A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Trajectory Tracking Control of a Four Rotor Unmanned Aerial Vehicle Based on Continuous Sliding Mode Controller

In this paper, a nonlinear Continuous Sliding Mode control (CSMC) application is presented for trajectory tracking control of a four rotor unmanned aerial vehicle (UAV) called the Quadrotor, also known as micro helicopter. The proposed controller is tested with different time-varying reference routes to provide a stable flight for position control. To show the effectiveness of the designed CSMC, well-tuned PI controller is also applied to quadrotor for the same routes. The current position of the quadrotor is taken from accelerometer, gyroscope and ultrasonic sensors. The experimental results show that the CSMC is adequate to dealing with parameter uncertainties occur in the system dynamics while flying and has satisfactory performance in terms of robustness against to disturbances and error elimination when it compared with PI controller

Quadrotor Aggressive Deployment, Using a Quaternion-based Spherical Chattering-free Sliding-mode Controller

International audienceThis paper introduces a non-conventional approach for autonomous multi-rotor UAV deployment, in which a quadro-tor is aggressively launched through the air with its motors turned off. A continuous quaternion attitude trajectory is proposed to safely recover the vehicle into hover mode. Then, an operator then could take the command or continue a desired mission in autonomous mode. The controller is a chattering-free sliding mode algorithm based on the geometrical properties of quaternions and axis-angle rotations. Lyapunov theory is used to analyze the system stability. The proposed methodology is validated in real world indoor and outdoor experiments

Dynamic modeling and control of a Quadrotor using linear and nonlinear approaches

With the huge advancements in miniature sensors, actuators and processors depending mainly on the Micro and Nano-Electro-Mechanical-Systems (MEMS/NEMS), many researches are now focusing on developing miniature flying vehicles to be used in both research and commercial applications. This thesis work presents a detailed mathematical model for a Vertical Takeo ff and Landing (VTOL) type Unmanned Aerial Vehicle(UAV) known as the quadrotor. The nonlinear dynamic model of the quadrotor is formulated using the Newton-Euler method, the formulated model is detailed including aerodynamic effects and rotor dynamics that are omitted in many literature. The motion of the quadrotor can be divided into two subsystems; a rotational subsystem (attitude and heading) and a translational subsystem (altitude and x and y motion). Although the quadrotor is a 6 DOF underactuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is underactuated. The derivation of the mathematical model is followed by the development of four control approaches to control the altitude, attitude, heading and position of the quadrotor in space. The fi rst approach is based on the linear Proportional-Derivative-Integral (PID) controller. The second control approach is based on the nonlinear Sliding Mode Controller (SMC). The third developed controller is a nonlinear Backstepping controller while the fourth is a Gain Scheduling based PID controller. The parameters and gains of the forementioned controllers were tuned using Genetic Algorithm (GA) technique to improve the systems dynamic response. Simulation based experiments were conducted to evaluate and compare the performance of the four developed control techniques in terms of dynamic performance, stability and the effect of possible disturbances

Model-Free Control of an Unmanned Aircraft Quadcopter Type System

A model-free control algorithm based on the sliding mode control method for unmanned aircraft systems is proposed. The mathematical model of the dynamic system is not required to derive the sliding mode control law for this proposed method. The knowledge of the system’s order, state measurements and control input gain matrix shape and bounds are assumed to derive the control law to track the required trajectories. Lyapunov’s Stability criteria is used to ensure closed-loop asymptotic stability and the error estimate between previous control inputs is used to stabilize the system. A smoothing boundary layer is introduced into the system to eliminate the high frequency chattering of the control input and the higher order states. The [B] matrix used in the model-free algorithm based on the sliding mode control is derived for a quadcopter system. A simulation of a quadcopter is built in Simulink and the model-free control algorithm based on sliding mode control is implemented and a PID control law is used to compare the performance of the model-free control algorithm based off of the RMS (Root-Mean-Square) of the difference between the actual state and the desired state as well as average power usage. The model-free algorithm outperformed the PID controller in all simulations with the quadcopter’s original parameters, double the mass, double the moments of inertia, and double both the mass and the moments of inertia while keep both controllers exactly the same for each simulation

