In recent decades, there has been a constant increase in the use of unmanned aerial vehicles (UAVs). There has also been a huge growth in the number of control algorithms to support the many applications embodied by the vehicles, including challenges and open issues to develop. This paper focuses on three major classes of control methods applied to quadrotors in order to create an open-source model based on the Arduino Mega that allows for the derivation and design of quadrotor control strategies. We consider the perspective classes, including linear, nonlinear, and intelligent methods representing in details with applications in developing an open-source controller for the quadrotor using the Arduino Mega and the BNO055 9 DOF sensor. We propose Proportional Integral Derivative (PID), backstepping integrator, and model predictive control (MPC) to track a generated Lissajous curve for surveillance. Simulations in the Matlab–Simulink environment with 3D visualization of a developed quadrotor model using CAD software, with robustness and performance discussion, are provided. Our experimental work is developed with an extensive illustration of the hardware and algorithm design and by demonstrating the effectiveness of the proposed architectures. The results show promise in practical and in intelligent applications.

Over the decades, with the advancement of science and technology, wheelchairs have undergone remarkable changes, such as controlling an electrical wheelchair by using brain signals. However, existing electrical wheelchairs still need improvements in terms of energy management. This paper proposes an hybrid Solar-Radio frequency (RF) harvesting system able to supply power for the continuous and effective operation of electrically powered wheelchairs. This system can simultaneously harvest power from RF and solar source that are both available in the surrounding environment. A maximum power point tracking (MPPT) and a boost converter are exclusively employed for the standalone solar system while the standalone RF system is equipped with a 9-stage voltage multiplier (VM). The voltage level for the charging process is obtained by adding the output voltage of each source. In addition, a current booster and a stabilizer are used to reach the required level of current and pin the charging voltage to a stable level, respectively. Simulation results show how the hybrid system is better and more stable when the boost current and stabilizer are used in the charging system. Moreover, we also provide some analytic results to prove the advantages of this system.

This paper proposes the application of the Sequential Quadratic Programming (SQP) algorithm to control a group of omnidirectional mobile robots using the Leader-Follower model. The method includes predicting the group’s kinematics, formulating a distributed model predictive control (DMPC) problem with a cost function comprising components for formation maintenance, trajectory tracking, and collision avoidance. The cost function is then optimized in real time using the SQP algorithm. In simulations, Gaussian noise is introduced into the states and control signals to evaluate the method’s effectiveness under real-world deployment conditions.

In this article we propose a method of using the extended Kalman filter combined with an inertial navigation system and a camera to assist in determining the location and calculate the parameters of a helicopter. These observations are combined with an inertial measurement instrument which uses the Kalman filter to collect accurately and promptly information about the location of a plane. The algorithms is simulated on Simulink and hardened by using dsPIC33F256 chip.