Abstract: In this paper, a worm-like micro robot designed for inpipe
application with intelligent active force control (AFC) capability
is modelled and simulated. The motion of the micro robot is based on
an impact drive mechanism (IDM) that is actuated using piezoelectric
device. The trajectory tracking performance of the modelled micro
robot is initially experimented via a conventional proportionalintegral-
derivative (PID) controller in which the dynamic response of
the robot system subjected to different input excitations is
investigated. Subsequently, a robust intelligent method known as
active force control with fuzzy logic (AFCFL) is later incorporated
into the PID scheme to enhance the system performance by
compensating the unwanted disturbances due to the interaction of the
robot with its environment. Results show that the proposed AFCFL
scheme is far superior than the PID control counterpart in terms of
the system-s tracking capability in the wake of the disturbances.
Abstract: The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.