Practical implementation of an effective robust adaptive fuzzy variable structure tracking control for a wheeled mobile robot

Adaptive control of electrically‐driven nonholonomic wheeled mobile robots: Taylor series‐based approach with guaranteed asymptotic stability

“…A two-layered fuzzy neural networks alongside extended Kalman filtering [37] has been utilized for the trajectory tracking control of a mobile manipulator. An adaptive fuzzy observer [38], a backstepping fuzzy sliding mode controller [39], and a robust adaptive fuzzy control based on a variable structure [40] have been designed to deal with the tracking problem of a wheeled mobile robot. Though universal approximators such as fuzzy systems and neural networks have the features to design model-free controllers, these methods usually suffer from a large number of tuning parameters and inputs which cause more computational efforts for control algorithms.…”

“…A remarkable feature of 3D simulation is that there is no need of mathematical dynamic model of WMR obtained by Newton-Euler method, Lagrange methodology or Gibbs-Appel method in simulation procedure. Moreover, the robust adaptive fuzzy controller [40] is simulated as a comparative study to show the proposed control's effectiveness. This manuscript is organized as follows: Section 2 provides the dynamics formulation of an electrically-driven differential drive wheeled mobile robot.…”

“…A comparative study is carried out with a well-designed robust adaptive fuzzy controller [40] to confirm the efficacy of our designed control structure. The robust adaptive fuzzy controller [40] utilizing variable structure was designed to be chattering-free and able to compensate for uncertainties ensuring the asymptotic tracking control of WMR without considering its actuators dynamics. Using an adaptive fuzzy variable structure, the discontinuous control gain has been approximated.…”

“…Using an adaptive fuzzy variable structure, the discontinuous control gain has been approximated. The control input is designed as [40] 𝒗 = −𝑩 0 𝜎 −1 𝑨 0 𝜎 − 𝑭 ̂(𝝈 * ) − 𝑲𝝈 * (84)…”

Robot Arm Structure Design Using Polyamide Evaluated by Finite Element Analysis

“…In Ref. 26, a robust solution to the trajectory tracking control problem under uncertainties and disturbances was obtained. Simulation and experimental results were explored to verify the effectiveness of the proposed control strategy.…”