理论.提出Youla补偿器参数的两个新算法;在此基础上运用Smith意义上等价的概念,以定理形式提出另一个更便于计算机运算的算法;另外,基于规范化互质分解理论提出求解Youla补偿器参数的第四个定理.与传统的Youla补偿器算法相比,这些新算法具有过程简单、计算量小和便于工程应用等优点.     

离散时间菱形不确定系统的鲁棒控制器设计

对一类MIMO的菱形不确定离散时间线性系统，利用有限端点检验结果，提出一种输出反馈控制器的设计方法，导出了输出反馈增益矩阵置所满足的一组特殊非线性方程，通过求解该方程组；使有限个线性系统输出反馈LQ问题同时达到最优，从而保证菱形闭环系统是鲁棒渐近稳定的。数值例子说明了该方法的正确性。     

Boundedness properties of nonlinear quasi-dissipative systems

Boundedness results for feedback interconnections of quasi-dissipative systems are presented. A classical result due to Hill and Moylan is generalized to the case of finite power gain stability of feedback interconnection of quasi-dissipative systems. It is also shown that under the assumption of strong finite-time detectability, such an interconnection has uniformly ultimately bounded trajectories for any uniformly bounded input.     

稳定化的有限频段H∞控制及有限频段跟踪问题

基于GKYP引理的动态输出反馈设计,未保证设计后闭环系统的稳定性。针对以小增益作为指标的有限频段动态输出反馈问题,在不增加新变量的前提下,增加稳定性约束,使得设计后的闭环系统渐近稳定且满足有限频段性能指标。针对增加约束后难以找到可行解的情况,基于零空间条件的不惟一性,补充了另一种零空间条件,从而扩大了问题的可行域。将改进后的方法应用于有限频段跟踪问题的研究,通过仿真例子验证,有限频段动态输出反馈虽然存在保守性,但在合理选择基矩阵R的情况下,仍然可以使得其保守性小于传统的全频段最优H∞控制的保守性。     

Stabilizable regions of receding horizon predictive control with input constraints

Stabilizable regions of receding horizon predictive control (RHPC) with input constraints are examined. A feasible region of states, which is spanned by eigenvectors of the closed-loop system with a stabilizing feedback gain, is derived in conjunction with input constraints. For states in this region, the feasibility of state feedback is guaranteed with the corresponding feedback gain. It is shown that an RHPC scheme with adequate finite terminal weights can guarantee stability for any initial state which can be steered into this region using finite number of control moves in the presence of input saturation. This methodology results in feasible regions which are infinite (in certain directions) even in the case of open-loop unstable systems. It is shown that the proposed feasible regions are larger than the ellipsoidal regions which were suggested in earlier works. We formulated the optimization problem in LMI so that it can be solved by semidefinite programming.     

Output‐feedback control strategies of lower‐triangular nonlinear nonholonomic systems in any prescribed finite time

In this paper, output‐feedback control strategies are proposed for lower‐triangular nonlinear nonholonomic systems in any prescribed finite time. Specifically, by employing the input‐state–scaling technique, the controlled systems are firstly converted into lower‐triangular nonlinear systems, which makes it possible to study such systems using the high‐gain technique. Then, by introducing a scaling of the state by a function that grows unbounded toward the terminal time and proposing a high‐gain observer–prescribed finite time recovering the system states, the output‐feedback regulation control problem in any prescribed finite time is firstly achieved for nonlinear nonholonomic systems with unknown constant incremental rate. Moreover, by designing another time‐varying high gain, the output‐feedback stabilization control problem in any prescribed finite time is then achieved for nonlinear nonholonomic systems with a time‐varying incremental rate. Finally, a numerical example is introduced to show the effectiveness of proposed control strategies.     

