Nonlinear Controllers in the Regulation Problem of the Robots ⁎ ⁎This work was financially supported by Russian Foundation for Basic Research [grant number 18-01-00702] and Ministry of Education and Science of Russia within the framework of the State task under Grant [9.5994.2017/BP ].

Andreev, Aleksandr; Peregudova, Olga

doi:10.1016/j.ifacol.2018.06.007

Cited by 7 publications

(1 citation statement)

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“…In [ 54 , 55 ], the researchers mentioned the cooperative output control of a mobile flexible manipulator and also the distributed output feedback control of non-holonomic mobile robots with only the leader’s position measurement. Then, in [ 56 , 57 ], an output trajectory tracking of mobile robots and an adaptive tracking control by means of output feedback for mobile robots are presented, respectively. Then, in [ 58 ], an output tracking of a non-holonomic mobile robot with fractional order visual feedback is evinced.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Output Feedback and Neural Network Control of a Non-Holonomic Mobile Robot

Cardona

Serrano

2023

Sensors

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This paper presents the design and synthesis of a dynamic output feedback neural network controller for a non-holonomic mobile robot. First, the dynamic model of a non-holonomic mobile robot is presented, in which these constraints are considered for the mathematical derivation of a feasible representation of this kind of robot. Then, two control strategies are provided based on kinematic control for this kind of robot. The first control strategy is based on driftless control; this means that considering that the velocity vector of the mobile robot is orthogonal to its restriction, a dynamic output feedback and neural network controller is designed so that the control action would be zero only when the velocity of the mobile robot is zero. The Lyapunov stability theorem is implemented in order to find a suitable control law. Then, another control strategy is designed for trajectory-tracking purposes, in which similar to the driftless controller, a kinematic control scheme is provided that is suitable to implement in more sophisticated hardware. In both control strategies, a dynamic control law is provided along with a feedforward neural network controller, so in this way, by the Lyapunov theory, the stability and convergence to the origin of the mobile robot position coordinates are ensured. Finally, two numerical experiments are presented in order to validate the theoretical results synthesized in this research study. Discussions and conclusions are provided in order to analyze the results found in this research study.

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