Oscillations and transfer properties of relay feedback systems with time-delay linear plants

Oscillations and transfer properties of relay feedback systems with linear plants having a dead time (time delay) are considered. Poincare maps are found explicitly in terms of the system parameters. The oscillatory and transfer properties are presented in the format of the locus of a perturbed relay system (LPRS), which represents the continuum of all possible periodic solutions and transfer properties of the system with a given linear plant. Conditions of local orbital asymptotic stability are found in terms of the system parameters. The proposed approach is illustrated by examples.     

线性时滞系统前馈-反馈次优控制: Taylor 级数法

研究线性时滞系统最优控制的前馈反馈近似设计问题.基于Taylor级数法,将系统的二次型最优控制问题转化为线性代数方程组的求解问题,给出了系统前馈反馈次优控制律的存在唯一性条件和Taylor级数表示形式.仿真算例验证了方法的有效性.     

A new convolution approach for the time-delay identification of systems with arbitrary entries

In this paper, an online delay identification approach of continuous-time linear systems with unstructured entries is achieved via a new algebraic technique. The arbitrary input and output trajectories are chosen with close and abundant crossing zero. Initial conditions and static disturbances are taken into account in the design of the identification approach. The proposed method is based on a distributional algebraic technique and a convolution approach. A proposed theorem is hence enounced to identify a single time-delay of such systems. The effectiveness of the proposed approach is demonstrated by an illustrative example. The obtained results show the high performances of the proposed time-delay identification approach in severe operation conditions of the considered system.     

A neural net-based time-delay compensation scheme and disturbance rejection for pneumatic systems

In practical electro-pneumatic or hydraulic servo mechanism, there is usually an unavoidable operating delay time in the solenoid valves. This may sometimes cause closed-loop instability if the time delay is not treated carefully in the control system designs. Furthermore, pneumatic actuators can offer high performance at low cost, but are often suffered from external disturbances depending on the operating conditions. This paper proposes a non-model-based design approach for pneumatic actuating systems. In the proposed control system, a gain scheduled fuzzy-PID controller ensures tracking performance an adaptable wavelet neuro compensator compensates for time-delay of the control valve, and a disturbance rejecter diminishes influence from load changes. A condition ensuring the closed-loop stability is derived. The proposed design is experimentally verified to show its effectiveness.     

具有持续扰动的时滞系统前馈2反馈最优控制

针对外部持续扰动下的线性时滞系统，提出一种前馈-反馈最优控制的逐次逼近算法．利用逐次逼近算法，将既含有时滞项又含有超前项的两点边值问题转化为不合时滞项和超前项的线性两点边值问题族，并证明了线性两点边值问题族的解序列一致收敛于原系统最优控制律．得到的最优控制律由解析的无时滞前馈-反馈控制部分和伴随向量序列极限形式的时滞补偿控制部分组成．通过截取时滞补偿序列的有限项，得到系统的前馈-反馈次优控制律．仿真示例表明，该方法对外部持续扰动具有良好的鲁棒性．     

一类离散不确定时滞系统的输出反馈变结构控制

针对一类离散不确定时滞系统,提出一种输出反馈变结构控制算法,该算法使系统状态无需完全可测.通过研究离散不确定时滞系统的简约型,基于LMI技术给出了滑模平面的设计方法,推导出了稳定的滑模面存在的充分条件,并将参数不确定性的影响等效为名义时滞系统的外界干扰,利用时延技术对干扰进行在线估计,从而抵消掉系统中的不确定性.采用离散趋近律的方法设计控制律,并通过仿真算例验证了所提出算法的有效性.     

