Exponential smoothing: The state of the art

This paper is a critical review of exponential smoothing since the original work by Brown and Holt in the 1950s. Exponential smoothing is based on a pragmatic approach to forecasting which is shared in this review. The aim is to develop state-of-the-art guidelines for application of the exponential smoothing methodology. The first part of the paper discusses the class of relatively simple models which rely on the Holt-Winters procedure for seasonal adjustment of the data. Next, we review general exponential smoothing (GES), which uses Fourier functions of time to model seasonality. The research is reviewed according to the following questions. What are the useful properties of these models? What parameters should be used? How should the models be initialized? After the review of model-building, we turn to problems in the maintenance of forecasting systems based on exponential smoothing. Topics in the maintenance area include the use of quality control models to detect bias in the forecast errors, adaptive parameters to improve the response to structural changes in the time series, and two-stage forecasting, whereby we use a model of the errors or some other model of the data to improve our initial forecasts. Some of the major conclusions: the parameter ranges and starting values typically used in practice are arbitrary and may detract from accuracy. The empirical evidence favours Holt's model for trends over that of Brown. A linear trend should be damped at long horizons. The empirical evidence favours the Holt-Winters approach to seasonal data over GES. It is difficult to justify GES in standard form–the equivalent ARIMA model is simpler and more efficient. The cumulative sum of the errors appears to be the most practical forecast monitoring device. There is no evidence that adaptive parameters improve forecast accuracy. In fact, the reverse may be true.     

ADAPTIVE FORECAST AND CONTROL OF THE MARKET ECONOMIC SYSTEM WITH FUZZY INPUTS

In this paper, the adaptive forecast and control of the market economic system with fuzzy inputs is discussed. A new method which is adapted for the adaptive forecast and control of this kind of system is introduced. Through a living example the better result is explained concretly.     

The teachers/practitioners corner comparative analysis of load forecasting techniques at a southern utility

The prime directive of any regulated electric utility is to provide adequate and reliable electricity supplies to the consuming public at reasonable cost. This requires the continual addition of new generating plants which is based on a long term forecast of energy and peak demand. This study documents the forecasting process used at a southern utility and compares the accuracy of their models to that produced using Holt's exponential smoothing and generalized adoptive filtering.     

Intelligent coordinated control of power-plant main steam pressure and power output

An intelligent coordinated control strategy has been proposed and successfully applied to a 300MW boiler-turbine unit i. e. Unit 1 of Yuanbaoshan power plant in China. Load following operation of coal-fired boiler-turbine unit in the power plant leads to changes in operating points which result in nonlinear variations of the plant variables and parameters. For the variation of operating condition and slowly varying dynamics, an intelligent control scheme has been developed by combining fuzzy self-tuning with adaptive control and auto-tuning techniques. As there exist strong couplings between control loops of main steam pressure and power output in the unit, a new design for static decoupler aimed at decoupling for setpoints and unmeasured pulverized coal disturbance of the system at the same time is presented. Satisfactory industrial application results show that such a control system has enhanced adaptability and robustness to the complex process, and better control performance and high economic benefi     

钢厂废水处理中pH的控制

给出钢厂废水处理的流程和原理，针对钢厂废水处理具有量大、时变、非线性、大滞后等特点，提出采用模糊自适应PID控制的方法，进行废水处理中关键环节pH的控制．常规PID控制中整定比例、积分、微分3个控制参数是难点，为此在常规PID算法基础上引入模糊推理，根据pH的偏差值和偏差变化率实时调整3个控制参数．经比较可以看出，该方法在pH控制中具有较理想的控制效果．     

自适应核时频分布在抑制交叉项中的应用

分析了固定核函数时频分布在抑制交叉项方面的局限性以及基于信号特征的自适应时频分布对时频分辨率的改善。通过对基于信号特征的径向高斯核时频分布进行改进,提出了一种基于信号特征的自适应核时频分布的改进算法。该算法采用短时模糊函数和随时间变化的自适应核,能够在时频分布中区分出多分量信号的细节部分。仿真结果表明,该分布具有较高的时频分辨率,且无交叉项干扰。同时它还适合分析长时间信号和实现在线信号处理。     

MIMO Adaptive Control System for Human Arterial Blood Pressure by Drug

This paper presents modeling and simulation of a multi-input multi-output (MIMO) adaptive control system (ACS) for human arterial blood pressure (HABP) by multiple drug inputs -infusion speed (IS) control of inotropic agent (IA) and vasoactive agent (VA). The MIMO ACS is able to choose the most appropriate IS of IA and VA at good IS in order to maintain the aortic pressure (AOP) and central vain pressure (CAP) at desired levels, and at the same time to increase the cardiac output (CO).This ACS simulation consists of 3 parts: the system model (SM), the identifier (ID), and the explicit multivariable self-turning controller (MSC). The SM is a 2-input 2-output bilinear model with nonwhite system noise. The variable ID is capable of estimating the variable onset delay model (BNVD). The ID is capable of estimating the variable onset delay online by compressing the value in gaining the unbiased parameter estimation with an improved generalized least-squares (LS) algorithm. The MSC employs the minimum variance one-step-ahead control law. These three parts make a closed-loop control system successfully for heart disease patients during and after the operation.     

多干扰情况下的自适应阵列设计

本文由多干扰情况下自适应阵的 SINR 表达式,研究了阵列优化设计问题。此问题不同于单干扰情况,我们将证明,单干扰时的 SINR 不随阵元增加而下降,但多干扰条件下此结论不成立,阵元的选择和阵元相对位置的不当都可能导致 SINR下降,因此,研究多干扰时的阵列优化设计是很必要的。本文中,我们还给出了设计最优阵的条件,包括阵元选取和阵元位置确定。     

基于HPA特性曲线拟合的自适应预失真技术

提出了一种用于正交频分复用(OFDM)系统中补偿由大功率放大器引起的非线性失真的基带自适应预失真方法。自适应预失真器是基于对大功率放大器的非线性特性进行分段估计,由曲线拟合逐段取逆变换来训练大功率放大器的预失真器的非线性参数,以达到预是真补偿的目的。计算机仿真结果表明,该方法具有收敛速度快、需要动态存储器(RAM)少、补偿效果好等特点。     

基于高阶微分滑模面的不确定飞机控制系统自适应滑模控制

飞机控制系统作为典型的多输入多输出(MIMO)非线性系统,具有很强的耦合性和不确定性,导致控制难度大幅度提高。针对这一情况,研究了一类飞机姿态控制系统的跟踪控制问题。首先,将飞机姿态控制系统进行坐标变换,并且考虑输入不确定性的存在情况,提出了一种新的高阶微分滑模面,证明了滑模面的稳定性,然后,基于此高阶微分滑模面和神经网络的逼近能力,设计了光滑的自适应滑模控制器。基于Lyapunov稳定性理论,证明了所设计的控制器既保证了飞机姿态控制系统具有很好的跟踪性能,又避免了传统滑模控制器抖振现象的出现。最后,通过仿真验证了所设计控制器的有效性。与传统的滑模控制器对比,所设计的控制器是光滑的,在实际飞机姿态控制领域中具有很好的应用前景。