Ahmed Nasr Ouda

The huge spreading of COVID-19 viral outbreak to several countries motivates many of the research institutions everywhere in numerous disciplines to try decreasing the spread rate of this pandemic. Among these researches are the robotics with different payloads and sensory devices with wireless communications to remotely track patients’ diagnosis and their treatment. That is, it reduces direct contact between the patients and the medical team members. Thus, this paper is devoted to design and implement a prototype of wireless medical robot (MR) that can communicate between patients and medical consultants. The prototype includes the modelling of a four-wheeled MR using systems' identification methodology, from which the model is utilized in control design and analysis. The required controller is designed using the proportional-integral-derivative (PID) and Fuzzy logic (FLC) techniques. The MR is equipped onboard with some medical sensors and a camera to acquire vital signs and physical parameters of patients. The MR model is obtained via an experimental test with input/output signals in open-loop configuration as single–input–single–output from which the estimation and validation results demonstrate that the identified model possess about 89% of the output variation/dynamics. This model is used for controllers' design with PID and FLC, the response of which is good for heading angle tracking. Concerning the medical measurements, more than two thousand real recorded Photo-plethysmography (PPG) signals and Blood Pressure (BP) are used to find the appropriate BP estimation model. Towards this objective, some experiments are designed and conducted to measure the PPG signal. Finally, the BP is estimated with mean absolute error of about 4.7 mmHg in systolic and 4.8 mmHg in diastolic using Artificial Neural Network.

This paper describes the design and implementation of PID and fuzzy logic controllers for tracking the desired heading angle for a scaled autonomous multi-wheeled combat vehicle (AMWCV). The challenge of designing these control systems is to control the steering of the front four wheels individually in order to obtain the correct heading angle of the vehicle. The performance of the developed controllers is validated in the presence of noise and disturbance in order to evaluate the irrobustness. A processor-in-the-loop (PIL) co-simulation is conducted to permit and achieve amore realistic situation where the developed control algorithms are evaluated while running on a dedicated processor. The obtained results from both simulation and PIL are compared. This comparison will demonstrate the controller effectiveness in tracking the desired heading angles.

In this paper, a study of open and closed loop scalar control of three phase induction motor (3-ph IM) for electric vehicle (EV) applications are presented. In scalar control, the air gap flux of the induction motor (IM) is kept constant by setting the ratio between stator voltage and frequency always constant. The stator voltage and frequency is controlled via a voltage source inverter using pulse width modulation (PWM) technique. The MATLAB/SIMULINK software package is used to simulate the EV driven by a 3-ph IM to investigate the effectiveness of the proposed control techniques. The simulation results show that the open loop scalar control is suitable for low accuracy EV applications while the closed loop is suitable for high accuracy applications.

This paper presents modeling for an air-to-air guided missile. The model describes a detailed missile system including the aerodynamics of the missile, the set of equations of motion and the autopilot. Possible tactical situations are applied on the model and included in the paper. System identification is also carried out to help in our research goals which include designing a new controller that takes into consideration the problems we faced using the current one. Our design is in a modular form based on previous work which is the base for a lot of missile systems' simulation software. Our model was designed using Simulink and MATLAB environments. Our work is characterized by using classical controller as an autopilot instead of complex controllers and maintaining accepted results in many possible tactical situations.

Autonomous vehicle technologies are receiving great attention with increasing demands for autonomy for both civilian and military purposes. In previous work (Mohamed et al., 2016), the recent developments in autonomous vehicles in the fields of advanced control, perception and motion planning techniques is surveyed. In this paper, the state of research w.r.t. autonomous vehicles from different perspectives will be described. The capability to integrate data and knowledge from different sensors are essential. In addition, advanced perception techniques and the capability to locate obstacles and targets are necessary to properly operate autonomous systems. Moreover, achieve reliable levels of performance by determining the faults and enabling the system to operate with these faults in mind. Fault tolerance is required to analysing the measured input/output signals of the system. This paper will briefly survey the recent developments in the field of autonomous vehicles from the perspectives of sensor fusion, computer vision, system identification and fault tolerance.

This paper proposed a robust autopilot design for air to air guided missile and a Hardware-in-the-Loop (HIL) simulation which is based on the derived missile-control transfer functions and the 6DOF simulation model. The introduced autopilot is implemented within the 6DOF simulation to check its robustness against non-modeled dynamics and nonlinearities. The nonlinear 6DOF equations of motions are solved together to obtain the pitch and yaw transfer functions. The missile equations are described in the form of modules programmed within the C++ environments to form the baseline for subsequent design and analysis. Furthermore, a comparison between both our previous work, i.e. classical and robust autopilot, are justified via HIL simulation. The simulation results demonstrated the robustness capability in presence disturbance and noise.