Nyambayar Baatar

Shape Optimal Design of a 9-pole 10-slot PMLSM for Detent Force Reduction Using Adaptive Response Surface Method

The detent force of a permanent magnet linear synchronous motor (PMLSM) consists of cogging and drag forces, and should be minimized for high precision purpose application. This paper suggests a new 9-pole 10-slot structure of a short primary PMLSM to remove the cogging force. Through theoretical and finite element analysis, the proposed structure is proven to remove most of the cogging force. The detent force is minimized by optimizing the length of armature core and shape of the exterior teeth simultaneously by using (1+lambda) evolution strategy coupled with response surface method using multi-quadric radial basis function. Additionally, simulation results for the proposed structures are verified by experimental measurements.

An Improved Differential Evolution Algorithm Adopting

The differential evolution (DE) algorithm has almost ten different variants according to a trial vector generation strategy. The trial vector generation strategy has a significant effect on the performance of the DE algorithm. The selection of a suitable mutation strategy, however, is difficult because of the differences in the convergence speed and diversity. This paper proposes an improved differential evolution algorithm adopting a new mutation strategy, “

\lambda

{\rm DE}/\lambda-{\rm best}/1

-Best Mutation Strategy for Global Optimization of Electromagnetic Devices

,” to increase the performance of global optimization. The suggested mutation strategy guides the population to the feasible region of various constraint optimization problems. The validity and numerical efficiency of the developed method was investigated through a comparison with conventional DEs on well known benchmark functions and Testing Electromagnetic Analysis Methods (TEAM) problem 22.

Adaptive Parameter Controlling Non-Dominated Ranking Differential Evolution for Multi-Objective Optimization of Electromagnetic Problems

This paper proposes an adaptive parameter controlling non-dominated ranking differential evolution (A-NRDE) algorithm for multi-objective optimal design of electromagnetic problems. The variable parameters, such as mutation and crossover rates, are self-controlled based on the information of successful individuals and the number of Pareto optimal solutions in current iteration. In mutation step, the proposed algorithm incorporates multi-guiders to obtain a uniformly distributed Pareto front; the advantages of DE are combined with the mechanisms of non-dominated ranking and crowding distance sorting. The proposed A-NRDE algorithm is applied to a multi-objective version of TEAM 22 and five benchmark problems. Experimental results show that the proposed our approach is able to obtain a good distribution of Pareto front and convergence in all cases. Compared with several other state-of-the-art evolutionary algorithms, it achieves not only comparable results in terms of convergence and diversity metrics, but also a considerable reduction of the computational effort.

Multiguiders and Nondominate Ranking Differential Evolution Algorithm for Multiobjective Global Optimization of Electromagnetic Problems

The differential evolution (DE) algorithm was initially developed for single-objective problems and was shown to be a fast, simple algorithm. In order to utilize these advantages in real-world problems it was adapted for multiobjective global optimization (MOGO) recently. In general multiobjective differential evolutionary algorithm, only use conventional DE strategies, and, in order to optimize performance constrains problems, the feasibility of the solutions was considered only at selection step. This paper presents a new multiobjective evolutionary algorithm based on differential evolution. In the mutation step, the proposed method which applied multiguiders instead of conventional base vector selection method is used. Therefore, feasibility of multiguiders, involving constraint optimization problems, is also considered. Furthermore, the approach also incorporates nondominated sorting method and secondary population for the nondominated solutions. The propose algorithm is compared with resent approaches of multiobjective optimizers in solving multiobjective version of Testing Electromagnetic Analysis Methods (TEAM) problem 22.

A collaborative design approach to interdisciplinary mixed-signal SoCs for automotive applications

A collaborative design approach to interdisciplinary mixed-signal SoCs for automotive applications is presented. Mixed-signal SoC design for vehicles involves the collaborative blending of mixed-signal systems with convergence among multidisciplinary areas of technology such as mechanical, MEMS, and semiconductor technologies with analog and digital signal processing. The key features of this approach include a system knowledge-based control algorithm, collaborative design, rapid prototyping, mixed signal interoperability, and intelligent information processing.

A dual-rail voltage supply for battery powered portable devices

A positive and negative dual rail voltage supply proposed for battery powered portable devices and a test chip designed and fabricated by using 0.13um CMOS triple-well process. Proposed dual voltage scheme provides an effective way of reducing the dynamic power consumption due to the charge recycling through the upper power rail and lower power rail separated by series connected capacitors. The additional advantage of the proposed system is that we can separate digital block and analog block depending on the requirement of operating speed and voltage swing levels.