Optimal Sizing of Amplifiers by Evolutionary Algorithms with Integer Encoding and $$g_m/I_D$$ Design Method

2017 ◽  
pp. 263-279
Author(s):  
Adriana C. Sanabria-Borbón ◽  
Esteban Tlelo-Cuautle ◽  
Luis Gerardo de la Fraga
Keyword(s):  
Evolutionary Algorithms ◽  
Design Method ◽  
Optimal Sizing

Evolutionary Algorithms in the Optimal Sizing of Analog Circuits

2011 ◽  
pp. 109-138 ◽  
Author(s):  
Esteban Tlelo-Cuautle ◽  
Ivick Guerra-Gómez ◽  
Luis Gerardo de la Fraga ◽  
Georgina Flores-Becerra ◽  
Said Polanco-Martagón ◽  
...  
Keyword(s):  
Evolutionary Algorithms ◽  
Analog Circuits ◽  
Optimal Sizing

Research of Space Electronic Circuit Optimization Design

2011 ◽  
Vol 48-49 ◽  
pp. 932-936
Author(s):  
Xue Song Yan ◽  
Qing Hua Wu ◽  
Cheng Yu Hu ◽  
Qing Zhong Liang
Keyword(s):  
Evolutionary Algorithms ◽  
Circuit Design ◽  
Optimization Design ◽  
Design Method ◽  
Dynamic Change ◽  
Electronic System ◽  
Circuit Optimization ◽  
The Stability ◽  
Exploratory Mission ◽  
Adverse Circumstance

During the space electronic system in carries out the exploratory mission in the deep space, it maybe faced with kinds of violent natural environment, to electric circuit's performance, the volume, the weight and the stability proposed a higher request, the traditional circuit design method already more and more with difficulty satisfied this kind of request. The traditional circuit design method already more and more with difficulty satisfied this kind of request. But unifies the programmable component and the evolutionary algorithms hardware may the dynamic change hardware's structure adapt the adverse circumstance, resume the damage of the function, the adaptation for the duty change. In view of the Xilinx Company's FPGA unique feature, proposed one kind of evolutionary algorithms which uses in the space electronic system circuit optimization design and through the experiment proved, the algorithm obtains the circuit structure to surpass the tradition circuit design method.

Optimisation of Subsea Tie-In Spools Using Evolutionary Algorithms

2013 ◽  
Author(s):  
Chris Madeley
Keyword(s):  
Evolutionary Algorithms ◽  
Design Method ◽  
Linear Optimization ◽  
Three Dimensional ◽  
Design Parameters ◽  
Element Analysis ◽  
Design Problems ◽  
Engineering Problems ◽  
Optimum Solution ◽  
Pipeline Design

Tie-in spools must be designed to resist a large number of onerous load combinations. These loads include gravitational, temperature, pressure and environmental loads along with various imposed displacements. Additionally, there are several design constraints that must be satisfied. Due to the three-dimensional geometric freedom of the spool there are many possible design scenarios that could be evaluated in the search for the optimum solution. It is the responsibility of the pipeline design engineer to use their own judgment and experience to find the best possible solution within the design period. Traditionally a trial and error design approach is used in an iterative manner. This method is typically slow and labor intensive and can be too focused on one design concept at the expense of others that are potentially superior. On similar engineering problems with many design parameters automated non-linear optimization routines have been shown to be very effective. Specifically, applying evolutionary algorithms is a robust, time-effective and adaptable approach. Such a tool assists the engineer in finding superior design solutions and assists in searching the entire design space. To test this design method, a multi-objective evolutionary algorithm has been applied to two semi-constrained spool design problems. The spool design has been modeled using finite element analysis. First, the algorithm was applied to the optimization of spool geometry for multiple design objectives. Within 24-hours of runtime the algorithm was able to find superior solutions to those found using a traditional iterative approach. Also, the trade-off between conflicting design objectives could be quantified and visualized to enable the designer to select the most appropriate candidate. The second problem evaluated was the placement of supports to mitigate the onset of vortex induced vibration (VIV). The algorithm was again able to quickly find a better solution and quantify the tradeoff between conflicting design objectives. The paper presents the results of this new design process as applied by subsea pipeline engineers to find optimum spool designs.

Circuit Optimization Design Using Evolutionary Algorithms

2011 ◽  
Vol 187 ◽  
pp. 303-308
Author(s):  
Xue Song Yan ◽  
Qing Hua Wu ◽  
Cheng Yu Hu ◽  
Qing Zhong Liang
Keyword(s):  
Evolutionary Algorithms ◽  
Circuit Design ◽  
Optimization Design ◽  
Design Method ◽  
Dynamic Change ◽  
Electronic System ◽  
Circuit Optimization ◽  
Circuit Structure ◽  
The Stability ◽  
Exploratory Mission

During the space electronic system in carries out the exploratory mission in the deep space, it maybe faced with kinds of violent natural environment, to electric circuit's performance, the volume, the weight and the stability proposed a higher request, the traditional circuit design method already more and more with difficulty satisfied this kind of request. The traditional circuit design method already more and more with difficulty satisfied this kind of request. But unifies the programmable component and the evolutionary algorithms hardware may the dynamic change hardware's structure adapt the adverse circumstance, resume the damage of the function, the adaptation for the duty change. After the optimization, obtains the circuit structure will often stem from our anticipation, this will be the altitude which the experience and the skillful institute hope to attain with difficulty. In view of the Xilinx Company's FPGA unique feature, proposed one kind of evolutionary algorithms which uses in the space electronic system circuit optimization design and through the experiment proved, the algorithm obtains the circuit structure to surpass the tradition circuit design method. This work investigates the application of genetic algorithms in the field of circuit optimization. For the case studies, this means has proved to be efficient and the experiment results show that the new means have got the better results.

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