Parameters optimization for exponentially weighted moving average control chart using generalized regression neural network

As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was introduced for optimal design of EWMA and multivariate EWMA （MEWMA） control charts, in which the optimal parameter pair （ λ, k） or （ λ, h ） was searched by using the generalized regression neural network （GRNN）. The results indicate that the optimal parameter pair can be obtained effectively by the proposed strategy for a given in-control average running length （ARLo） and shift to detect under any conditions, removing the drawback of incompleteness existing in the tables that had been reported.

Safety Impact of Average Speed Control in the UK

There is considerable safety potential in ensuring that motorists respect the speed limits. High speeds increase the number and severity of accidents. Technological development over the last 20 years has enabled the development of systems that allow automatic speed control. The first generation of automatic speed control was point-based, but in recent years a potentially more effective alternative automatic speed control method has been introduced. This method is based upon records of drivers’ average travel speed over selected sections of the road and is normally called average speed control or section control. This article discusses the different methods for automatic speed control and presents an evaluation of the safety effects of average speed control, documented through changes in speed levels and accidents before and after the implementation of average speed control at selected sites in the UK. The study demonstrates that the introduction of average speed control results in statistically significant and substantial reductions both in speed and in number of accidents. The evaluation indicates that average speed control has a higher safety effect than point-based automatic speed control.

BOUNDS ON AVERAGE CONTROLLED DIRECT EFFECTS WITH AN UNOBSERVED RESPONSE VARIABLE

This paper considers the problem of estimating the bounds on the average controlled direct effects （ACDEs） of a treatment variable on an unobserved response variable in the presence of unobserved confounders between an intermediate variable and the response variable. When the response variable is observed, Cai, et al.（2008） derived the formulas for the sharp bounds on the ACDEs. When the response variable is unobserved, the authors propose a graphical criterion for selecting variables affected by the response variable to derive the formulas for the bounds on the ACDEs, which is an extension of the result of Kuroki（2005） to ACDEs. The results enable us not only to judge from the graph structure whether the bounds on the ACDEs can be expressed through observed variables when the response variable is unobserved, but also to provide their formulas when the answer is affirmative.

Sliding mode control of reaction flywheel-based brushless DC motor with buck converter

Reaction flywheel is a significant actuator for satellites＇ attitude control. To improve output torque and rotational speed accuracy for reaction flywheel, this paper reviews the modeling and control approaches of DC-DC converters and presents an application of the variable structure system theory with associated sliding regimes. Firstly, the topology of reaction flywheel is constructed. The small signal linearization process for a buck converter is illustrated. Then, based on the state averaging models and reaching qualification expressed by the Lee derivative, the general results of the sliding mode control （SMC） are analyzed. The analytical equivalent control laws for reaction flywheel are deduced detailedly by selecting various sliding surfaces at electromotion, energy consumption braking, reverse connection braking stages. Finally, numerical and experimental examples are presented for illustrative purposes. The results demonstrate that favorable agreement is established between the simulations and experiments. The proposed control strategy achieves preferable rotational speed regulation, strong rejection of modest disturbances, and high-precision output torque and rotational speed tracking abilities.

Regional averaged controllability for hyperbolic parameter dependent systems

The purpose of this paper is to extend the notion of regional controllability for hyperbolic parameter dependent systems.The key idea is the characterization of the averaged regional control with minimal energy.This control steers the state average(with respect to such a parameter)towards the desired state only on a given part of the system evolution domain.In this paper,we give the precis definition and the properties of this new concept.Then,we use an approach based on an extension of the Hilbert uniqueness method devoted to the calculation of the control in two different cases:zone control and pointwise control.

A single-inductor dual-output switching converter with average current mode control

An integrated single-inductor dual-output （SIDO） switching DC-DC converter is presented. The outputs are specified with 1.2 V/400 mA and 1.8 V/200 mA. A decoupling small signal model is proposed to analyze the multi-loop system and to design the on-chip compensators. An average current control mode is introduced with lossless, continuous current detection. The converter has been fabricated in a 0.25μm 2P4M CMOS process. The power efficiency is 86% at a total output power of 840 mW while the output ripples are about 40 mV at an oscillator frequency of 600 kHz.

CARMA-model-based j-step-ahead prediction for MIMO systems

The single-input single-output(SISO)j-step-ahead predictor for generalized predictive control(GPC)controllers was traditionally derived using the polynomial approach through the Diophantine equations.An equivalent version of the predictor in a state-space form is available in the literature.In this paper,a z-domain analysis of the multiple input multiple output(MIMO)extension of the state-space predictor is carried out,and then an MIMO j-step-ahead predictor in polynomial form based on the controlled auto-regressive moving average model is derived.The predictor enables us to simplify the GPC algorithm design for multivariable systems.In the SISO case the predictor is just the traditional GPC predictor,therefore this paper gives rigorous proof of the equivalence between the traditional GPC predictor and the state-space predictor.