APPLICATION OF A REAL-TIME CONTROL STRATEGY FOR BAYESIAN BELIEF NETWORKS TO SHIP CLASSIFICATION PROBLEM SOLVING

Author(s):  
S.A. MUSMAN ◽  
L.W. CHANG ◽  
L.B. BOOKER

Many classification problems must be performed in a timely or time constrained manner. For this reason, the generation of control schemes which are capable of responding in real-time are fundamental to many applications. For our problem, that of ship classification, tactical scenarios often dictate the response time required from a system. In this paper, we discuss efficient ways to prioritize and gather evidence within belief networks. We also suggest ways in which we can structure our large problem into a series of small ones. This both pre-defines much of our control strategy into the system structure and also localizes our run-time control issues into much smaller networks. The overall control strategy thus includes the combination of both of these methods. By combining them correctly we can reduce the amount of dynamic computation required during run-time and thus improve the responsiveness of the system.

Author(s):  
Weiwei Yang ◽  
Jiejunyi Liang ◽  
Jue Yang ◽  
Nong Zhang

Considering the energy consumption and specific performance requirements of mining trucks, a novel uninterrupted multi-speed transmission is proposed in this paper, which is composed of a power-split device, and a three-speed lay-shaft transmission with a traction motor. The power-split device is adapted to enhance the efficiency of the engine by adjusting the gear ratio continuously. The three-speed lay-shaft transmission is designed based on the efficiency map of traction motor to guarantee the drivability. The combination of the power-split device and three-speed lay-shaft transmission can realize uninterrupted gear shifting with the proposed shift strategy, which benefits from the proposed adjunct function by adequately compensating the torque hole. The detailed dynamic models of the system are built to verify the effectiveness of the proposed shift strategy. To evaluate the maximum fuel efficiency that the proposed uninterrupted multi-speed transmission could achieve, dynamic programming is implemented as the baseline. Due to the “dimension curse” of dynamic programming, a real-time control strategy is designed, which can significantly improve the computing efficiency. The simulation results demonstrate that the proposed uninterrupted multi-speed transmission with dynamic programming and real-time control strategy can improve fuel efficiency by 11.63% and 8.51% compared with conventional automated manual transmission system, respectively.


2018 ◽  
Vol 165 (9) ◽  
pp. E366-E374 ◽  
Author(s):  
Hai-yin Xu ◽  
Zhao-hui Yang ◽  
Yuan-ling Luo ◽  
Ping Wang ◽  
Jing Huang ◽  
...  

RSC Advances ◽  
2015 ◽  
Vol 5 (105) ◽  
pp. 86490-86496 ◽  
Author(s):  
Tianqi Ma ◽  
Shaohui Guo ◽  
Zhihui Guo ◽  
Qiushi Zhu ◽  
Jinfu Chen

Indicated high pH benefits the accuracy of real-time control strategy, explained why DO as a control parameter is unreliable.


Pharmaceutics ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 181 ◽  
Author(s):  
Brecht Vanbillemont ◽  
Niels Nicolaï ◽  
Laurens Leys ◽  
Thomas De Beer

The standard operation of a batch freeze-dryer is protocol driven. All freeze-drying phases (i.e., freezing, primary and secondary drying) are programmed sequentially at fixed time points and within each phase critical process parameters (CPPs) are typically kept constant or linearly interpolated between two setpoints. This way of operating batch freeze-dryers is shown to be time consuming and inefficient. A model-based optimisation and real-time control strategy that includes model output uncertainty could help in accelerating the primary drying phase while controlling the risk of failure of the critical quality attributes (CQAs). In each iteration of the real-time control strategy, a design space is computed to select an optimal set of CPPs. The aim of the control strategy is to avoid product structure loss, which occurs when the sublimation interface temperature ( T i ) exceeds the the collapse temperature ( T c ) common during unexpected disturbances, while preventing the choked flow conditions leading to a loss of pressure control. The proposed methodology was experimentally verified when the chamber pressure and shelf fluid system were intentionally subjected to moderate process disturbances. Moreover, the end of the primary drying phase was predicted using both uncertainty analysis and a comparative pressure measurement technique. Both the prediction of T i and end of primary drying were in agreement with the experimental data. Hence, it was confirmed that the proposed real-time control strategy is capable of mitigating the effect of moderate disturbances during batch freeze-drying.


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