Control Design for Unmanned Aerial Vehicles with Four Rotors

Abstract

Altitude and attitude controlled quadcopter model is used for the behavior and control algorithm testing, before the implementation on the experimental setup. The main objective is the control system design which will achieve good task performance in the combination with the quadcopter dynamic model. Also, for the control model, it is important to be relatively easy to modify for the use of other control algorithms and to be easy to implement on the experimental setup. At the beginning of this article, the control system design process is described. Quadcopter dynamics equations are simplified by applying several assumptions and in that form are used for the controller synthesis. Quadcopter control system is split into inner and outer control loop because the quadcopter is underactuated system which means that the direct control of all of the degrees of freedom is not possible. In the second part, the PI-D control algorithm is described which is applied on the simplified quadcopter dynamic model. The inner loop controls roll, pitch and yaw angles together with the quadcopter altitude. Its outputs are four control variables. Outer loop controls quadcopter X and Y position. Its outputs are roll and pitch desired angles. Regulated quadcopter model behavior is shown for the three types of task. First, the achieving of position in space is simulated. Second, the reference trajectory tracking is shown. Last task shown is the reference trajectory tracking with added periodical disturbances. Simulations show bounded positions error of the regulated quadcopter system using PI-D controller for the different types of tasks performed under different conditions.

Tuning of PID Controllers for Quadcopter System using Hybrid Memory based Gravitational Search Algorithm – Particle Swarm Optimization

“…4 has the advantage that parameters (Kp, Ki, Kd) are easy to tune, which is simple to design and has good robustness. However, the quadcopter includes non-linearity in the mathematical model and may include some inaccurate modeling of some of the dynamics, which will case bad performance of the control system, thus it is needed form the designer to be careful when neglecting some effects in the model or simplifying the model [9]. Stabilization is very important for an under-actuated system like a quadrotor, as it is inherently unstable due to its six degrees of freedom and four actuators.…”

“…Also regarding the control of quadcopter, there is a good amount of research done both in linear and nonlinear control methods, [8]. However, for practicality the linear controller especially PID perform better in practical implementation and that is the reason PID was used as the controller for the quadcopter in this work [5,9,10]. In addition, some researchers work on the stabilization of quadcopter that means inner loop [11,13].…”

Nonlinear PID controller design for a 6-DOF UAV quadrotor system

“…Many researchers studied the quadrotor control design with different types of controllers. One of the most used controllers is the LPID control because of its simplicity [13][14][15][16] but on the other hand it has many disadvantages: 1) sometimes it gives a high control signal due to the fact of windup, thus, overshooting and continuing to increase as the accumulated error is unwound (offset by errors in the other direction, 2) the differentiator Email address: ibraheem.i.k@ieee.org (Ibraheem Kasim Ibraheem) leads to noise amplification. Other used controllers like: NLPID control [17] and [18], LQR [19], geometric control [20], nonlinear model predictive control [21], L1 control [22], fuzzy control [23,24].…”

On-line Inertia Measurement of Unmanned Aerial Vehicles using on board Sensors and Bifilar Pendulum

“…In order to attain the requisite precision of such system model, all important parameters are needed to be known with sufficient accuracy [1,2]. Since moment of inertia cannot be estimated through static tests, its identification could pose certain difficulties.…”