On the Synthesis of a Linear Quadratic Controller for a Quadcopter

This paper discusses about synthesizing a state-feedback controller for a quadcopter based on an optimal linear quadratic control method. The resulting flight control system enables the quadcopter to maintain stability and to track a reference input. The solution to this control problem involves solving an algebraic Riccati equation. The reference-input tracking capability is simulated to show the capability of the quadcopter flight control system

Hover Position of Quadrotor Based on PD-like Fuzzy Linear Programming

The purpose of this paper is to present the altitude control algorithm for quadrotor to be able to fly at a particular altitude. Several previous researchers have conducted studies on quadrotor altitude by using PID control but there are problems in the overshoot and oscillation. To optimize the control, tunning on PID algorithm must be first conducted to determine proportional and derivative constants. Hence, the paper presents altitude control modification by using PID-like fuzzy without tuning. The PID algorithm is a control algorithm for linear systems. While, system to be controlled is a non-linear, so that linearization is needed by using equilibrium. The proposed algorithm is a modification of the PID algorithm used as an altitude control which enables quadrotor to be stable when hovering. The algorithm used is not PID algorithm with tuning using fuzzy, but this is a single input single output (SISO) control PID-like fuzzy linear programming. The result of the research shows that quadrotor can hover in a rapid raise time, steady state and settling time without performing overshoot and oscillation

ℒ1 adaptive control of quadrotor UAVs in case of inversion of the torque direction

This paper presents a method for fault tolerant control of quadrotor UAVs in case of inversion of the torque direction, a situation that might occur due to structural, hardware or software issues. The proposed design is based on multiple-model ℒ1 adaptive control. The controller is composed of a nominal reference model and a set of degraded reference models. The nominal model is that with desired dynamics that are optimal regarding some specific criteria. In a degraded model, the performance criteria are reduced. It is designed to ensure system robustness in the presence of critical failures. The controller is tested in simulations and it is shown that the multiple model ℒ1 adaptive controller stabilizes the system in case of inversion of the control input, while the ℒ1 adaptive controller with a single nominal model fails

Design, Modeling, and Control of a Flying-Insect-Inspired Quadrotor with Rotatable Arms

Aerial manipulation and delivery using quadrotors are becoming more and more popular in recent years. However, the displacement of the center of gravity (CoG) is a common issue experienced by these applications due to various eccentric payloads carried. Conventional quadrotors with eccentric payloads are usually stabilized by robust control strategies through adjusting rotation speeds of BLDC motors, which has negative effects on stability and energy efficiency of quadrotors. In this thesis, a flying-insect-inspired quadrotor with rotatable arms is proposed. With four rotatable arms, the proposed quadrotor can automatically estimate the displacement of the CoG and drive the four arms to their optimal positions during flight. In this way, the proposed quadrotor can move its symmetric center to the CoG of the quadrotor with the eccentric payload to increase its stability and energy efficiency. The design, dynamics modeling, and control strategy of the proposed quadrotor are presented in this thesis. Both calculation and experiment results show that the proposed quadrotor with rotatable arms has better flight performance of stability and energy efficiency than the conventional quadrotor with fixed arms

Automatic control of a multirotor

Objective of this thesis is to describe the design and realisation phases of a multirotor to be used for low risk and cost aerial observation. Starting point of this activity was a wide literature study related to the technological evolution of multirotors design and to the state of the art. Firstly the most common multirotor configurations were defined and, according to a size and performance based evaluation, the most suitable one was chosen. A detailed computer aided design model was drawn as basis for the realisation of two prototypes. The realised multirotors were “X-shaped” octorotors with eight coaxially coupled motors. The mathematical model of the multirotor dynamics was studied. “Proportional Integral Derivative” and “Linear Quadratic” algorithms were chosen as techniques to regulate the attitude dynamics of the multirotor. These methods were tested with a nonlinear model simulation developed in the Matlab Simulink environment. In the meanwhile the Arduino board was selected as the best compromise between costs and performance and the above mentioned algorithms were implemented using this platform thanks to its main characteristic of being completely “open source”. Indeed the multirotor was conceived to be a serviceable tool for the public utility and, at the same time, to be an accessible device for research and studies. The behaviour of the physical multirotor was evaluated with a test bench designed to isolate the rotation about one single body axis at a time. The data of the experimental tests were gathered in real time using a custom Matlab code and several indoor tests allowed the “fine tuning” of the controllers gains. Afterwards a portable “ground station” was conceived and realised in adherence with the real scenarios users needs. Several outdoor experimental flights were executed with successful results and the data gathered during the outdoor tests were used to evaluate some key performance indicators as the endurance and the maximum allowable payload mass. Then the fault tolerance of the control system was evaluated simulating and experimenting the loss of one motor; even in this critical condition the system exhibited an acceptable behaviour. The reached project readiness allowed to meet some potential users as the “Turin Fire Department” and to cooperate with them in a simulated emergency. During this event the multirotor was used to gather and transmit real time aerial images for an improved “situation awareness”. Finally the study was extended to more innovative control techniques like the neural networks based ones. Simulations results demonstrated their effectiveness; nevertheless the inherent complexity and the unreliability outside the training ranges could have a catastrophic impact on the airworthiness. This is a factor that cannot be neglected especially in the applications related to flying platforms. Summarising, this research work was addressed mainly to the operating procedures for implementing automatic control algorithms to real platforms. All the design aspects, from the preliminary multirotor configuration choice to the tests in possible real scenarios, were covered obtaining performances comparable with other commercial of-the-shelf platforms

Linear quadratic control for quadrotors UAVs dynamics and formation flight

Cooperative control of Unmanned Aerial Vehicles (UAVs) is currently being researched for a wide range of applications. Applicability of aerial unmanned systems might be increased by formation flight. After a necessary overview of quadrotor flight dynamics and linear quadratic control fundamentals, this control technique is applied to the full quadrotor dynamics. Then the more recent and challenging neural networks based control strategy is introduced from a theoretical perspective and applied to the quadrotor vertical dynamics; the results are compared with the relevant linear quadratic controlled behaviour. Finally, based on the developed single-quadrotor control architectures, a practical leader-follower formation concept is simulated, both for the linear quadratic and the neural networks based approach

Linear quadratic control for quadrotors UAVs dynamics and formation flight

Cooperative control of Unmanned Aerial Vehicles (UAVs) is currently being researched for a wide range of applications. Applicability of aerial unmanned systems might be increased by formation flight. After a necessary overview of quadrotor flight dynamics and linear quadratic control fundamentals, this control technique is applied to the full quadrotor dynamics. Then the more recent and challenging neural networks based control strategy is introduced from a theoretical perspective and applied to the quadrotor vertical dynamics; the results are compared with the relevant linear quadratic controlled behaviour. Finally, based on the developed single-quadrotor control architectures, a practical leader-follower formation concept is simulated, both for the linear quadratic and the neural networks based approach