Optimal control by least squares support vector machines
Neural Networks
Stable Adaptive Neural Network Control
Stable Adaptive Neural Network Control
Robust Autonomous Guidance
Dynamic Analysis of a Nonholonomic Two-Wheeled Inverted Pendulum Robot
Journal of Intelligent and Robotic Systems
Velocity and position control of a wheeled inverted pendulum by partial feedback linearization
IEEE Transactions on Robotics
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
Brief Adaptive stabilization of uncertain nonholonomic systems by state and output feedback
Automatica (Journal of IFAC)
An overview of statistical learning theory
IEEE Transactions on Neural Networks
A versatile software tool making best use of sparse data for closed loop process control
Advances in Engineering Software
Development and path planning of a biped robot
ICSR'12 Proceedings of the 4th international conference on Social Robotics
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The dynamic balance and motion control based on LS-SVM (least squares support vector machine) are considered for mobile wheeled inverted pendulums (WIP), in the presence of parametric and functional dynamics uncertainties. Based on Lyapunov synthesis, the proposed control mechanisms use the advantage of LS-SVM combined with on-line parameters estimation strategy in order to have an efficient approximation. Under the controller designed, we can ensure that the outputs of the system track the given bounded reference signals within a small neighborhood of zero, and guarantee semi-global uniform boundedness of all the closed loop signals. Simulation results are presented to verify the effectiveness of the proposed control.