MULTI-OBJECTIVE OPTIMIZATION FOR A NOVEL ELECTROSTATIC-FEEDBACK MICRO-SENSOR BASED ON GENETIC ALGORITHM
In this paper, we present the multi-objective optimization for an entire microsystem, a novel capacitive electrostatic feedback accelerometer. From the energy relations of the coupled electrostatic-field, the dynamic model of the system is constructed. Aiming at the global performance, a multi-objective optimization model, where sensitivity, resolution and damping resonant frequency are selected as objectives, is established based on the concept of multidisciplinary design optimization (MDO). Genetic algorithm (GA) is used to solve this problem, and compared with a traditional optimization approach, sequence quadratic programming (SQP). Both the two algorithms can achieve our aim commendably, and the optimal solution given by GA is more satisfied. The research provides us a good foundation to develop the stochastic and implicit parallel properties of GA to obtain Pareto optimal solutions.
Yongquan Wang Hualing Chen Zhiying Ou Xueming He
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China School of Aerospace, Xi’an Jiaotong University, Xi’an 710049, China
国际会议
海南三亚
英文
2007-01-10（万方平台首次上网日期，不代表论文的发表时间）