Optimal fuzzy controller design: local concept approach

In this paper, we present a global optimal and stable fuzzy controller design method for both continuous- and discrete-time fuzzy systems under both finite and infinite horizons. First, a sufficient condition is proposed which indicates that the global optimal effect can be achieved by the fuzzily combined local optimal controllers. Based on this sufficient condition, we derive a local concept approach to designing the optimal fuzzy controller by applying traditional linear optimal control theory. The stability of the entire closed-loop continuous fuzzy system can be ensured by the designed optimal fuzzy controller. The optimal feedback continuous fuzzy system can not only be guaranteed to be exponentially stable, but also be stabilized to any desired degree. Also, the total energy of system output is absolutely finite. Moreover, the resultant feedback continuous fuzzy system possesses an infinite gain margin; that is, its stability is guaranteed no matter how large the feedback gain becomes. Two examples are given to illustrate the proposed optimal fuzzy controller design approach and to demonstrate the proved stability properties     

A new methodology to compute stabilizing control laws for continuous‐time LTV systems

This paper is devoted to the problem of computing control laws for the stabilization of continuous‐time linear time‐varying systems. First, a necessary and sufficient condition to assess the stability of a linear time‐varying system based on the norm of the transition matrix computed over a sequence of successive finite‐time intervals is proposed. A link with a stability condition for an equivalent discrete‐time model is also established. Then, 3 approaches for the computation of stabilizing state‐feedback gains are proposed: a continuous‐time technique, ie, directly derived from the stability condition, not suitable for numerical implementation; a method based on the stabilization of the discrete‐time equivalent model along with a transformation to generate the desired continuous‐time gain; and the computation of stabilizing gains for a set of periodic discrete‐time systems. Finally, by adapting one of the existing methods for the stabilization of periodic discrete‐time systems, an algorithm for the computation of a stabilizing state‐feedback continuous‐time gain is proposed. A numerical example illustrates the validity of the technique.     

Finite‐time stabilization of stochastic nonlinear systems with SiISS inverse dynamics

This paper investigates the finite‐time control problem for a class of stochastic nonlinear systems with stochastic integral input‐to‐state stablility (SiISS) inverse dynamics. Motivated by finite‐time stochastic input‐to‐state stability and the concept of SiISS using Lyapunov functions, a novel finite‐time SiISS using Lyapunov functions is introduced firstly. Then, by adopting this novel finite‐time SiISS small‐gain arguments, using the backstepping technique and stochastic finite‐time stability theory, a systematic design and analysis algorithm is proposed. Given the control laws that guarantee global stability in probability or asymptotic stability in probability, our design algorithm presents a state‐feedback controller that can ensure the solution of the closed‐loop system to be finite‐time stable in probability. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control scheme. Copyright © 2017 John Wiley & Sons, Ltd.     

Time‐varying feedback for stabilization in prescribed finite time

This paper provides a time‐varying feedback alternative to control of finite‐time systems, which is referred to as “prescribed‐time control,” exhibiting several superior features: (i) such time‐varying gain–based prescribed‐time control is built upon regular state feedback rather than fractional‐power state feedback, thus resulting in smooth (C^m) control action everywhere during the entire operation of the system; (ii) the prescribed‐time control is characterized with uniformly prespecifiable convergence time that can be preassigned as needed within the physically allowable range, making it literally different from not only the traditional finite‐time control (where the finite settling time is determined by a system initial condition and a number of design parameters) but also the fixed‐time control (where the settling time is subject to certain constraints and thus can only be specified within the corresponding range); and (iii) the prescribed‐time control relies only on regular Lyapunov differential inequality instead of fractional Lyapunov differential inequality for stability analysis and thus avoids the difficulty in controller design and stability analysis encountered in the traditional finite‐time control for high‐order systems.     

A small gain theorem for systems with non-causal subsystems

Small gain theorems are used to verify the stability of a feedback interconnection of causal stable systems. In this work, we extend the small gain condition to test the stability of a feedback interconnection of two stable systems at least one of which is non-causal. This result may find application in the robust controller design for time-delay systems.