A self-tuning fuzzy controller for a class of multi-input multi-output nonlinear systems

This paper presents a systematic design procedure of a multivariable fuzzy controller for a general Multi-Input Multi-Output (MIMO) nonlinear system with an input-output monotonic relationship or a piecewise monotonic relationship for each input-output pair. Firstly, the system is modeled as a Fuzzy Basis Function Network (FBFN) and its Relative Gain Array (RGA) is calculated based on the obtained fuzzy model. The proposed multivariable fuzzy controller is constructed with two orthogonal fuzzy control engines. The horizontal fuzzy control engine for each system input-output pair has a hierarchical structure to update the control parameters online and compensate for unknown system variations. The perpendicular fuzzy control engine is designed based on the system RGA to eliminate the multivariable interaction effect. The resultant closed-loop fuzzy control system is proved to be passive stable as long as the augmented open-loop system is input-output passive. Two sets of simulation examples demonstrate that the proposed fuzzy control strategy can be a promising way in controlling multivariable nonlinear systems with unknown system uncertainties and time-varying parameters.     

SIMATIC PCS7在燃煤角管式锅炉中的应用

从3×35T／h燃煤角管式蒸汽锅炉的生产工艺、控制要求入手,介绍了西门子公司PCS7控制系统在该类装置上的应用,并详细阐述了生产控制要求所转换为的系统功能实现及PCS7系统在该类项目上的应用。     

An algorithm for non-linear space—Time nuclear reactor control

A novel multivariable control algorithm for non-linear space-time nuclear reactor dynamics is proposed in this paper. The multivariable control algorithm is based on a mathematical model of the nuclear reactor which includes: a single energy group of neutrons, delayed neutron precursors, iodine, xenon and thermal-hydraulic feedback. The multivariable control algorithm is composed of non-linear time-varying feedforward and feedback control signals, a reference model of the nuclear reactor and a dynamic observer. The non-linear proportional plus integral feedback controller forces the nuclear reactor to follow the response of the reference model. The dynamic observer estimates the unmeasurable state variables. The feedforward and feedback control signals are determined in a novel approach by specifying the form of the closed-loop response of the neutron density variables. By virtue of the multivariable control algorithm the closed-loop differential equations are linear and time-varying. A linear stability analysis for base-load and load-cycle operation indicates that the closed-loop system is stable provided that the thermal-hydraulic subsystem is inherently stable. The simulated dynamic response indicates that the multivariable control algorithm provides excellent response characteristics.     

管控一体化在卷烟厂动力车间锅炉房的应用

以卷烟厂动力车间锅炉房多台燃煤锅炉为例,提出了从底层仪表和电器设备到上层信息管理系统的管控一体化实施方案。结果表明:保证了锅炉的稳定、安全和经济运行,达到了预期的目的,受到用户及相关部门的好评。     

An approach to multivariable combustion control design

In this paper, an approach to multivariable combustion control design within the Individual Channel Design (ICD) framework for analysis and control design is presented. ICD is a framework which involves an interplay between customer specification, uncertain plant characteristics, and the multivariable feed-back design itself. Established multivariable methods and process engineering knowledge can be incorporated or evaluated within the ICD framework. The combustion control has been designed and evaluated with a computer simulation of both a linearized model and a nonlinear model of the closed-loop system. The ICD multivariable framework shows in a highly transparent manner, by way of simple graphical frequency response indicators, what the main possibilities and difficulties posed by a combustion process for multivariable control are, and how much trade-off between control specifications is possible. Solutions are also presented for problems such as: integrity of closed-loop control, balance of input-output channels, simple and transparent controller structure, and robustness.     

一类飞行器的多变量鲁棒控制

对一类飞行器建立了数学模型并进行了分析,使用非最小相位控制系统的智能设计方 法,设计了飞行器的多变量鲁棒控制系统.基于真实模型的控制系统仿真证实了这一设计方 法的有效性.该设计方法对航空航天控制工程具有参考意义.     

