There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

We present a robust adaptive second-order sliding mode controller that rejects external disturbances and uncertainties to improve the tracking performance of attitude and altitude in a quadcopter based on a Proportional–Integral–Derivative sliding surface. The algorithm provides a rapid adaptation and strict robustness of the flight control for the vehicle under the effect of perturbations. The proposed controller design is based on the theory of second order sliding mode technique that eliminates the chattering phenomenon present in first-order sliding mode controllers. In addition, we derive an adaptive law from the Lyapunov stability to ensure the robust control for the quadcopter even without knowing the upper bound for disturbances. Applying the same external disturbances, we use a numerical simulation to compare our algorithm to recent alternatives, such as normal adaptive sliding mode control, super-twisting sliding mode control, modified super-twisting sliding mode control, and nonsingular terminal sliding mode control. The results demonstrate the effectiveness of our proposed algorithm.

Quadcopter Robust Adaptive Second Order Sliding Mode Control Based on PID Sliding Surface

Abstract Over the past decade, unmanned aerial vehicles (UAVs) have received a significant attention due to their diverse capabilities for non-combatant and military applications. The primary aim of this study is to unveil a clear categorization overview for more than a decade worth of substantial progress in UAVs. The paper will begin with a general overview of the advancements, followed by an up-to-date explanation of the different mechanical structures and technical elements that have been included. The paper will then explore and examine various vertical take-off and landing (VTOL) configurations, followed by expressing the dynamics, applicable simulation tools and control strategies for a Quadrotor. In conclusion to this review, the dynamic system presented will always face limitations such as internal and/or external disturbances. Hence, this can be minimised by the choice of introducing appropriate control techniques or mechanical enhancements. 

/pdf/a-review-of-quadrotor-unmanned-aerial-vehicles-applications-2x6q1h8m.pdf

A Review of Quadrotor Unmanned Aerial Vehicles: Applications, Architectural Design and Control Algorithms

http://www.cell.com/article/S2405844022006879/pdf

Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

Quadcopter unmanned aerial vehicles continue to play important roles in several applications and the improvement of their control performance has been explored in a great number of studies. In this paper, we present an altitude control algorithm for quadcopters that consists of a combination of nonlinear and linear controllers. The smooth transition between the nonlinear and linear modes are guaranteed through controller gains that are obtained based on mathematical analysis. The proposed controller takes advantage and addresses some known shortcomings of the conventional proportional–integral–derivative control method. The algorithm is simple to implement, and we prove its stability through the Lyapunov theory. By prescribing certain flight conditions, we use numerical simulations to compare the control performance of our control method to that of a conventional proportional–derivative–integral approach. Furthermore, we use a DJI-F450 drone equipped with a laser ranging sensor as the experimental quadcopter platform to evaluate the performance of our new controller in real flight conditions. Numerical simulation and experimental results demonstrate the effectiveness of the proposed algorithm.

https://www.mdpi.com/2076-3417/9/10/2122/pdf

Improved Altitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles

This article proposes a comparative method to assess the performance of artificial neural network’s direct inverse control (DIC-ANN) with the PID control system. The comparison served as an analysis tool to assess the advantages of DIC-ANN over conventional control method for a UAV attitude controller. The development of ANN method for UAV control purposes arises due to the limitations of the conventional control method, which is the mathematical based model, involving complex expression, and most of them are difficult to be solved directly into analytic solution. Although the linearization simplified the solving process for such mathematical based model, omitting the nonlinear and the coupling terms is unsuitable for the dynamics of the multirotor vehicle. Thus, the DIC-ANN perform learning mechanism to overcome the limitation of PID tuning. Therefore, the proposed comparative method is developed to obtain conclusive results of DIC-ANN advantages over the linear method in UAV attitude control. Better achievement in the altitude dynamics was attained by the DIC-ANN compared to PID control method.

/pdf/neural-network-control-system-of-uav-altitude-dynamics-and-4sqdf8eww9.pdf

Neural Network Control System of UAV Altitude Dynamics and Its Comparison with the PID Control System

Research on multicopter nowadays is rapidly growing in many fields of application. One of the problems in the multicopter application is the ability to lift a heavy load that requires the careful design and selection of the proper type of multicopter for its ability in carrying out the missions involving the heavy load lifting. One type of multicopters that is often used is hexacopter. This paper describes the design of hexacopter that lift a heavy load. The design is done by calculating and analyzing the constraints and the criteria by the aid of software. The first flight experiment proved the capability of the designed heavy-lift hexacopter to fly in stable attitude while carrying a heavy load.

Design and development of heavy-lift hexacopter for heavy payload

This article proposes a practical new method to obtain the moment of inertia of UAV, named ARES. The ARES method simultaneously determined all the elements of UAV's Tensor of Inertia, i.e. the moments and the products of inertia through algebraic solving. The ARES method directly uses the UAV Flight Data to accommodate accuracy issues of modeling such as vehicle's geometrical imperfection; manufacturing defect, any non-symmetrical due component placement, etc. This proposed method was applicable for various purposes of UAV modeling e.g. flight control design, flight dynamics analysis, etc. Conventionally, UAV moments of inertia were estimated by tabulating, CAD-based, or pendulum method. Since these existing methods were constrained by the accuracy and practical issues, we develop the ARES method which using the UAV's flight data to resolve both issues. After undergone appropriate mathematical strategies, the ARES produce a linear construction for algebraic solving technique. The implementation the proposed method in the quadrotor flight data showing that ARES are successfully measured the asymmetrical terms which important for nonlinear controlling, that previously neglected by the conventional methods. Thus, the ARES estimates the UAV Tensor of Inertia in holistic, sophisticated and practical fashion.

Estimating the UAV moments of inertia directly from its flight data

Adequate models of UAV's dynamics were important for a successful aerial mission. Such adequate model of flight dynamics were required to assemble a good flight controller. For modeling purposes, the state space methods have been applied in various system dynamics. In the conventional modeling, the UAV's state space constructed from the first principle which involved efforts of measurement and deals with uncertainties and errors in sensors reading. Hence, this work proposes a simplified method to identify the UAV state space directly from its flight data. The flight data were directly used to overcome the uncertainties issues. As the conclusion, this method were able to ommit the requirement for moments of inertia measurement compared to previous technique of State Space modeling.

Determining the UAV State Space Rotational Dynamics Model Using Algebraic Inversion Technique

This paper addresses the construction of the quadrotor State Space from its flight data. Using numerical simulation, the flight data generated to be processed then obtaining the elements of the State Space matrices. In conventional fashion, one constructs the state space from physical properties measurement such as weight, moments of inertia, vehicle dimension, etc. On the contrary, using the flight data to obtain the State Space omitted the requirement of those physical properties. The method was already described in the authors previous publication, and being assessed in this manuscript. To bring the simulation closer to the real quadrotor dynamics, the complete nonlinear attitude equation of motion applied in the vector form to be solved numerically. The simulated flight data then sampled to mimic the actual measurement process in UAV. The sampled flight data inputted to the coefficient matrix for algebraic inversion to obtain the elements of the UAV state space.

Jemie Muliadi

Papers

Neural Network Control System of UAV Altitude Dynamics and Its Comparison with the PID Control System

Design and development of heavy-lift hexacopter for heavy payload

Estimating the UAV moments of inertia directly from its flight data

Determining the UAV State Space Rotational Dynamics Model Using Algebraic Inversion Technique

Assessing the method of state space determination from the quadrotor flight simulation