Parametric modelling approach using bacterial foraging algorithms for modelling of flexible manipulator systems

This paper presents current work on biologically-inspired optimisation techniques based on bacterial foraging algorithms (BFAs) and their application to modelling of a single-link flexible manipulator. The objective of this work is to develop a single-link flexible manipulator model based on modified BFAs. First, three adaptation mechanisms of the chemotactic step size mechanism of BFA are proposed. New approaches of adaptable chemotactic step size are based on linear, quadratic and exponential functions of cost function value. Then, these three adaptive BFAs are used to develop three single-input single-output models to characterise a flexible manipulator from torque input to hub-angle, hub velocity and end-point acceleration responses. The performances of the adaptive BFAs are compared to that of standard BFA based on convergence to optimum value, the optimum value achieved and time-domain and frequency domain responses of the developed models.     

Optimization of pretreatment of Jatropha oil with high free fatty acids for biodiesel production

A central composite rotatable design and response surface methodology were used in order to investigate the individual and combined effects of the ethanol-to-oil ratio, H₂SO₄ concentration, temperature and time of reaction on the reduction of free fatty acid (FFA) in jatropha oil. A quadratic polynomial model relating the reaction variables with FFA reduction was developed, presenting a good coefficient of determination (R²= 0.893). For reducing FFA to less than 1%, the optimal combination was found to be 0.62 v·v^-1 ethanol-to-oil ratio (14.9 v·v^-1 ethanol-to-FFA ratio), 1.7% v·v^-1 H₂SO₄ concentration, and 79 min reaction time at a reaction temperature of 54°C. These results are of great relevance to maximize methyl esters formation by transesterification using an alkaline catalyst.