fuzzy adaptive control of a two-wheeled inverted pendulum
abstract
recently, the two-wheeled inverted pendulum has drawn the attention of robotic community
in view of a plethora of applications, such as transport vehicles: segway, teleconferencing
robots, and electronic network-vehicle. as a widely-used personal transportation vehicle, a
two-wheeled inverted pendulum robot has the advantages of small size and simple structure.
moreover, with the advent of modern control technology, these kinds of platforms with
safety features and sophisticated control functions can be cost down, so that they have high
potential to satisfy stringent requirements of various autonomous service robots with high
speed. at the same time, it is of great interest from control point of view as the inverted
pendulum is a complicated, strongly coupled, unstable and nonlinear system. therefore, it
is an ideal experimental platform for various control theories and experiments.
to understand such a complex system, the lagrangian equation has been introduced to
develop a dynamic model. and following the mathematical model, linear quadratic regulator
control and fuzzy adaptive method are proposed for upright stabilization, velocity control
and position control of the system. however, sometimes these kinds of robots need to move
on a slope, so an advanced linear quadratic regulator controller and a modified fuzzy adaptive
controller have been proposed to achieve position control on a slope for the robot while
stabilizing its body in balance. in addition, trajectory tracking control using proportional
integral derivative control and sliding mode control with fuzzy adaptive backstepping method
is also designed to make the robot autonomously navigate in two dimensional plane.
simulation results indicate that the proposed controllers are capable of providing appropriate
control actions to steer the vehicle in desired manners. then, a couple of real time experiments
have been conducted to verify the the effectiveness of the developed control strategies.