Fault Diagnosis and Fault-Tolerant Control of Unmanned Aerial Vehicles

With the increasing demand for unmanned aerial vehicles (UAVs) in both military and civilian applications, critical safety issues need to be specially considered in order to make better and wider use of them. UAVs are usually employed to work in hazardous and complex environments, which may seriously threaten the safety and reliability of UAVs. Therefore, the safety and reliability of UAVs are becoming imperative for development of advanced intelligent control systems. The key challenge now is the lack of fully autonomous and reliable control techniques in face of different operation conditions and sophisticated environments. Further development of unmanned aerial vehicle (UAV) control systems is required to be reliable in the presence of system component faults and to be insensitive to model uncertainties and external environmental disturbances. This thesis research aims to design and develop novel control schemes for UAVs with consideration of all the factors that may threaten their safety and reliability. A novel adaptive sliding mode control (SMC) strategy is proposed to accommodate model uncertainties and actuator faults for an unmanned quadrotor helicopter. Compared with the existing adaptive SMC strategies in the literature, the proposed adaptive scheme can tolerate larger actuator faults without stimulating control chattering due to the use of adaptation parameters in both continuous and discontinuous control parts. Furthermore, a fuzzy logic-based boundary layer and a nonlinear disturbance observer are synthesized to further improve the capability of the designed control scheme for tolerating model uncertainties, actuator faults, and unknown external disturbances while preventing overestimation of the adaptive control parameters and suppressing the control chattering effect. Then, a cost-effective fault estimation scheme with a parallel bank of recurrent neural networks (RNNs) is proposed to accurately estimate actuator fault magnitude and an active fault-tolerant control (FTC) framework is established for a closed-loop quadrotor helicopter system. Finally, a reconfigurable control allocation approach is combined with adaptive SMC to achieve the capability of tolerating complete actuator failures with application to a modified octorotor helicopter. The significance of this proposed control scheme is that the stability of the closed-loop system is theoretically guaranteed in the presence of both single and simultaneous actuator faults

Seguimiento de trayectoria robusta de un cuadricóptero sin mediciones de velocidad utilizando el control super-twisting generalizado

This paper presents a nonlinear control strategy to solve the path tracking problem for a quadrotor unmanned aerial vehicle under perturbations. This strategy is based on the Generalized Super-Twisting Algorithm (GSTA); it means the second order sliding mode technique, which is able to ensure robustness with respect to modeling errors and bounded external disturbances due to the added extra linear correction terms. The controller goal is to achieve suitable path tracking of desired absolute positions and yaw angle while keeping the stability of the pitch and roll angle, in spite of the presence of disturbances and the handling of all system nonlinearities. In this work, a scenario in which velocities measurements are not available and are estimated by the Generalized Super-Twisting Observer is considered. Finally, the simulation results are also provided in order to illustrate the performances of the proposed controller.Este artículo presenta una estrategia de control no lineal para resolver el problema de seguimiento de trayectorias para un vehículo aéreo no tripulado bajo perturbaciones. Esta estrategia se basa en el Algoritmo Super-Twisting Generalizado (GSTA); es una técnica de modos deslizantes de segundo orden, la cual es capaz de asegurar robustez con respecto a errores de modelado y perturbaciones externas acotadas debido a los términos de corrección lineales añadidos respecto al algoritmo Super Twisting convencional. El objetivo del controlador es conseguir un seguimiento de trayectoria adecuado de las posiciones absolutas deseadas y del ángulo de guiñada, mientras se mantiene la estabilidad del ángulo de inclinación y de alabeo, a pesar de la presencia de perturbaciones y las no linealidades del sistema. En este trabajo, es considerado un escenario en el que las mediciones de las velocidades no están disponibles y son estimadas por el Observador Super-Twisting Generalizado. Finalmente, también fueron proporcionados los resultados de simulación para ilustrar el desempeño del controlador propuesto

Investigations of Model-Free Sliding Mode Control Algorithms including Application to Autonomous Quadrotor Flight

Sliding mode control is a robust nonlinear control algorithm that has been used to implement tracking controllers for unmanned aircraft systems that are robust to modeling uncertainty and exogenous disturbances, thereby providing excellent performance for autonomous operation. A significant advance in the application of sliding mode control for unmanned aircraft systems would be adaptation of a model-free sliding mode control algorithm, since the most complex and time-consuming aspect of implementation of sliding mode control is the derivation of the control law with incorporation of the system model, a process required to be performed for each individual application of sliding mode control. The performance of four different model-free sliding mode control algorithms was compared in simulation using a variety of aerial system models and real-world disturbances (e.g. the effects of discretization and state estimation). The two best performing algorithms were shown to exhibit very similar behavior. These two algorithms were implemented on a quadrotor (both in simulation and using real-world hardware) and the performance was compared to a traditional PID-based controller using the same state estimation algorithm and control setup. Simulation results show the model-free sliding mode control algorithms exhibit similar performance to PID controllers without the tedious tuning process. Comparison between the two model-free sliding mode control algorithms showed very similar performance as measured by the quadratic means of tracking errors. Flight testing showed that while a model-free sliding mode control algorithm is capable of controlling realworld hardware, further characterization and significant improvements are required before it is a viable alternative to conventional control algorithms. Large tracking errors were observed for both the model-free sliding mode control and PID based flight controllers and the performance was characterized as unacceptable for most applications. The poor performance of both controllers suggests tracking errors could be attributed to errors in state estimation, which effectively introduce unknown dynamics into the feedback loop. Further testing with improved state estimation would allow for more conclusions to be drawn about the performance characteristics of the model-free sliding mode control algorithms