The Multi objective Optimization of a Tricept Parallel Manipulator Using Evolutionary Algorithm:

syed saad farooq

Article Details

The Multi objective Optimization of a Tricept Parallel Manipulator Using Evolutionary Algorithm:

Authors:

syed saad farooq

Publisher:

Kuwait University

Journal:

Journal of Engineering Research Vol.9 Issue 2, pp.0-0

Document Type:

Article

Publication Date:

5/2021

Document Language:

English

Document ID (Org No.):

2001942095

pISSN:

2307-1885

Abstract:

 Parallel manipulator famous for its rigidity and precision needs optimization in different performance parameters like conditioning index, workspace volume and the global index. This paper will emphasis on the special type of parallel namely Tricept mechanism. Tricept is a 3 DOF UPS mechanism with one static base and the moving head platform. Mechanisms previously modeled with its inverse kinematics and jacobians that lead us towards the conditioning index and the workspace volumes and optimized through the genetic algorithms. With a view to compare with previous work, Weighted Particle swarm (PSO) technique has been introduced here for the multi objective optimization and results achieved through this technique was compared and validated with already published optimization results. Keywords: Inverse kinematics, Conditioning index, Workspace volume, GCI, Single Objective Optimization, Multi objective Particle Swarm Optimization (MOPSO), Weighted Sum Strategy.

Article Details

The Multi objective Optimization of a Tricept Parallel Manipulator Using Evolutionary Algorithm:

Authors: syed saad farooq

Publisher: Kuwait University

Journal: Journal of Engineering Research Vol.9 Issue 2, pp.0-0

Document Type: Article

Publication Date: 5/2021

Document Language: English

Document ID (Org No.): 2001942095

pISSN: 2307-1885

Issues

Authors:

syed saad farooq

Publisher:

Kuwait University

Journal:

Journal of Engineering Research Vol.9 Issue 2, pp.0-0

Document Type:

Article

Publication Date:

5/2021

Document Language:

English

Document ID (Org No.):

2001942095

pISSN:

2307-1885