Controlling the Rolling Position of a Spherical Robot Using Fuzzy-Based Technique with IoT Application

This paper presents the organized design and analysis in steps towards achieving the best fuzzy-based controller for Spherical Robot (SR) rolling mechanism and tested with monitoring applications using IOT. The SR was tested with different closed loop performance analysis using fuzzy-based controller where different types of Proportional-Integral-Derivatives (PID)-based Fuzzy Logic Controller (FLC) were designed for the position controller of the rolling mechanism. The design was started with an uncompensated Proportional (P)-type, followed with the Proportional-Derivative (PD)-type, Proportional-Integrator (PI)-type, and Proportional-Integrator-Derivative (PID)-type of FLC. Although it is common to conclude PID-based is superior in many applications but this research has proven others, since this type of robot is known to be nonlinear in nature. All controllers were designed using triangular membership function and Gaussian membership function with Mamdani method applied for its Fuzzy Inference System (FIS). PD-type FLC with triangular MF has outperformed other types of PID-based FLC for rolling position control and therefore was chosen for the hardware implementation. The Particle Swarm Optimization (PSO) algorithm was developed to systematically tune the input and output gains of the PD-type FLC for further performance enhancement which later shown that rise time and settling time of the rolling position have significantly reduced by 81.4 % and 82.6 % respectively. The optimized controller has been integrated with the SR equipped with many sensors for surveillance and monitoring using IOT application.