Multivariable adaptive control: A survey

Adaptive control is a control methodology capable of dealing with uncertain systems to ensure desired control performance. This paper provides an overview of some fundamental theoretical aspects and technical issues of multivariable adaptive control, and a thorough presentation of various adaptive control schemes for multi-input–multi-output systems, literature reviews on adaptive control foundations and multivariable adaptive control methods, and related technical problems. It covers some basic concepts and issues such as certainty equivalence, stability, tracking, robustness, and parameter convergence. It discusses some of the most important topics of adaptive control: plant uncertainty parametrization, stable controller adaptation, and design conditions for different adaptive control schemes. The paper also presents a detailed study of well-developed multivariable model reference adaptive control theory and design techniques. It provides an introduction to multivariable adaptive pole placement and adaptive nonlinear control, and it concludes by identifying some open research problems.     

A self-tuning regulator for multivariable systems

The controller described in this paper is designed for multivariable plants with constant, unknown parameters. The algorithm operates on-line with the a priori information about the time delay. The order of the system may be given a priori. In the case where the order of the system is unknown it can be determined by a generalized likelihood-ratio statistical test which is described in this paper. The multivariable self tuning regulator consists of the two tasks of estimation and regulation. Estimation of the input-output system model parameters is based on the least-squares principle. The control is computed to minimize the combined cost of output deviation and control energy. Asymptotic properties of the estimation are discussed. Usefulness and simplicity of this approach are illustrated by examples.     

Parameterization issues in multivariable adaptive control

This paper gives both an overview of multivariable adaptive control algorithms which have evolved to date and presents some new approaches to the design of indirect multivariable adaptive control systems. All algorithms are presented using a unified pole placement approach. Furthermore the emphasis is on parameterization issues such as: types of control structures necessary for implementation, required prior information necessary for implementation and techniques for reducing the size of the resulting parameter estimation problem.     

A multivariable MRAC scheme with application to a nonlinear aircraft model

This paper revisits the multivariable model reference adaptive control (MRAC) problem, by studying adaptive state feedback control for output tracking of multi-input multi-output (MIMO) systems. With such a control scheme, the plant-model matching conditions are much less restrictive than those for state tracking, while the controller has a simpler structure than that of an output feedback design. Such a control scheme is useful when the plant-model matching conditions for state tracking cannot be satisfied. A stable adaptive control scheme is developed based on LDS decomposition of the high-frequency gain matrix, which ensures closed-loop stability and asymptotic output tracking. A simulation study of a linearized lateral-directional dynamics model of a realistic nonlinear aircraft system model is conducted to demonstrate the scheme. This linear design based MRAC scheme is subsequently applied to a nonlinear aircraft system, and the results indicate that this linearization-based adaptive scheme can provide acceptable system performance for the nonlinear systems in a neighborhood of an operating point.     

Multivariable Intelligent Decoupling Control System and its Application

Many industrial processes have compositive complexities including multivariable, strong coupling, nonlinearity, time-variant and operating condition variations. Combining multivariable adaptive decoupling control with neural networks, this paper presents a multivariable neural network-based decoupling control algorithm. This control algorithm is integrated with distributed control technique and intelligent control technique, and a three-leveled intelligent decoupling control system consisting of basic control level, coordinating control level, and management and decision level is developed. The configuration and function of the control system are discussed in detail. This system has been successfully applied in ball mill pulverizing systems of 200MW power units, and remarkable benefits have been obtained.     

Chattering-free fuzzy variable structure control for multivariable nonlinear systems

In this paper, a fuzzy logic controller (FLC) based variable structure control (VSC) with guaranteed stability for multivariable systems is presented. It is aimed at obtaining an improved performance of nonlinear multivariable systems. The main contribution of this work is firstly developing a generic matrix formulation of the FLC-VSC algorithm for nonlinear multivariable systems, with a special attention to non-zero final state. Secondly, ensuring the global stability of the controlled system. The multivariable nonlinear system is represented by T-S fuzzy model. The identification of the T-S model parameters has been improved using the well known weighting parameters approach to optimize local and global approximation and modeling capability of T-S fuzzy model. The main problem encountered is that T-S identification method cannot be applied when the membership functions (MFs) are overlapped by pairs. This in turn restricts the application of the T-S method because this type of membership function has been widely used in control applications. In order to overcome the chattering problem a switching function is added as an additional fuzzy variable and will be introduced in the premise part of the fuzzy rules together with the state variables. A two-link robot system and a mixing thermal system are chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of proposed FLC-VSC method.     

