Adaptable fuzzy control solutions for driving systems working under continuously variable conditions

Based on our previous research results partially published in [1], [2], [3] and [4], the paper presents a survey on dedicated control solutions for driving systems working under continuously variable conditions: variable reference input (speed), variable moment of inertia and variable load disturbance. The solutions were validated using numerical simulation and tested on a laboratory equipment [5]. The structures employ the switching between different Model-Based (MB) control algorithms; due on the simplicity in adaptation, different fuzzified Takagi-Sugeno control solutions are offered. A hybrid Takagi-Sugeno PI-neuro-fuzzy controller is presented. The solutions are based on a classical cascade control structure with an inner current controller and an external speed control loop with bump-less switching between the control algorithms. Our solutions are representative for mechatronics applications.