DYNAMIC APPROACH TO OPTIMUM SYNTHESIS OF A FOUR-BAR MECHANISM USING A SWARM INTELLIGENCE ALGORITHM

This paper presents a dynamic approach to the synthesis of a crank-rocker four-bar mechanism, that is obtained by an optimization problem and its solution using the swarm intelligence algorithm called Modified-Artificial Bee Colony (M-ABC). The proposed dynamic approach states a mono-objective dynamic optimization problem (MODOP), in order to obtain a set of optimal parameters of the system. In this MODOP, the kinematic and dynamic models of the whole system are consider as well as a set of constraints including a dynamic constraint. The M-ABC algorithm is adapted to solve the optimization problem by adding a suitable constraint-handling mechanism that is able to incorporate the kinematic and dynamic constraints of the system. A set of independent computational runs were carried out in order to validate the dynamic approach. An analysis from the mechanical and computational point of view is presented, based on the obtained results. From the analysis of the simulation and its results, it is shown that the solutions for the proposed algorithm lead to a more suitable design based on the dynamic approach.