A finite-time particle swarm optimization algorithm for odor source localization

作者：Lu, Qiang^*; Han, Qing-Long; Liu, Shirong

来源：Information Sciences, 2014, 277: 111-140.

DOI：10.1016/j.ins.2014.02.010

• Particle swarm optimization
• Finite-time convergence
• Multi-robot system
• Odor source localization

This paper is concerned with a finite-time particle swarm optimization algorithm for odor source localization. First, a continuous-time finite-time particle swarm optimization (FPSO) algorithm is developed based on the continuous-time model of the particle swarm optimization (PSO) algorithm. Since the introduction of a nonlinear damping item, the proposed continuous-time FPSO algorithm can converge over a finite-time interval. Furthermore, in order to enhance its exploration capability, a tuning parameter is introduced into the proposed continuous-time FPSO algorithm. The algorithm's finite-time convergence is analyzed by using the Lyapunov approach. Second, the discrete-time FPSO algorithm is obtained by using a given dicretization scheme. The corresponding convergence condition is derived by using a linear matrix inequality (LMI) approach. Finally, the features and performance of the proposed FPSO algorithm are illustrated by using two ill-posed functions and twenty-five benchmark functions, respectively. In numerical simulation results, the problem of odor source localization is presented to validate the effectiveness of the proposed FPSO algorithm.

• 出版日期2014-9-1
• 单位杭州电子科技大学