不确定时滞分布参数系统鲁棒控制的LMI方法

对常时滞、变时滞的不确定分布参数控制系统,提出了一种与现有的研究分布参数控制系统不同的鲁棒控制方法.该方法通过构造平均Lyapunov函数,利用线性矩阵不等式知识,在只要求系统本身所固有的系数是负定矩阵的条件下,给出了所给的分布参数系统镇定的充分条件.当模型中的时滞为常时滞时,所得的充分条件与时滞无关.当模型中的时滞为变时滞时,所得模型的镇定准则依赖于时滞.此外,该方法与已有方法比较的一个显著优点就是所获得的条件容易检验,因而易于应用.最后举了一个实例以说明该方法的有效性.     

一类非线性时滞互联系统模糊分散输出反馈控制

对于一类状态不可测非线性互联时滞系统,给出一种基于观测器的模糊分散输出反馈控制方法.首先采用模糊T-S模型对非线性互联时滞系统进行模糊建模,在此基础上给出了模糊分散观测器和基于观测器的模糊分散输出控制器的设计.应用李亚普诺夫函数法和线性矩阵不等式方法给出了模糊分散控制系统稳定的充分条件.仿真结果进一步验证了所提出的模糊分散控制方法的有效性.     

A clustering-based approach for the identification of a class of temporally switched linear systems

The behaviours of hybrid dynamic systems (HDS) are determined by combining continuous variables with discrete switching logic. The identification of a HDS aims to find an accurate model of the system’s dynamics based on its past inputs and outputs. In pattern recognition (PR) methods, each mode is represented by a set of similar patterns that form restricted regions in the feature space. These sets of patterns are called classes. A pattern is a vector built from past inputs and outputs. HDS identification is a challenging problem since it involves the estimation of different sets of parameters without knowing in advance which sections of the measured data correspond to the different modes of the system. Therefore, HDS identification can be achieved by combining two steps: clustering and parameter estimation. In the clustering step, the number of discrete modes (i.e., the classes that input-output data points belong) is estimated. The parameter estimation step finds the parameters of the models that govern the continuous dynamics in each mode. In this paper, an unsupervised PR method is proposed to achieve the clustering step of the identification of temporally switched linear HDS. The determination of the number of modes does not require prior information about the modes or their number.     

Command and stability systems for aircraft: A new digital adaptive approach

Ensuring good handling qualities of aircraft in the whole flight envelope is a difficult and time consuming task, because aircraft parameters are subjected to drastic changes. Adaptive control is a very promising technique to solve these problems and to improve the performance deficiencies of conventional stability systems with preprogrammed control gains.The approach used in this paper is based on digital control and on a special stabilization concept which requires only three dynamic parameters of the aircraft to meet standard handling qualities criteria. These three parameters cannot be measured directly. Therefore a recursive, weighted least squares algorithm is used, which delivers sufficient fast and accurate on-line parameter estimates. The adaptive control system has proven its very satisfactory performance in several digital and hybrid simulations including fast parameters variations and turbulence conditions. Real flight test data have been used to verify the performance of the identification process and recently flight tests of the complete adaptive system have been successfully carried out with the DO 28 D SK YSERVANT aircraft.     

A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.     

T-S模糊时滞系统的时滞相关鲁棒稳定新判据

研究了基于Takagi-Sugeno（T-S）模糊模型描述的非线性时滞系统的稳定性和H∞扰动抑制问题,利用线性矩阵不等式（LMI）技术,导出了一种满足优化H∞性能的时滞相关稳定新判据,该判据不仅适用于系统时滞变化率大于1的情形,且与现有方法相比具有更小的保守性,数值仿真结果证明了所提方法的有效性。     

A new adaptive scheme for a class of discrete-time nonlinear systems

A new adaptive control scheme for discrete-time systems is proposed. The objective is the tracking of the trajectory. Global boundedness convergence and boundedness are obtained for a certain subclass of nonlinear systems.     

