原料预热温度的模糊PID-神经元控制

针对具有不确定性、大纯滞后的催化裂化反应再生装置原料预热温度控制,提出了一种模糊PID-神经元控制方法.从介绍催化裂化反应再生装置原料预热被控对象的建模、神经元非模型控制和公式化的模糊控制方法人手,建立了模糊PID-神经元控制系统,设计了模糊神经元混合控制器,并使用神经元来在线调整模糊PID控制器的模糊规则.仿真实验结果表明所提出的模糊PID-神经元控制方法具有强鲁棒性,能有效控制具有大纯滞后和不确定性的对象.     

一种基于规则和学习算法设计的电力系统智能PID控制器

提出了一种基于规则和学习算法设计的电力系统智能ＰＩＤ控制器的设计方法。通过对固定参数电力系统ＰＩＤ控制器性能的研究，验证并获得了一些关于电力系统电压和稳定性控制协调与鲁棒性的结论。在此基础上，研制出一种智能ＰＩＤ控制器，它由基于规则的开关控制和基于学习控制的算法组成。在单机无穷大电力系统中应用的非线性仿真表明，这种智能ＰＩＤ控制器满足电力系统电压和稳定性协调控制的要求，且具有较强的鲁棒性。     

适用于非线性对象的模糊-神经元控制方法

针对具有严重非线性的受控对象，提出了一种模糊-神经元控制方法。该方法将模糊PID控制器与神经元控制器相结合，用于改善控制器控制非线性对象的性能，以误差、误差变化率及设定值的变化来自调整神经元控制器增益，提高了控制系统的响应速度和鲁棒性。将所提出控制方法用于pH中和过程控制，仿真实验结果表明，该方法具有满意的控制品质及很强的适应性。     

DISCRETIZING CONTINUOUS‐TIME CONTROLLERS WITH FUZZY LOGIC SYSTEMS AND ITS STABILITY ANALYSIS

In this paper, a new method, applying the fuzzy logic system, is proposed to discretize the continuous‐time controller in computer‐controlled systems. All the continuous‐time controllers can be reconstructed by the proposed method under the Sampling Theorem. That is, the fuzzy logic systems are used to add nonlinearity and to approximate smooth functions. Hence, the proposed controller is a new smooth controller that can replace the original controller, independent of the sampling time under the Sampling Theorem. Consequently, the proposed controller not only can discretize the continuous‐time controllers, but also can tolerate a wider range of sampling time uncertainty. Besides, the input‐output stability is proposed for discretizing the continuous‐time controller of the fuzzy logic systems. Finally, computer simulation shows that the proposed method can easily reconstructthe continuous‐time controller and has very good robustness for different sampling times.     

现代控制理论在电厂中央空调系统中的应用研究

本课题针对电厂2X600MW机组电厂中央空调系统的典型子系统一电子设备间空调系统为研究对象,采用现代控制理论模糊关系辨识方法,建立了电子设备间温度控制系统的模糊模型。设计了它的模糊控制器,综合模糊控制和传统PID控制的优劣,提出了一种电子设备间温度控制采用模糊一PID的控制方案。     

Multi‐Variable Direct Self‐Organizing Fuzzy Neural Network Control for Wastewater Treatment Process

A multi‐variable direct self‐organizing fuzzy neural network control (M‐DSNNC) method is proposed for the multi‐variable control of the wastewater treatment process (WWTP). In this paper, the proposed control system is an essential multi‐variable control method for the WWTP. No exact plant model is required, which avoids the difficulty of establishing the mathematics model of WWTP. The M‐DSNNC system is comprised of a fuzzy neural network controller and a compensation controller. The fuzzy neural network is used for approximating the ideal control law under a general nonlinear system. Moreover, the neural network is designed in a self‐organizing mode to adapt the uncertainty environment. Simulation results, based on the international benchmark simulation model No.1 (BSM1), demonstrate that the control accuracy is improved under the proposed M‐DSNNC method, and the controller has a much stronger decoupling ability.     

