In this paper a novel algorithm with a dynamic fuzzy controller applied to the control of trajectory of vehicles with two independent wheels is proposed. An automatic control of trajectory of a vehicle can behave in a not efficient way. It is necessary to consider the friction of the actuators and possible perturbations coming from the outside environment, as for instance the variable characteristics of the ground where the vehicle moves. These perturbations, which depend also on the contact between the wheel and the ground, involve violations of nonholonomic constraints. Thus it is necessary to compensate for these perturbations to obtain a robust control system. The controller synthetized in this work is able to obtain a term of additive adaptation to the dynamic control law by means of a fuzzy inference mechanism. Asymptotic stability of equilibrium state of fuzzy control system is developed by the Direct Lyapunov method and Barbalat''s lemma. A series of simulations in Matlab 6.5 confirms the validity of the algorithm.
RAIMONDI FM, MELLUSO M (2005). A New Fuzzy Robust Dynamic Fuzzy Controller for Autonomous Vehicle with Nonholonomic Constraints. ROBOTICS AND AUTONOMOUS SYSTEMS, 52, 115-131 [http://dx.doi.org/10.1016/j.robot.2005.04.006].
A New Fuzzy Robust Dynamic Fuzzy Controller for Autonomous Vehicle with Nonholonomic Constraints
RAIMONDI, Francesco Maria;MELLUSO, Maurizio
2005-01-01
Abstract
In this paper a novel algorithm with a dynamic fuzzy controller applied to the control of trajectory of vehicles with two independent wheels is proposed. An automatic control of trajectory of a vehicle can behave in a not efficient way. It is necessary to consider the friction of the actuators and possible perturbations coming from the outside environment, as for instance the variable characteristics of the ground where the vehicle moves. These perturbations, which depend also on the contact between the wheel and the ground, involve violations of nonholonomic constraints. Thus it is necessary to compensate for these perturbations to obtain a robust control system. The controller synthetized in this work is able to obtain a term of additive adaptation to the dynamic control law by means of a fuzzy inference mechanism. Asymptotic stability of equilibrium state of fuzzy control system is developed by the Direct Lyapunov method and Barbalat''s lemma. A series of simulations in Matlab 6.5 confirms the validity of the algorithm.File | Dimensione | Formato | |
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