Dynamic performance of induction motors in control systems

1968 ◽  
Vol 115 (12) ◽  
pp. 1865 ◽  
Author(s):  
B.V. Jayawant ◽  
K.N. Bateson
Keyword(s):  
Control Systems ◽  
Induction Motors ◽  
Dynamic Performance

Analysis of dynamic performance of induction motors in control systems

1964 ◽  
Vol 111 (11) ◽  
pp. 1949
Author(s):  
G.J. Rogers ◽  
J.C. West ◽  
B.V. Jayawant ◽  
G. Williams
Keyword(s):  
Control Systems ◽  
Induction Motors ◽  
Dynamic Performance

Analysis of dynamic performance of induction motors in control systems

1964 ◽  
Vol 10 (8) ◽  
pp. 271 ◽  
Author(s):  
J.C. West ◽  
B.V. Jayawant ◽  
G. Williams
Keyword(s):  
Control Systems ◽  
Induction Motors ◽  
Dynamic Performance

Multi-objective particle swarm optimisation approach for production-inventory control systems

2018 ◽  
Vol 13 (4) ◽  
pp. 1037-1056 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Control Systems ◽  
Inventory Control ◽  
Dynamic Performance ◽  
Particle Swarm ◽  
Particle Swarm Optimisation ◽  
Inventory Level ◽  
Content Type ◽  
Multi Objective ◽  
Production Inventory

Purpose This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO). Design/method/approach The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation. Findings The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions. Research limitations/implications This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level. Originality/value PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.

Dynamics of Human Operator Control Systems Using Tactile Feedback

1962 ◽  
Vol 84 (2) ◽  
pp. 297-301 ◽  
Author(s):  
S. Weissenberger ◽  
T. B. Sheridan
Keyword(s):  
Control Systems ◽  
Human Activities ◽  
Tactile Stimulus ◽  
Dynamic Performance ◽  
Tactile Feedback ◽  
Human Operator ◽  
Stimulus Information ◽  
The Past ◽  
Important Sense ◽  
Operator Control

Much has been learned in the past ten years about the dynamic performance of the human operator in control tasks primarily involving visual stimuli. In many human activities, however, sight is complemented or superseded by other senses. One important sense modality whose dynamic use is as yet poorly understood is touch. This paper describes an experimental technique for investigating human operator dynamics in tasks where tactile stimulus information is of primary importance; some exemplary results are presented.

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