Extracting gene regulation information for cancer classification

In this paper, we address the problem of extracting gene regulation information from microarray data for cancer classification. From the biological viewpoint, a model of gene regulation probability is established where three types of gene regulation states in a tissue sample are assumed and then two regulation events correlated with the class distinction are defined. Different from the previous approaches, the proposed algorithm uses gene regulation probabilities as carriers of regulation information to select genes and construct classifiers. The proposed approach is successfully applied to two public available microarray data sets, the leukemia data and the prostate data. Experimental results suggest that gene selection based on regulation information can greatly improve cancer classification, and the classifier based on regulation information is more efficient and more stable than several previous classification algorithms.     

基于模式运动的一类生产过程调节性能与聚类参数关系

为研究基于模式运动的系统动力学描述方法中聚类参数对生产过程调节性能的影响,给出描述系统动态调节性能与产品质量调节性能的指标,分析并建立了聚类参数与系统调节性能间的关系;介绍了基于模式运动的一类复杂生产过程建模方法,并利用LMI方法给出了状态反馈控制器设计方法;提出了基于粒子群优化方法的最大熵聚类算法,定义并提取了系统调节性能指标;利用提出的新的覆盖分类神经网络,建立最大熵聚类方法的参数与调节性能间的映射关系,并分析了分类网络泛化能力;采用实际烧结矿生产数据进行仿真,结果表明所提方法可以分析与建立调节性能与聚类参数间的关系,且可为实际生产中聚类参数的选择提供一定的依据.     

基于Bagging算法的水库水沙联合智能调度

水库水沙调度是一项非常复杂的综合性问题,存在大量的非线性关系。传统的调度方法往往难以达到满意的效果。该文提出了一种基于Bagging算法的水库调度方法。用神经网络建立水库调度预测函数,在此基础上,利用Bagging算法构造了基于神经网络的预测函数序列进行预测,预测的平均值用于水库调度。实验结果表明,符合实际情况,且具有明显的经济安全效益。     

智能温度控制器在罩式退火炉上的应用

介绍了罩式退火炉的温度控制系统。该系统的控制核心部件是英国欧陆８１８ 型智能温度调节器,它可以针对不同的退火工艺,预先设定多条温度控制曲线,并进行 Ｐ Ｉ Ｄ 闭环调节或自动优化控制。采用欧陆８１８ 型智能温度调节器组成的温控系统结构简单,工作稳定,控制灵活,调整方便,可广泛应用于各种温度控制场合。     

A general framework for tackling the output regulation problem

Output regulation aims to achieve, in addition to closed-loop stability, asymptotic tracking and disturbance rejection for a class of reference inputs and disturbances. Thus, it poses a more challenging problem than stabilization. For over a decade, the nonlinear output regulation problem has been one of the focuses in nonlinear control research, and active research on this problem has generated many fruitful results. Nevertheless, there are two hurdles that impede the further progress of the research on the output regulation problem. The first one is the assumption that the solution or the partial solution of the regulator equations is polynomial. The second one is the lack of a systematic mechanism to handle the global robust output regulation problem. We establish a general framework that systematically converts the robust output regulation problem for a general nonlinear system into a robust stabilization problem for an appropriately augmented system. This general framework, on one hand, relaxes the polynomial assumption, and on the other hand, offers a greater flexibility to incorporate recent new stabilization techniques, thus setting a stage for systematically tackling the robust output regulation with global stability.     

Control of two Electrical Plants

In this paper, a controller is recommended for the regulation of two electrical plants. Since electrical plants generate electricity all the time, the regulation to get that all the plant states reach constant behaviors is important. Two main characteristics of the introduced method are: (i) it is based in the separation of the plant model equations, only some model equations are chosen for the regulation while the other model equations are ignored, it avoids the difficulty in the consideration of the full plant model; (ii) the Lyapunov strategy is employed to analyze the stability of the selected model equations in the electrical plant, it lets to ensure the regulation purpose. The advised method is applied in a gas turbine and a wind turbine for the electricity generation.     

The local approximate output regulation problem: convergence region estimates

In this paper, the problem of local approximate output regulation is considered. The presented results answer the question: given a controller solving the local approximate output regulation problem, how to estimate the set of initial conditions for which approximate output regulation occurs. The results are illustrated by a disturbance rejection problem for the TORA system. Copyright © 2004 John Wiley & Sons, Ltd.     