交流励磁发电机智能模糊励磁控制研究

在深入分析和研究交流励磁发电机的基础上,结合模糊控制不依赖对象模型、控制迅速等优点,针对交流励磁发电机提出了一种带有智能模糊控制器的新颖解耦励磁控制方法.通过模糊控制理论建立了相应的励磁控制模型,并以双PWM变换器为基础设计了智能模糊励磁控制器;通过仿真分析验证了智能模糊励磁控制器提高了系统的运行性能,以及智能模糊控制方法的正确性和有效性.     

Decoupled fuzzy sliding-mode control

A decoupled fuzzy sliding-mode controller design is proposed. The decoupled method provides a simple way to achieve asymptotic stability for a class of fourth-order nonlinear systems with only five fuzzy control rules. The ideas behind the controller are as follows. First, decouple the whole system into two second-order systems such that each subsystem has a separate control target expressed in terms of a sliding surface. Then, information from the secondary target conditions the main target, which, in turn, generates a control action to make both subsystems move toward their sliding surface, respectively. A closely related fuzzy controller to the sliding-mode controller is also presented to show the theoretical aspect of the fuzzy approach in which the characteristics of fuzzy sets are determined analytically to ensure the stability and robustness of the fuzzy controller. Finally, the decoupled sliding-mode control (SMC) is used to control three highly nonlinear systems and confirms the validity of the proposed approach     

模糊整定PID控制在水电机组中应用研究

传统的水电机组PID控制不能根据系统的动态过程自动调整控制参数,系统在工况变化时很难达到较好的控制效果。本文提出一种改进的智能自适应模糊PID控制系统,模糊推理输出在线修改PID参数,并探讨了如何整定PID参数以达到最优控制效果。仿真实验表明这是一种有效的控制策略,尤其在启停机过程及负载扰动过程较传统PID控制具有更好的鲁棒性和稳定性。     

Nonlinear inversion-based output tracking control of a boiler-turbine unit

The capability to perform fast load-following has been an important issue in the power industry. An output tracking control system of a boiler-turbine unit is developed. The system is composed of stable inversion and feedback controller. The stable inversion is implemented as a feedforward controller to improve the load-following capability, and the feedback controller is utilized to guarantee the stability and robustness of the whole system. Loop-shaping H∞ method is used to design the feedback controller and the final controller is reduced to a multivariable PI form. The output tracking control system takes account of the multivariable, nonlinear and coupling behavior of boiler-turbine system, and the simulation tests show that the control system works well and can be widely applied.     

A nonlinear state‐feedback state‐feedforward tracking control strategy for a boiler‐turbine unit

A boiler‐turbine unit is a primary module for coal‐fired power plants, and an effective automatic control system is needed for the boiler‐turbine unit to track the load changes with the drum water level kept within an acceptable range. The aim of this paper is to develop a nonlinear tracking controller for the Bell‐Åström boiler‐turbine unit. A Takagi‐Sugeno fuzzy control system is introduced for the nonlinear modeling of the Bell‐Åström boiler‐turbine unit. Based on the Takagi‐Sugeno fuzzy models, a nonlinear tracking controller is developed, and the proposed control law is comprised of a state‐feedforward term and a state‐feedback term. The stability of the closed‐loop control system is analyzed on the basis of Lyapunov stability theory via the linear matrix inequality approach and Schur complement. Moreover, model uncertainties are also considered, and it is proved that with the proposed control law the tracking error converges to zero. To assess the performance of the proposed nonlinear state‐feedback state‐feedforward control strategy, a nonlinear model predictive control strategy and a linear strategy are presented as comparisons. The effectiveness and the advantages of the proposed nonlinear state‐feedback state‐feedforward control strategy are demonstrated by simulations.     

