An Optimized Design of New XYθ Mobile Positioning Microrobotic Platform for Polishing Robot Application Using Artificial Neural Network and Teaching-Learning Based Optimization

Table 9

Validation results.

Case study	Method	Performances
		y-stroke (μm)	Safety factor
Case 1	Proposed method	1558.6763	1.58
	FEA results	1432.2	1.47
Error (%)		8.8	7.48
Case 2	Proposed method	1300.6	2.3
	FEA results	1368.7	2.2
Error (%)		4.97	4.54
Case 3	Proposed method	1568.1	2.04
	FEA results	1689.8	2.17
Error (%)		7.2	5.9