Generalized difference control of parallel streams temperatures

A furnace with multiple parallel passes and multiple burners is commonly seen in petroleum refineries. In order to maintain the furnace running in a safe, stable, and high-efficiency state it is necessary to control the outlet temperatures of the multiple passes to be the same. Due to the fact that the process of the oil heating in such furnace is nonlinear, multivariable, time varying, has serious coupling among passes, has frequent dynamic changes and a large time delay, traditional control methods have trouble in controlling these temperatures, and some advanced control methods, including predictive control, adaptive control, and robust control, are usually too complex for convenient use. In this paper, a control technique, called differences control technique (DsCT), is proposed to distribute the stream flowrates such that the stream temperatures are as identical as possible. The principle of the proposed technique is explained and demonstrated, and the results of its application to a real-life petroleum refinery furnace are also reported. The DsCT technique has the following advantages: it does not need complicated design procedures, the controller structure is simple, it is easy to apply, and it can be canonically applied to furnaces with different number of passes.     

二维直线电机平台的双神经网络前馈解耦控制

针对二维直线电机系统中的直线电机本身存在的非线性以及XY两轴之间互相影响产生的耦合对控制精度的影响,提出了一种基于前馈结构的双神经网络解耦控制方法.根据二维直线电机两轴间的耦合结构和前馈控制结构,对应搭建了双神经网络模型,设计一种双神经网络的解耦控制策略,以消除二维直线电机两轴间的非线性强耦合对系统控制精度的影响.仿真结果表明:提出的双神经网络前馈解耦控制方法的有效性,并在起始阶段的跟踪方面表现出良好的性能.     

超精密平面电机控制技术

分析了平面电机的结构及其原理,提出了相应控制技术.对平面电机的驱动力进行解耦,讨论了磁场非均匀性及磁场耦合对平面电机驱动力非线性的影响,并给出相应的补偿方法.最后给出了平面电机定子垂向对称性标定方法,提高了平面电机的定位精度.     

电火花加工智能控制系统的建模及仿真

为增强电火花加工过程的稳定性,基于模糊RBF神经网络智能控制,同时利用模糊控制的解耦性,以在电火花加工过程中统计的空载率、正常放电率、不正常放电率(包括电弧及短路放电)、相对于脉冲周期和他抬刀周期的正常放电率为输入,设计了以伺服参考电压、脉冲间隔和抬刀周期为输出的电火花加工模糊RBF神经控制器,并利用MATLAB对设计的模糊RBF神经控制器进行了建模及仿真.仿真结果表明了模糊RBF神经网络控制系统在电火花加工中对于稳定加工状态的有效性.     

Disturbance decoupled fault reconstruction using sliding mode observers

This paper investigates and presents conditions that guarantee disturbance decoupled fault reconstruction using sliding mode observers, which are less stringent than those of previous work, and show that disturbance reconstruction is not necessary. An aircraft model validates the ideas proposed in this paper. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

IEEE1451智能传感器多传感信息自校正方法研究

针对多传感信息耦合问题,基于IEEE1451标准,提出了一种通用的多传感信息自校正模型。模型根据传感元件输出信号额定特征,从信号幅度、变化趋势等方面,实现对传感器的故障判断和自免疫处理;然后基于多传感信息插值解耦数学原理,建立了基于特定TEDS格式的校正引擎,通过将标定点数据以矩阵表格形式输入TEDS中来实现解耦校正。试验研究表明:通过TEDS解耦校正引擎,可实现对多传感耦合信息的良好校正补偿,提高检测准确度,在解耦校正的前端引入传感元件的自评估技术,可有效提高智能传感器自校正的可靠性。     

Tuning of PI controllers with one-way decoupling in 2×2 MIMO systems based on finite frequency response data

A method of tuning for PI controllers with one-way lead/lag decoupling tuning is demonstrated for 2×2 input-output systems, based on finite frequency response data. The frequency response estimates are obtained from closed loop tests using an identification technique based on bandpass filters. The open-loop frequency response is calculated and used to tune PI controllers and to fit lead-lag compensators for decoupling by weighted least-squares. Separate optimization of the PI controllers and the lead-lag compensator is preferred. The tuning takes into account violations of desired multivariable robustness criteria. The method is illustrated by application to a paper machine headbox simulation and by experiments in distillation column temperature control.     

基于RBF和BP神经网络的DTG全解耦方法比较

为了提高动调陀螺仪（DTG）的精度,需要对DTG的解耦方法进行研究。BP神经网络解耦方法虽然可以达到DTG的全解耦目的,但是与传统的解耦方法相比仍有一些不足,如学习过程较慢,隐含层也很难确定、泛化能力较差等。因此,需要探求更好的解耦方法。通过对RBF神经网络与BP神经网络相比较,得到新的解耦方法。最后通过仿真实验,验证了RBF神经网络的解耦速度比BP神经网络快,并且准确性要高。     

A method for optimal control and filtering of multitime-scale linear singularly-perturbed stochastic systems

In this paper we introduce a transformation for the exact closed-loop decomposition of the optimal Kalman filter and the linear quadratic optimal controller of multi time scale continuous-time, linear, singularly-perturbed stochastic systems. The solution of the corresponding algebraic regulator and filter Riccati equations are obtained in terms of solutions of reduced-order subsystem, algebraic, Riccati equations corresponding to the system time scales. We have also obtained N completely independent reduced-order subsystem Kalman filters working in parallel in different time scales. This allows parallel processing of information with lower-order, different rates Kalman filters consistent with the system time scales.     

板宽板厚多变量系统的自抗扰控制

针对精轧板宽板厚多变量系统具有强耦合、不确定性、大时滞、干扰因素多、非线性等特点,应用ADRC静态解耦和ESO动态解耦技术,给出了一种全新的多变量ADRC设计及实现方案。解耦后各通道的ADRC可分别按常规的单变量时滞系统来设计。为满足快速性要求,各通道的ADRC改由ESO、NF两部分组成,而且这两部分没有采用常规的非线性函数,而是改用线性函数。改进后的ADRC由Simulink编程实现。仿真结果表明这种方法的有效性。