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.

Second order sliding mode control with back stepping approach for moving mass spinning missiles

An attitude controller using the second order sliding mode control methodology with a backstepping approach（SOSMCB）is designed and implemented for a spinning missile with two internal moving mass blocks.The system consists of a rigid body and two radial internal moving mass blocks and its mathematical model is established based on Newtonian mechanics.The control scheme integrates a second order sliding mode control algorithm into the last step of the backstepping approach,and its stability is proved by means of a Lyapunov function.The performance of the controller is demonstrated by numerical simulations,the results show that the attitude controller is stable and effective.

NEW METHOD FOR VIBRATION MEASUREMENT AND CONTROL OF MOVING WIRE

On-line measurement and control method of moving wire vibration are developed. The response measurement of the wire is indirectly accomplished by 'vibration transfer method ' and active con- trol is carried out on the vibration receiving body by piezoelectric ceramics. The fundamental princi- ples of measurement and control are stated and experimental results are presented.

A remining technology of underground coal gasification at Zhongliangshan Coal Mine

The field trail used a mixture of steam and air with various levels of oxygen en- richment.Steady conditions were achieved in the field trail which produced high quality hydrogen-enriched syngas.To understand and optimize the UCG process,a simplified heat and mass transfer model was presented,providing a predictive tool for temperature and the major constituents of the syngas production.The model is compared with the field trail measurements for air and two levels of oxygen enrichment,showing reasonable agreement for the channel temperature and product syngas concentration profile.

Smoke movement in a tunnel of a running metro train on fire

Research on the distribution of smoke in tunnels is significant for the fire emergency rescue after an operating metro train catches fire. A dynamic grid technique was adopted to research the law of smoke flow diffusion inside the tunnel when the bottom of a metro train was on fire and to compare the effect of longitudinal ventilation modes on the smoke motion when the burning train stopped. Research results show that the slipstream curves around the train obtained by numerical simulation are consistent with experimental data. When the train decelerates, the smoke flow first extends to the tail of the train. With the decrease of the train's speed, the smoke flow diffuses to the head of the train. After the train stops, the slipstream around the train formed in the process of train operation plays a leading role in the smoke diffusion in the tunnel. The smoke flow quickly diffuses to the domain in front of the train. After forward mechanical ventilation is provided, the smoke flow inside the tunnel continues to diffuse downstream. When reverse mechanical ventilation operates, the smoke in front of the train flows back rapidly and diffuses to the rear of the train.

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.