多变量PID控制器的在线自整定

本文研究具有ＰＩＤ结构反馈控制器的多变量控制系统的参数自整定，提出了具有校正因子的多变换ＰＩＤ控制算法及在线自动调整校正因子的专家自整定方法，将该方法用于火电单元机组负荷控制系统自整定仿真研究，结果表明系统具有好的完整性和鲁棒性。     

The velocity control of an electro‐hydraulic displacement‐controlled system using adaptive fuzzy controller with self‐tuning fuzzy sliding mode compensation

Hydraulic servo control systems have been used widely in industry. Within the realm of hydraulic control systems, conventional hydraulic valve‐controlled systems have higher response and lower energy efficiency, whereas hydraulic displacement‐controlled servo systems have higher energy efficiency. This paper aims to investigate the velocity control performance of an electro‐hydraulic displacement‐controlled system (EHDCS), where the controlled hydraulic cylinder is altered by a variable displacement axial piston pump to achieve velocity control. For that, a novel adaptive fuzzy controller with self‐tuning fuzzy sliding‐mode compensation (AFC‐STFSMC) is proposed for velocity control in EHDCS. The AFC‐STFSMC approach combining adaptive fuzzy control and the self‐tuning fuzzy sliding‐mode control scheme, has the advantages of the capability of automatically adjusting the fuzzy rules and of reducing the fuzzy rules. The proposed AFC‐STFSMC scheme can design the sliding‐mode controller with no requirement on the system dynamic model, and it can be free of chattering, thereby providing stable tracking control performance and robustness against uncertainties. Moreover, the stability of the proposed scheme via the Lyapunov method is proven. Therefore, the velocity control of EHDCS controlled by AFC‐STFSMC is implemented and verified experimentally in different velocity targets and loading conditions. The experimental results show that the proposed AFC‐STFSMC method can achieve good velocity control performance and robustness in EHDCS with regard to parameter variations and external disturbance. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Quasi sliding mode‐based single input fuzzy self‐tuning decoupled fuzzy PI control for robot manipulators with uncertainty

This paper presents a robust adaptive control strategy for robot manipulators, based on the coupling of the fuzzy logic control with the so‐called sliding mode control (SMC) approach. The motivation for using SMC in robotics mainly relies on its appreciable features. However, the drawbacks of the conventional SMC, such as chattering effect and required a priori knowledge of the bounds of uncertainties can be destructive. In this paper, these problems are suitably circumvented by adopting a reduced rule base single input fuzzy self tuning decoupled fuzzy proportional integral sliding mode control approach. In this new approach a decoupled fuzzy proportional integral control is used and a reduced rule base single input fuzzy self‐tuning controller as a supervisory fuzzy system is added to adaptively tune the output control gain of the decoupled fuzzy proportional integral control. Moreover, it is proved that the fuzzy control surface of the single‐input fuzzy rule base is very close to the input/output relation of a straight line. Therefore, a varying output gain decoupled fuzzy proportional integral sliding mode control approach using an approximate line equation is then proposed. The stability of the system is guaranteed in the sense of the Lyapunov theorem. Simulations using the dynamic model of a 3DOF planar manipulator with uncertainties show the effectiveness of the approach in high speed trajectory tracking problems. The simulation results that are compared with the results of conventional SMC indicate that the control performance of the robot system is satisfactory and the proposed approach can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances. Copyright © 2011 John Wiley & Sons, Ltd.     

