Design, Simulation, Analysis and Optimization of PID and Fuzzy Based Control Systems for a Quadcopter

Unmanned aerial vehicles or drones are becoming one of the key machines/tools of the modern world, particularly in military applications. Numerous research works are underway to explore the possibility of using these machines in other applications such as parcel delivery, construction work, hurricane hunting, 3D mapping, protecting wildlife, agricultural activities, search and rescue, etc. Since these machines are unmanned vehicles, their functionality is completely dependent upon the performance of their control system. This paper presents a comprehensive approach for dynamic modeling, control system design, simulation and optimization of a quadcopter. The main objective is to study the behavior of different controllers when the model is working under linear and/or non-linear conditions, and therefore, to define the possible limitations of the controllers. Five different control systems are proposed to improve the control performance, mainly the stability of the system. Additionally, a path simulator was also developed with the intention of describing the vehicle’s movements and hence to detect faults intuitively. The proposed PID and Fuzzy-PD control systems showed promising responses to the tests carried out. The results indicated the limits of the PID controller over non-linear conditions and the effectiveness of the controllers was enhanced by the implementation of a genetic algorithm to autotune the controllers in order to adapt to changing conditions.

Dynamic Modeling and Control of a Parallel Mechanism Used in the Propulsion System of a Biomimetic Underwater Vehicle

Incorporation of parallel mechanisms inside propulsion systems in biomimetic autonomous underwater vehicles (BAUVs) is a novel approach for motion generation. The vehicle to which the studied propulsion system is implemented presents thunniform locomotion, and its thrust depends mainly on the oscillation from its caudal fin. This paper describes the kinematic and dynamic modeling of a 3-DOF spherical 3UCU-1S parallel robotic system to which the caudal fin of a BAUV is attached. Lagrange formalism was employed for inverse dynamic modeling, and its derivation is detailed throughout this paper. Additionally, the implementation of control strategies to compute forces required to actuate limbs to change platform’s flapping frequencies was developed. Four controllers: classic PD, a feedforward plus feedback PD, an adaptive Fuzzy-PD, and a feedforward plus Fuzzy-PD were compared in different simulations. Results showed that augmenting oscillating frequencies (from 0.5 to 5 Hz) increased the complexity of the path tracking task, where the classic control strategy (i.e., PD) was not sufficient, reaching percentage errors above 9%. Control strategies using feedforward terms combined with adaptive feedback techniques reduced tracking error below 2% even during the presence of external disturbances.