This paper reports a current study on modeling and simulation of adaptive Active Force Control (AFC) based scheme embedded with an artificial neural network (ANN) and/or fuzzy logic (FL) in response manipulations of the twin rotor multi-input multi-output (MIMO) system (TRMS). TRMS is well known for its non-linear behaviour and common classical control scheme such as Proportional-Integral-Derivative (PID) would not be adequate to compensate disturbances. The disturbances in this case were as the results of non-linear external and internal parametric changes, namely angular momentum and couple reactions between the two axes of TRMS. The adaptive control algorithm was proposed in both pitch and yaw to generate an optimum control gain for both responses, simulated viz. MATLAB/SIMULINK software Package. The ANN and FL were integrated into the scheme and act as optimum control algorithm in catalyzing the performance of the TRMS. The results from hybrid conditions of PID-AFC, PID-AFC-ANN and PID-AFC-FL respectively were observed and analyzed. From performance evaluation, PID-AFC-FL scheme has demonstrated a potentially robust and effective manipulating capability in trajectory tracking.
Autonomous Unmanned Aerial Vehicle (UAV) in the form of multi-rotor system is having a great potential in various applications such as disaster management (as first response system) and surveillance. It is known that conventional helicopter system, capable of hovering, is practical and reliable as many applications have confirmed its capabilities. However it is only achievable once highly optimized control architecture is realized. The objective of the research presented in this paper is, to develop a small multi rotor UAV system that is able to autonomously flying from one way point to another in a stable manner. This small UAV is termed as Mini (or Micro) Aerial Vehicle (MAV). In this project, a four-rotor system was developed, and becoming the platform of various sensors system, flight control system, and electric propulsion system. The MAV was programmed to be able to lift off and fly to waypoints making use of GPS. This paper presents the architecture of the MAV and its autonomous flight.
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