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The quadrotor unmanned aerial vehicles (UAV) are rich system with attractive and challenging properties such as nonlinearities and underactuated dynamics, which motivates researchers to design advanced and robust control algorithms. In this paper, we contribute to a further improved design of quadrotor UAV. The quadrotor dynamics and kinematics equations are briefly presented. Then, an improved integral sliding mode controller (ISMC) has been proposed and applied within an inner loop to stabilize and track the quadrotor attitude at the desired values. The aim is to enhance the performance of the ISMC controller by eliminating the chattering problem, meanwhile maintaining the trajectory tracking in a robust fashion. In our design, the switching function (sign(s)), causing the chattering, is replaced by the approximated functions (tan h, error, saturation, quasi-sliding mode method) in the ISMC control law. PD controller is applied as an outer loop controller to enable the quadrotor to track the desired position. The performance of the proposed ISMC controller is studied with regard to the chattering attenuation and trajectory tracking robustness and tested by simulation MATLAB/SIMULINK. Finally, a comparison with the switching function (sign(s)) is performed to alleviate the superior performance of the proposed design.

Recently, soft robotics represents a new era of advanced robotics systems. Based on the flexible nature of soft robots, they are more adequate to have safe interaction with humans and handle complex or delicate objects. Due to the nature of soft robotics, there is a crucial need to propose new designs, fabrication, and control systems suitable for the flexibility nature. In this research project, a novel three parallel soft muscle actuator is proposed. The proposed design and analytical models for predicting actuation behavior are based on a set of design parameters. First, the actuator modules are parametrically designed and identified with the aid of finite element analysis. The simulation was run at various pressures. The tip location was determined from the kinematic model as a function of pressure. The inverse kinematic model was built using ANN to calculate the pressure at the soft muscle tip. The MSE was 2.6778e-8 due to the ANN model's accuracy.

The quadrotor unmanned aerial vehicles (UAV) systems have been getting more focus recently from researchers and engineers due to their outstanding impact and wide range of applications either in civilian or military. In this article, the sliding mode controller has been designed to control the attitude of the quadrotor as the inner loop controller. The major aim in this research is to reduce the chattering associated with the conventional sliding mode control (SMC), by implementing the adaptive fuzzy gain scheduling SMC technique (AFGS-SMC). Meanwhile, the performance of the proposed control has been evaluated in the presence of the model parameters uncertainty. The PD controller has been implemented as an outer loop controller to control the quadrotor position and supply the inner loop proposed controller (AFGS-SMC) with the desired generated quadrotor's attitude. Finally, the performance of the proposed AFGS-SMC controller has been evaluated by simulation in Matlab/Simulink platform, and compared with the classical SMC, in terms of chattering attenuation and robust trajectory tracking in the presence of the parameter uncertainty in the mass of the quadrotor UAV.

Quadcopter unmanned aerial vehicles (UAVs) systems are receiving remarkable attention from researchers due to their daily use in numerous applications, particularly at the current time where UAVs are playing a significant role in combating the COVID-19 pandemic. This paper is concerned with the problem of UAV navigation and control in the presence of uncertainty and external disturbances. It addresses this issue by proposing an improved adaptive sliding mode control (IASMC). Improved control law generates an adaptive switching gain achieving fast adaptation and robustness against both parameter uncertainties and external disturbances. Simultaneously, the control law allows for maintaining robust trajectory tracking with chattering attenuation. The performance of the proposed IASMC controller has been evaluated using a Matlab/Simulink platform. The obtained simulation results showed that the proposed IASMC control scheme as an inner loop controller is robust when dealing with uncertainties and can effectively track the desired trajectories while significantly attenuating the well-known chattering introduced by the SMC controller.

