Direct model reference adaptive tracking control of wheeled mobile robot

Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling if left unattended. In this work, three soft computing techniques were proposed to track a desired velocity of the TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP model. All the three controllers have shown practically good performance in tracking the desired speed and keeping the robot in upright position and ANFIS has shown slightly better performance than FLC, while NN consumes more energy.

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Direct model reference adaptive tracking control of wheeled mobile robot

Cited by 2 publications

References 5 publications

Model Following Adaptive Control for a Class of Complex Dynamic Networks Based on the Dynamics of Links

Model Following Adaptive Control for a Class of Complex Dynamic Networks Based on the Dynamics of Links

Intelligent Controllers for Velocity Tracking of Two Wheeled Inverted Pendulum Mobile Robot

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