Title :
Stochastic source seeking with tuning of forward velocity
Author :
Liu, Shu-Jun ; Frihauf, Paul ; Krstic, Miroslav
Author_Institution :
Dept. of Math., Southeast Univ., Nanjing, China
Abstract :
Using the method of stochastic extremum seeking, we navigate an autonomous vehicle, modeled as a nonholonomic unicycle, towards the maximum of an unknown, spatially distributed signal field by measuring only the signal at the vehicle´s position. The vehicle position is not measured. Keeping the angular velocity constant, we control the forward velocity by designing a stochastic source seeking control law, which employs excitation based on filtered white noise rather than sinusoidal perturbations used in previous works. We prove local exponential convergence, both almost surely and in probability, to a small neighborhood near the source and provide numerical simulations to illustrate the effectiveness of the algorithm.
Keywords :
convergence; filtering theory; mobile robots; motion control; path planning; position control; probability; signal processing; stochastic systems; velocity control; angular velocity; autonomous agents; autonomous vehicle; forward velocity control; forward velocity tuning; local exponential convergence; mobile robot; nonholonomic unicycle; spatially distributed signal field; stochastic extremum seeking method; stochastic source seeking control law; white noise filtering; Angular velocity; Convergence; Mobile robots; Position measurement; Stochastic processes; Tuning; Vehicles; Extremum seeking; nonholonomic unicycle; stochastic averaging;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3