Browsing by Author "Gamage, L. B"

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Design evolution of engineering systems using bond graphs and genetic programming
(Pergamon, 2016-02-01) Samarakoon, B. L; Gamage, L. B; de Silva, C. W
This paper presents a scheme of evolutionary design optimization, which integrates modeling with bond graphs and optimization using genetic programming for multi-domain engineering systems, particularly mechatronic systems. The performance of the developed system is studied using both experimentation and simulation. During the evolutionary optimization, in addition to the desired response error, system complexity is also taken into account. For the experimental study, the method is implemented in an industrial fish processing machine at the Industrial Automation Laboratory of the University of British Columbia, and the obtained results for suggested design modifications are studied and tested. The drawbacks of the fitness calculation methodologies that are presented in literature are identified and improved fitness functions are developed for evolutionary design in the present work. While previous work has investigated the integration of bond graphs and genetic programming for designing an engineering system, the present work specifically addresses the application of the developed method for the design improvement of an industrial machine. The proposed method is applicable particularly to existing engineering systems, first because the initial model can be tested by comparing its simulated results with the corresponding results from the actual physical system, and second because the design improvements as suggested by the evolutionary design framework, which is developed in the present work, may be implemented and tested against the behavior of the corresponding model.
Embargo
Design evolution of mechatronic systems through modeling, on-line monitoring, and evolutionary optimization
(Pergamon, 2012-02-01) Gamage, L. B; De Silva, C. W; Campos, R
This paper presents a system framework to automate the design evolution of multi-domain engineering systems. The developed system integrates machine health monitoring with an expert system to monitor the performance of an existing mechatronic system and to take a decision as to whether and which part of the system a design improvement is necessary. A system model represented by Linear Graphs is evolved using genetic programming to obtain a design that optimally satisfies a specified level of performance. The developed approach allows exploration of the design space to find the optimum design solution in an automated manner. In order to control the arbitrary exploration of the design space, domain knowledge, expertise, and input from the machine health monitoring system are used. The design evolution algorithm is implemented using GPLAB, a MATLAB tool, and integrated with Simscape for modeling and simulation. The developed system is applied to redesign the electro-mechanical conveyor system of an industrial fish processing machine.