A curriculum for real-time computer and control systems engineering

Bacteria are capable of sensing and responding to changes in their environment. One of the ways they do this is via chemotaxis, regulating swimming behaviour. The chemotaxis pathway senses chemoattractant gradients and uses a feedback loop to change the bacterial swimming pattern; this feedback loop differs in detail between species. In the present article, we summarize the current understanding of the regulatory mechanisms in three species and how these pathways can be viewed and analysed through the ideas of feedback control systems engineering.

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A LEGO Mindstorms NXT approach for teaching at Data Acquisition, Control Systems Engineering and Real-Time Systems undergraduate courses

Computers & Education ◽

10.1016/j.compedu.2012.03.026 ◽

2012 ◽

Vol 59 (3) ◽

pp. 974-988 ◽

Cited By ~ 58

Author(s):

A. Cruz-Martín ◽

J.A. Fernández-Madrigal ◽

C. Galindo ◽

J. González-Jiménez ◽

C. Stockmans-Daou ◽

...

Keyword(s):

Data Acquisition ◽

Control Systems ◽

Real Time ◽

Systems Engineering ◽

Real Time Systems ◽

Control Systems Engineering ◽

Lego Mindstorms ◽

Time Systems

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Realtime production scheduling and control systems in smart industry

Impact ◽

10.21820/23987073.2020.8.60 ◽

2020 ◽

Vol 2020 (8) ◽

pp. 60-61

Author(s):

Wei Weng

Keyword(s):

Control Systems ◽

Real Time ◽

Production Scheduling ◽

Production Control ◽

Optimal Solution ◽

Scheduling Problem ◽

Optimal Solutions ◽

Scheduling Problems ◽

Smart Industry ◽

And Control

For a production system, 'scheduling' aims to find out which machine/worker processes which job at what time to produce the best result for user-set objectives, such as minimising the total cost. Finding the optimal solution to a large scheduling problem, however, is extremely time consuming due to the high complexity. To reduce this time to one instance, Dr Wei Weng, from the Institute of Liberal Arts and Science, Kanazawa University in Japan, is leading research projects on developing online scheduling and control systems that provide near-optimal solutions in real time, even for large production systems. In her system, a large scheduling problem will be solved as distributed small problems and information of jobs and machines is collected online to provide results instantly. This will bring two big changes: 1. Large scheduling problems, for which it tends to take days to reach the optimal solution, will be solved instantly by reaching near-optimal solutions; 2. Rescheduling, which is still difficult to be made in real time by optimization algorithms, will be completed instantly in case some urgent jobs arrive or some scheduled jobs need to be changed or cancelled during production. The projects have great potential in raising efficiency of scheduling and production control in future smart industry and enabling achieving lower costs, higher productivity and better customer service.

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