Abstract
Perceptual Control Theory (PCT) theorizes that a creature’s behaviour is varied so that their perception can reach and maintain certain fixed limits, despite external disturbances. The distinguishing characteristic of PCT is that the controlled variables are the inputs (perceptions, as opposed to the system outputs). This paper presents the first direct comparison of a PCT controller for a mobile robot (a two-wheeled ‘inverted pendulum’ balancing robot) with a classical control method, LQR. Simulations and experimental validation results show that the performance of the PCT controller is comparable to the LQR controller and better at disturbance rejection.
Highlights
Humans, other animals and a variety of machines can be said to ‘behave’ [1]
Another study attempted to achieve optimal control of this system in simulation [17] and found that their LQR controller was able to stabilise at a new reference point in approximately 6s. This result is consistent with the results reported here, and so the LQR controller implemented in this study is considered to be well-performing
The perceptual control theory (PCT) controlled robot had a steady-state error of ≈ 2◦, Fig. 8 A Definition of the Angular and Linear Displacement maintaining a position that was within 5mm of the set point: the performance of the PCT controller in this test was far greater than either of the other competing methods
Summary
Other animals and a variety of machines can be said to ‘behave’ [1]. Yet scientific theories that traverse the life, social and physical sciences are rare. The theory models the system from the inside and permits the system to attempt to control its own sensory input by comparing the current sensory signal to its internally specified reference value, and acting against disturbances in the environment to reduce this difference. Powers utilized this basic scheme to account for complex behavior by proposing that the reference values are set by a cascade of downward signals from higher level units. The comparison vehicle chosen for this study is the inverted pendulum robot, which is a popular benchmark for control theory comparisons [15]
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