Multivariable Intelligent Decoupling Control System and its Application

Many industrial processes have compositive complexities including multivariable, strong coupling, nonlinearity, time-variant and operating condition variations. Combining multivariable adaptive decoupling control with neural networks, this paper presents a multivariable neural network-based decoupling control algorithm. This control algorithm is integrated with distributed control technique and intelligent control technique, and a three-leveled intelligent decoupling control system consisting of basic control level, coordinating control level, and management and decision level is developed. The configuration and function of the control system are discussed in detail. This system has been successfully applied in ball mill pulverizing systems of 200MW power units, and remarkable benefits have been obtained.     

基于CAN总线的锅炉控制系统的设计

本文针对某厂锅炉（50t/h）改造项目,设计了一套基于CAN总线的锅炉控制系统。给出了系统的硬件结构及软件。此系统能够进行对锅炉工况实时监测与优化控制,人机对话界面友好,操作方便,提高了锅炉运行的稳定性、安全性。     

焦炉加热智能控制系统的研究与应用

焦炉是具有大时滞、强非线性、多变量耦合、变参数的复杂对象，直行温度受多种因 素的影响，采用常规的控制方法难以将直行温度控制到要求的精度范围内．焦炉生产过程既 受连续时间信号驱动，又受离散事件信号驱动，本文将焦炉及其操作过程作为一类混杂系统 ，研究并开发了焦炉加热智能控制系统．系统采用神经网络建模、多变量模糊控制、专家控 制和预测控制等多种算法，构造了切换系统模型，在北京炼焦化学厂投入生产运行后，取得 良好控制效果．该系统对提高焦炭质量，降低能耗和延长炉体使用寿命都有重要的意义．     

基于改进GNG算法的燃煤锅炉数据动态特征分析与控制

数据动态特征分析与控制技术是一种重要的数据挖掘手段,燃煤锅炉数据具有明显时序性和漂移性等特点,针对目前数据跟踪与监督算法大多缺乏动态性、实时性和稳定性等问题,设计一种基于改进生长神经气模型(GNG)的自适应聚类模型,建立基于概率、范围搜寻、节点平均距离的节点生成、删除机制,实现对漂移数据实时监控.最后以燃煤锅炉动态数据为分析对象进行实验,实验结果表明该模型和算法对动态漂移数据的实时跟踪能力更强,能对燃煤锅炉动态数据进行准确、有效的监督和控制.     

Adaptive dynamic surface control for linear multivariable systems

In this paper, an output-feedback adaptive control is presented for linear time-invariant multivariable plants. By using the dynamic surface control technique, it is shown that the explosion of complexity problem in multivariable backstepping design can be eliminated. The proposed scheme has the following features: (1) The L_∞ performance of the system’s tracking error can be guaranteed, (2) it has least number of updated parameters in comparison with other multivariable adaptive schemes, and (3) the adaptive law is necessary only at the first design step, which significantly reduces the design procedure. Simulation results are presented to demonstrate the effectiveness of the proposed scheme.     

多变量V规范型解耦控制系统设计

本文提出多变量系统部分变量前置V型解耦,部分变量后置V型解耦的设计方法。并就某电厂三输入、三输出磨煤机系统,设计解耦控制系统,给出了仿真结果。     

基于模糊内模控制的球磨机系统的研究

球磨机系统具有多变量、强耦合、长时滞以及生产工况变化大等特点,采用常规控制策略很难达到控制目标。针对该问题,文章提出了一种基于模糊内模控制的球磨机系统的设计方案,分析了球磨机工作原理,建立了其数学模型,详细介绍了球磨机系统的解耦分析,最后给出了球磨机模糊内模控制器的设计方法。仿真结果表明,基于模糊内模控制的球磨机系统具有良好的解耦能力,鲁棒性强,能够较好地解决球磨机系统的时变性、耦合性和延迟性问题,具有一定的工程应用价值。     

一类确定性多变量非线性系统的自适应控制

本文研究了可用确定性多变量Hammerstein模型描述的一类多变量非线性系统的自适 应控制,基于对一步最优控制律所产生的闭环系统的稳定性条件的分析,提出了一种适用于线 性部分为具有任意关联矩阵的非最小相位系统的简单次优控制律及相应的直接自适应控制算 法,并证明了算法的全局收敛性.