Currently, the quadcopter Unmanned Aerial Vehicles (UAVs) are playing a significant role in combating the COVID-19 pandemic crisis, which induced the researchers to design robust control techniques. In this paper, a fuzzy PID controller is designed to stabilize and/or track the desired trajectory of the quadcopter UAV. The mathematical model of the quadcopter UAV has been briefly presented, where it has been divided into two portions, the position dynamic and the attitude dynamic subsystems. Subsequently, a robust fuzzy PID controller has been designed for both the inner loop and outer loop to control and stabilize the position and the attitude of the quadcopter, which adaptively manipulate the system’s input based on the tracking error. The proposed controller is benchmarked with the conventional PID controller to show the robustness of the fuzzy PID controller. Fuzzy PID controller has been verified through simulation work utilizing Matlab/Simulink, where better performance is achieved compared with the conventional PID controller. It is found that the errors in the quadcopter’s attitude and position have been significantly reduced through using fuzzy PID controller by 70% and 87%, respectively.

Any large scale cargo port requires the use of container cranes for loading of intermodal containers as well as unloading them. The operator of such a large crane must be appropriately trained to prevent any accidents at the cargo port. This should be achieved by training crane operators on all the protocols of crane operation with significant hours of practice. The aim of this project is to develop a virtual reality (VR) simulation for operator training of container cranes which are remotely controlled, situated at the cargo ports. The simulation consists of a virtual control room equipped with joysticks and display screens, container crane, container ships, trucks and a cargo port environment. We used an actual super post-Panamax quay crane as a reference model for this simulation. The project has been built using Unity3d for the programming and 3DSMAX for the designing of models. The virtual joysticks in the simulation can be interacted by using the Oculus Rift VR setup thus allowing to maneuver the crane and the container load in all three dimensions. This paper mainly discusses the structure and implementation of the virtual reality simulation for crane operator training, along with a proposal for further improvements.

In this paper, an adaptive sliding mode (ASMC) controller designed for a multi-inputs and multi-outputs (MIMO) robotic arm nonlinear manipulator system. The controller is designed based on Lyapunov theorem to achieve a robust trajectory tracking taking into consideration the system’s uncertainties in addition to reducing the effect of chattering problem associated with the traditional sliding mode control. It’s found that, even in the presence of the parameters’ uncertainties, the performance of the proposed controller for the trajectory tracking is robust. Furthermore, chattering is significantly reduced.

The quadrotor unmanned aerial vehicles (UAV) systems have been getting recently more focus from researchers and engineers due to its outstanding impact and broad applications in civilian and military sectors. In this paper, the quadrotor dynamic model has been introduced. Firstly, the sliding mode controller has been designed to control the attitude of the quadrotor as the inner loop controller. This research aims to reduce the chattering associated with the conventional sliding mode control (SMC), by applying the adaptive fuzzy gain scheduling SMC technique (AFGS-SMC). Secondly, PD controller has been implemented as an outer loop controller to control the quadrotor position. Finally, the performance of the proposed AFGS-SMC controller has been evaluated by simulation Matlab/Simulink, and compared with the conventional SMC, in terms of chattering attenuation and trajectory tracking.

In this article, the adaptive sliding mode controller (ASMC) is developed for the quadrotor attitude subsystem. The proposed ASMC controller aims to reduce/decrease the unwanted chattering phenomena associated with the conventional sliding mode controller, and meanwhile achieving a robust trajectory tracking for the attitude. The stability of the proposed (ASMC) controller has been verified based on Lyapunov stability theorem. The quadrotor UAV model and the performance of the proposed controller have been simulated and tested by simulation using MATLAB/SIMULINK environment. The simulation result is proof that the chattering has been reduced significantly.

A robotic arm having two links is considered in this report for modeling and control. First the dynamic model of the robot is obtained using the so-called Lagrange equation, then a robust control strategy based on the conventional sliding mode control is introduced to control the motion of the robot at specific position for pick and place tasks along with PID control scheme. The results of the two controllers are compared. From the simulation results the SMC is found to be superior to the PID controller in term of fast and robust response yet with higher control input. High join speeds are observed in case of SMC which are related to the high control signals.