Robust grid‐oriented control of high voltage DC links embedded in an AC transmission system

Several studies have shown that the way to design controllers for the high‐voltage direct current (HVDC) links impacts the transient behavior of the electric system in which the latter are inserted. This can be exploited to improve the performances of the stability of the power system. In this paper, a robust multivariable control design for the converters of an HVDC link is proposed. It is based on the coordination of the control actions of the HVDC converters and the use of a control model. The latter takes into consideration, in addition to the dynamics that mostly impact the stability of the neighbor zone of the HVDC link, several cases of faulted situations modeled as uncertainties. An H_∞ controller allowed us to achieve robustness against such uncertainties. The new controller is tested in comparison with the standard vector control and an optimal linear quadratic controller using the EUROSTAG simulation software (Tractebel Engineering, Brussels, Belgium and Réseau de Transport d'Electricité (RTE) ‐ France) on both academic and realistic large‐scale power systems. Copyright © 2015 John Wiley & Sons, Ltd.     

海水淡化温度模糊-PID控制的设计与实现

针对海水淡化主体温度控制过程复杂、非线性、参数时变和滞后性的特点,采用模糊控制理论和PID控制理论相结合方法,综合PID控制具有算法简单、可靠性高和稳态误差小的优点和模糊控制具有灵活性和鲁棒性好的优点,研究和设计模糊-PID温度控制器,实现海水淡化主体的稳定控制.     

Stable and robust fuzzy control for uncertain nonlinear systems

Presents the stability and robustness analysis for multivariable fuzzy control systems subject to parameter uncertainties based on a single-grid-point (SGP) approach. To perform the analysis, we represent a multivariable nonlinear system using a TS-fuzzy plant model. Three design approaches of fuzzy controllers are introduced to close the feedback loop. By estimating the matrix measures of the system parameters and parameter uncertainties, stability and robustness conditions for different cases are derived. Application examples are given to show the design procedures and the merits of the proposed fuzzy controller     

一种多变量模糊神经网络解耦控制器的设计

为提高多变量、非线性和强耦合系统的动态特性和解耦能力,根据解耦原理和神经网络思想,提出一种两级串联结构的自适应模糊神经网络解耦控制器.前级是基于智能权函数规则的自调整模糊控制器,后级是基于动态耦合特性的自适应神经网络解耦控制器.同时从理论上证明了学习算法的收敛性.仿真实例表明,所提出的解耦控制器具有良好的鲁棒性和自适应解耦能力,是解决多变量、非线性和强耦合问题的一种简便有效的控制算法.     

A multivariable predictive fuzzy PID control system

In this paper, a novel multivariable predictive fuzzy-proportional-integral-derivative (F-PID) control system is developed by incorporating the fuzzy and PID control approaches into the predictive control framework. The developed control system has two main units referred as adaptation and application parts. The adaptation part consists of a F-PID controller and a fuzzy predictor. The incremental control actions are generated by the F-PID controller. The controller parameters are adjusted with the predictive control approach. The fuzzy predictor provides the multi-step ahead predictions of the plant outputs. Therefore, the F-PID controller parameters are adjusted by minimizing the errors between the predicted plant outputs and reference trajectories over the prediction horizon. The fuzzy predictor is trained with an on-line training procedure in order to adapt the changes in the plant dynamics and improve the prediction accuracy. The Levenberg–Marquardt (LM) optimization method with a trust region approach is used to adjust both the controller and predictor fuzzy systems parameters. In the application part, an identical F-PID controller of the adaptation part is used to control the actual plant. The adjusted parameter values are transferred to this identical controller at each time step. The performance of the proposed control system is tested for both single-input single-output (SISO) and multiple-input multiple-output (MIMO) nonlinear control problems. The adaptation, robustness to noise, disturbance rejection properties together with the tracking performances are examined in the simulations.     

某机载雷达智能环境控制器模糊算法设计

为了提高某机载雷达环境控制系统控制品质,设计了一种基于PID控制与模糊控制相结合的智能控制器。文章介绍了该智能控制器的基本原理、系统组成,详细论述了温度控制算法。该算法具有更大的灵活性、更快的响应速度、抗干扰性强和鲁棒性高的优点,特别适用于非线性、时变和大滞后的控制系统。试验表明,采用该算法的环境控制系统,具有良好的控制性能,对机载设备冷却或加热取得了满意的效果。