Position Control of Vtol System Using Anfis via Hardware in the Loop

Abstract

Electric motors have been widely applied in various equipment. One application is found in Unmanned Aerial Vehicles (UAVs). An electric motor speed control system that can balance the aircraft's position is one of the mandatory features that must be owned by the aircraft. The position balancer control also supports the Vertical Take-Off Landing (VTOL) system. This study's VTOL position control system uses Hardware-in-the-loop (HIL) method with MATLAB Simulink and Arduino. ANFIS (Adaptive Neuro-Fuzzy Inferences System) is used as a position control algorithm. The controller performance is compared with conventional PID and FLC (Fuzzy Logic Controller). The system is tested as an initial position variation and loading test. The experiment shows that HIL can help fast prototyping by faster changes in the controller algorithms and is easy to program. The result is varied in each experiment. In the ISE (Integral Square of Error) point of view, ANFIS is better than PID by 100 % and has a very small difference from FLC in the initial position test. ANFIS is better by 95.44% and 4.56% compared with PID and FLC in the loading test, respectively.

Interface Design of DJI Tello Quadcopter Flight Control

“…Some of the components used to design a quadcopter consist of the flight controller, brushless motors, quadcopter frames, electronic speed controllers (ESCs), accelerometers, inertial measurement units (IMU) sensors, and Global Positioning System (GPS) [8]. The advantage of a quadcopter is its ability to take off and land which is known as vertical take-off landing (VTOL) [9]- [10].…”