A Chaotic Krill Herd Optimization Algorithm for Global Numerical Estimation of the Attraction Domain for Nonlinear Systems

Nowadays, solving constrained engineering problems related to optimization approaches is an attractive research topic. The chaotic krill herd approach considered as one of most advanced techniques. An hybrid technique exploited in this paper solve the challenging problem estimating largest domain attraction for nonlinear systems. Indeed, intelligent methodology estimation stable equilibrium established on quadratic Lyapunov functions developed. designed aims at computing and characterizing a level set function that included particular region, satisfying some hard delicate algebraic constraints. formulated searches tangency constraint between LF derivative sign constraints sets. Such formulation avoids possible dummy solutions solver. analytical development solution exploits Chebyshev map ensures high search space capabilities. accuracy efficiency has been evaluated by benchmark models shows effective determining estimate domain. Moreover, since global optimality needed proper estimation, bound type meta-heuristic solver implemented. In contrast existing strategies, synthesized can be both rational polynomial functions. it permits exploitation operative algorithm which guarantees converging expanded essentially restricted running time. discussed, with several examples illustrate advantageous aspects approach.