This paper describes an approach to the systems integration problem using multiobjective genetic algorithms. An architecture for evolutionary systems integration is presented and the component parts discussed. An example of an aircraft gas turbine engine control system design problem is shown demonstrating aspects of the proposed architecture that allow many design objectives from different disciplines to be considered in parallel. Potential closed-loop control configurations are evaluated and compared against one another within an optimization framework. As a result of this analysis, it is shown how informed decisions may be made regarding the nature of the control employed, acceptable performance margins and elements of the engine design
The evolutionary approach to multiple function optimization formulated in the first part of the pape...
The increasing use of embedded intelligence to produce smart sensors and actuators offers great pote...
Challenging optimisation problems, which elude acceptable solution via conventional methods, arise r...
This paper describes a novel approach to the design of a control system for an aircraft gas turbine ...
This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multiva...
The control configuration design problem is to find appropriate sets of closed - and/or open-loop co...
Multidisciplinary optimization (MDO) is concerned with complex systems exhibiting challenges in term...
This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multiva...
This paper describes a novel approach to the problem of control mode analysis for advanced concept g...
The work in this thesis examines how complex dynamic systems can be improved and analysed using opti...
A multi-stage design approach that uses a multiobjective genetic algorithm as the framework for opti...
Developments in computational models of evolutionary processes have led to the realization of powerf...
Optimisation is a challenge for computerized multidisciplinary design. With multidisciplinary design...
The increasing use of embedded intelligence to produce smart sensors and actuators offers great pote...
Abstract: This paper presents a methodology based on Multiobjective Genetic Algorithms (MOGA’s) for ...
The evolutionary approach to multiple function optimization formulated in the first part of the pape...
The increasing use of embedded intelligence to produce smart sensors and actuators offers great pote...
Challenging optimisation problems, which elude acceptable solution via conventional methods, arise r...
This paper describes a novel approach to the design of a control system for an aircraft gas turbine ...
This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multiva...
The control configuration design problem is to find appropriate sets of closed - and/or open-loop co...
Multidisciplinary optimization (MDO) is concerned with complex systems exhibiting challenges in term...
This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multiva...
This paper describes a novel approach to the problem of control mode analysis for advanced concept g...
The work in this thesis examines how complex dynamic systems can be improved and analysed using opti...
A multi-stage design approach that uses a multiobjective genetic algorithm as the framework for opti...
Developments in computational models of evolutionary processes have led to the realization of powerf...
Optimisation is a challenge for computerized multidisciplinary design. With multidisciplinary design...
The increasing use of embedded intelligence to produce smart sensors and actuators offers great pote...
Abstract: This paper presents a methodology based on Multiobjective Genetic Algorithms (MOGA’s) for ...
The evolutionary approach to multiple function optimization formulated in the first part of the pape...
The increasing use of embedded intelligence to produce smart sensors and actuators offers great pote...
Challenging optimisation problems, which elude acceptable solution via conventional methods, arise r...