Global Robust Output Regulation for a Class of Switched Nonlinear Systems with Nonlinear Exosystems

The problem of global robust output regulation for a class of switched nonlinear systems with nonlinear exosystems is investigated in this paper where not all subsystems are stabilizable. First, as an extension of the concept of non‐switched internal model, this paper defines a switched internal model, which together with the plant is called the switched augmented system. Also, we show that the problem of output regulation for the switched nonlinear system can be converted into a global robust regulation problem of the switched augmented system. Second, based on the average dwell time method, the global robust regulation problem under a class of switching signals with average dwell time is solved, which leads to the solution of the problem of global robust output regulation. Finally, an example is provided to demonstrate the effectiveness of the proposed design approach.     

Output regulation of linear systems with bounded continuous feedback

This paper studies the classical problem of output regulation for linear systems subject to control constraint. The asymptotically regulatable region, the set of all initial conditions of the plant and the exosystem for which output regulation is possible, is characterized in terms of the controllable region of the antistable subsystem of the plant. Continuous output regulation laws, of both state feedback type and error feedback type, are constructed from a given stabilizing state feedback law. It is shown that a stabilizing feedback law that achieves a larger domain of attraction leads to a feedback law that achieves output regulation on a larger subset of the asymptotically regulatable region. A feedback law that achieves global stabilization on the asymptotically controllable region leads to a feedback law that achieves output regulation on the entire asymptotically regulatable region.     

Regulated quality diffusion under quadratic costs

We study how to regulate quality processes so as to attain a desirable target. The effect of the regulation varies in a random fashion due to disturbances. The interaction between regulatory actions and outcomes is termed quality diffusion . In this paper, we address a specific version of such diffusion known as a mean-reverting process (also termed Ornstein Uhlenbeck process). The total production cost includes both a quadratic cost of quality deviations, and a linear cost of production control. Assuming that both regulation and quality processes are continuously reviewed, an optimal quality regulation policy is sought to minimize the total production cost over a finite horizon. The optimal regulation is found to be a surge-discharge control that can be characterized by a triplet including a discharge time, a stopping time, and a discharge function. The surge-discharge control is easy to be implemented for a variety of applications. Computational algorithms for the optimal control are developed.     

一类带扰动线性开关系统的误差反馈输出调节问题

研究了带扰动线性开关系统的输出调节问题,在开关系统的一个凸组合系统输出调节问题可解的条件下,设计每个子系统的控制器及开关系统的切换规律,从而给出开关系统输出调节问题的控制策略.     

以激励为导向的配电网分布式电压调节

针对高渗透率可再生能源导致的配电网电压波动及越限问题,提出了基于分布式机组快速电压支撑能力的辐射状配电网分布式电压调节算法。不同于已有采用直接控制方式的分布式电压调节,利用激励信号间接控制分布式机组来实现配电网分布式电压调节。在所提的电压调节问题中,不但考虑了配电网从主网购入有功的成本,同时考虑了电压调节过程中配电网内附加无功的平衡。基于障碍函数法和对偶上升算法,将所提电压调节问题转化为一个可由配电网各节点协同求解的分布式优化问题,并提出了相应的以激励为导向的分布式电压调节框架。在该框架下,配电网运营商根据各节点反馈的出力决策,持续更新并发布节点有功及无功激励信号来协调各节点的出力,从而实现配电网电压的分布式调节。仿真研究证明了该算法在配电网电压陡降和电压突升情形下的有效性。     

Almost Asymptotic Regulation of Markovian Jumping Linear Systems in Discrete Time

This paper considers the problems of almost asymptotic output regulation for discrete‐time Markovian jumping linear systems. Based on a stochastic Lyapunov‐Krasovskii functional framework, sufficient conditions for the extension of the regulation scheme to such stochastic systems are obtained via state feedback and via error feedback. Relying on a characterization of the feedback controllers, the almost asymptotic regulation is accomplished. The problem of guaranteeing stochastic stability and almost asymptotic tracking is achieved by solving linear matrix inequalities subject to a set of linear equality constraints. In order to ensure relaxed solutions of the regulation equations, a semi‐definite optimization approach via disciplined convex programming is outlined. Simulation results also are given to illustrate the effectiveness of the proposed design approach.     

Semi-global output regulation for linear systems with input saturation by composite nonlinear feedback control

To improve transient performance of output response, this paper applies composite nonlinear feedback (CNF) control technique to investigate semi-global output regulation problems for linear systems with input saturation. Based on a linear state feedback control law for a semi-global output regulation problem, a state feedback CNF control law is constructed by adding a nonlinear feedback part. The extra nonlinear feedback part can be applied to improve the transient performance of the closed-loop system. Moreover, an observer is designed to construct an output feedback CNF control law that also solves the semi-global output regulation problem. The sufficient solvability condition of the semi-global output regulation problem by CNF control is the same as that by linear control, but the CNF control technique can improve the transient performance. The effectiveness of the proposed method is illustrated by a disturbance rejection problem of a translational oscillator with rotational actuator system.     

