Lion algorithm for standard and large scale bilinear system identification: A global optimization based on Lion´s social behavior

Nonlinear system identification process, especially bilinear system identification process exploits global optimization algorithms for betterment of identification precision. This paper attempts to introduce a new optimization algorithm called as Lion algorithm to accomplish the system characteristics precisely. Our algorithm is a simulation model of the lion´s unique characteristics such as territorial defense, territorial takeover, laggardness exploitation and pride. Experiments are conducted by identifying a nonlinear rationale digital benchmark system using standard bilinear model and comparisons are made with prominent genetic algorithm and differential evolution. Subsequently, curse of dimensionality is also experimented by defining a large scale bilinear model, i.e. bilinear system with 1023 bilinear kernel models, to identify the same digital benchmark system. Lion algorithm dominates when using standard bilinear model, whereas it is equivalent to differential evolution and better than genetic algorithm when using large scale bilinear model.