Dynamic leaders’ containment control of high-order multi-agent systems with state time-delay: an LMI approach

This paper addresses the containment control of a multi-agent system with dynamic leaders while considering the state time-delay and time-varying input disturbances. The agents dynamics are assumed to be high-order integrals and an unkown state time-delay with a known upper bound is considered. In order to deal with dynamic leaders and time-varying input disturbances, an appropriate distributed PI^p-type-based control protocol is proposed in this study. Thereafter, utilising the Lyapunov–Krasovskii stability theorem and based on LMI (Linear Matrix Inequality) approach, two theorems are proved which guarantee asymptotically stability of the multi-agent system with fixed and switching networks. In addition to stability assurance, the gains of the proposed protocol are achieved through solving the LMI. Finally, some numerical examples are given to demonstrate the validity of the theoretical results.     

An approach to polynomial NARX/NARMAX systems identification in a closed-loop with variable structure control

Many physical processes have nonlinear behavior which can be well represented by a polynomial NARX or NARMAX model. The identification of such models has been widely explored in literature. The majority of these approaches are for the open-loop identification. However, for reasons such as safety and production restrictions, open-loop identification cannot always be done. In such cases, closed-loop identification is necessary. This paper presents a two-step approach to closed-loop identification of the polynomial NARX/NARMAX systems with variable structure control （VSC）. First, a genetic algorithm （GA） is used to maximize the similarity of VSC signal to white noise by tuning the switching function parameters. Second, the system is simulated again and its parameters are estimated by an algorithm of the least square （LS） family. Finally, simulation examples are given to show the validity of the proposed approach.     

A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems

A universal, approximation-free state feedback control scheme is designed for unknown pure feedback systems, capable of guaranteeing, for any initial system condition, output tracking with prescribed performance and bounded closed loop signals. By prescribed performance, it is meant that the output error converges to a predefined arbitrarily small residual set, with convergence rate no less than a certain prespecified value, having maximum overshoot less than a preassigned level. The proposed state feedback controller isolates the aforementioned output performance characteristics from control gains selection and exhibits strong robustness against model uncertainties, while completely avoiding the explosion of complexity issue raised by backstepping-like approaches that are typically employed to the control of pure feedback systems. In this respect, a low complexity design is achieved. Moreover, the controllability assumptions reported in the relevant literature are further relaxed, thus enlarging the class of pure feedback systems that can be considered. Finally, simulation studies clarify and verify the approach.     

Physiologic insulin delivery with insulin feedback: A control systems perspective

Individuals with type 1 diabetes mellitus must effectively manage glycemia to avoid acute and chronic complications related to aberrations of glucose levels. Because optimal diabetes management can be difficult to achieve and burdensome, research into a closed-loop insulin delivery system has been of interest for several decades. This paper provides an overview, from a control systems perspective, of the research and development effort of a particular algorithm—the external physiologic insulin delivery system. In particular the introduction of insulin feedback, based on β-cell physiology, is covered in detail. A summary of human clinical trials is provided in the context of the evolution of this algorithm, and this paper outlines some of the research avenues that show particular promise.     

基于LM I 的一类非线性时滞关联大系统的分散模糊控制

针对一类采用Takagi—Sugeno模糊模型描述的非线性时滞关联大系统，研究其分散模糊状态反馈控制器设计问题；利用Lyapunov稳定性分析理论和线性矩阵不等式等工具，得到了闭环系统的可镇定条件和相应的分散模糊状态反馈控制器；在此基础上，通过求解具有线性矩阵不等式组约束的凸优化问题，给出了具有较小反馈增益的分散模糊控制器设计方法。     

output feedback control design for uncertain fuzzy singularly perturbed systems: an LMI approach

This paper examines the problem of designing a robust H_∞ output feedback controller for a class of singularly perturbed systems described by a Takagi–Sugeno fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain singularly perturbed nonlinear systems to have an H_∞ performance are derived. To eliminate the ill-conditioning caused by the interaction of slow and fast dynamic modes, solutions to the problem are presented in terms of LMIs which are independent of the singular perturbation . The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard singularly perturbed nonlinear systems. A numerical example is provided to illustrate the design developed in this paper.