Perfect control of the robust servomechanism problem

The problem of finding a robust servomechanism controller which achieves exact asymptotic tracking/regulation for a modeled class of reference and disturbance signals, arbitrarily good approximate error regulation (AGAER) for reference/disturbance signals which lie outside of this design class, and arbitrarily good transient response is considered. It is shown that a necessary condition that must be satisfied to accomplish this requirement is that the initial conditions of the servocompensator should be zero. An explicit algorithm for designing such controllers is then given. A simple controller, called the high gain servomechanism controller is also presented, which has the property that it gives AGAER and arbitrarily good transient response, when the robust exact asymptotic tracking/regulation requirement is relaxed. This controller shows that dynamics in a controller is not essential for achieving good error regulation in the presence of unknown unmeasurable disturbances. It is also shown that using the controllers proposed, exact error regulation occurs, for a larger class of design signals, called the extended disturbance/reference input signals, even if the conditions for perfect control are not satisfied. Some examples are included to illustrate the type of results obtained.     

Adaptive control of nonlinear systems with nonlinear parameterization

An adaptive feedback regulation scheme is proposed for a class of single input nonlinear systems, with nonlinear parameterizations. A proof of local regulation is given. The results are validated through a simulation study.     

Multi-robot coordination for jams in congested systems

This paper describes a novel coordination methodology of autonomous mobile robots for jams in a congested system with bottlenecks. This methodology consists of two approaches based on an interaction force and behavior regulation rule for a robot. The former is for directly controlling velocity of a robot in the behavioral dynamics, and the latter is for amplifying the interaction force so that velocity of a robot is externally reduced in a certain place. In the first approach, a previously-proposed robot behavior control technique by the authors that utilizes the interaction force among robots is improved, and it enables the robots to reduce their velocity in response to not only a jam but also a decelerating robot immediately in front of them. In the second approach, a behavior regulation rule in connection with the interaction force is designed and provided in congested segments on a lane. Thus, the amplified interaction force causes the robots to move more slowly in the congested segments. The improved robot behavior control technique and behavior regulation rule are implemented in simulation experiments and compared to the previous robot behavior control technique and adaptive cruise control (ACC) that has been proposed for vehicles. Furthermore, the improved interaction force and behavior regulation rule are appended to ACC, and the potential of using ACC with the two approaches is discussed. Finally, the effectiveness of the improved interaction force and the behavior regulation rule for multi-robot coordination in a congested system with bottlenecks is shown.     

Semi-global robust output regulation for a class of singular nonlinear systems via nonlinear internal model

Most of existing results on robust output regulation problem of singular nonlinear systems are limited to local solutions. In this paper, the semi-global robust output regulation problem for a class of singular nonlinear systems is investigated by using a nonlinear internal model. Attaching a nonlinear internal model to the singular nonlinear system yields an augmented singular nonlinear system whose semi-global robust stabilisation solution leads to the solution of the semi-global robust output regulation problem of the original singular nonlinear system. The solvability conditions of the semi-global output regulation problem are established by addressing the solvability of the robust stabilisation problem of augmented singular nonlinear system. Finally, a numerical simulation example is used to illustrate the design of the semi-global regulator for the singular nonlinear systems.     

New matching conditions for output regulation of a class ofuncertain nonlinear systems

Some sufficient conditions for the structure of modelling uncertainties for output regulation of uncertain systems are presented. It turns out that these conditions include as special cases the ordinary matching conditions for state regulation of uncertain systems and the disturbance decoupling condition. The previous restrictions on the structure of modelling uncertainties can be considerably relaxed in the case of output regulation. The significance of the result is shown by a simple example     

Evolution of regulation errors in the diffusion layer in electrodeposition process control

A random field induced by infinitely many noises emerges in numerous processes, such as a mixed boundary electrochemical deposition process, which is determined by the main reaction and several side reactions. Since the process is controlled on one boundary without knowledge of the side reactions, a model error emerges and the regulation error trails. The model considered in this paper allows for general settings and is defined for white noise and colour noise. The white noise is responsible for unpredictable model errors and the colour noise for systematic errors. A relatively simple boundary control is applied that, when lifted into the domain, acts as a smooth function. The paper demonstrates that the regulation error can be suppressed effectively even if the correlation of random noises is relatively weak. The regulation error is suppressed by the double effects of the Laplacian and noise correlation. The traces of covariance operators are found for several categories of the domain noises and for the boundary noises. A similar trace function in general settings satisfies a Kolmogorov equation in infinitely many state variables. The solution for the Kolmogorov equation is simplified to a form that makes numerical treatment possible. The regulation errors induced by white noise are compared with the errors induced by coloured noise in the numerical analysis.