Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

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

A Comparative Study for Control of Quadrotor UAVs

Modeling and controlling highly nonlinear, multivariable, unstable, coupled and underactuated systems are challenging problems to which a unique solution does not exist. Modeling and control of Unmanned Aerial Vehicles (UAVs) with four rotors fall into that category of problems. In this paper, a nonlinear quadrotor UAV dynamical model is developed with the Newton–Euler method, and a control architecture is proposed for 3D trajectory tracking. The controller design is decoupled into two parts: an inner loop for attitude stabilization and an outer loop for trajectory tracking. A few attitude stabilization methods are discussed, implemented and compared, considering the following control approaches: Proportional–Integral–Derivative (PID), Linear–Quadratic Regulator (LQR), Model Predictive Control (MPC), Feedback Linearization (FL) and Sliding Mode Control (SMC). This paper is intended to serve as a guideline work for selecting quadcopters’ control strategies, both in terms of quantitative and qualitative considerations. PID and LQR controllers are designed, exploiting the model linearized about the hovering condition, while MPC, FL and SMC directly exploit the nonlinear model, with minor simplifications. The fast dynamics ensured by the SMC-based controller together with its robustness and the limited estimated command effort of the controller make it the most promising controller for quadrotor attitude stabilization. The outer loop consists of three independent PID controllers: one for altitude control and the other two, together with a dynamics’ inversion, are entitled to the computation of the reference attitude for the inner loop. The capability of the controlled closed-loop system of executing complex trajectories is demonstrated by means of simulations in MATLAB/Simulink®

Towards Human-UAV Physical Interaction and Fully Actuated Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) ability to reach places not accessible to humans or other robots and execute tasks makes them unique and is gaining a lot of research interest recently. Initially UAVs were used as surveying and data collection systems, but lately UAVs are also efficiently employed in aerial manipulation and interaction tasks. In recent times, UAV interaction with the environment has become a common scenario, where manipulators are mounted on top of such systems. Current applications has driven towards the direction of UAVs and humans coexisting and sharing the same workspace, leading to the emerging futuristic domain of Human-UAV physical interaction. In this dissertation, initially we addressed the delicate problem of external wrench estimation (force/torque) in aerial vehicles through a generalized-momenta based residual approach. To our advantage, this approach is executable during flight without any additional sensors. Thereafter, we proposed a novel architecture allowing humans to physically interact with a UAV through the employment of sensor-ring structure and the developed external wrench estimator. The methodologies and algorithms to distinguish forces and torques derived by physical interaction with a human from the disturbance wrenches (due to e.g., wind) are defined through an optimization problem. Furthermore, an admittance-impedance control strategy is employed to act on them differently. This new hardware/software architecture allows for the safe human-UAV physical interaction through exchange of forces. But at the same time, other limitations such as the inability to exchange torques due to the underactuation of quadrotors and the need for a robust controller become evident. In order to improve the robust performance of the UAV, we implemented an adaptive super twisting sliding mode controller that works efficiently against parameter uncertainties, unknown dynamics and external perturbations. Furthermore, we proposed and designed a novel fully actuated tilted propeller hexarotor UAV. We designed the exact feedback linearization controller and also optimized the tilt angles in order to minimize power consumption, thereby improving the flight time. This fully actuated hexarotor could reorient while hovering and perform 6DoF (Degrees of Freedom) trajectory tracking. Finally we put together the external wrench observer, interaction techniques, hardware design, software framework, the robust controller and the different methodologies into the novel development of Human-UAV physical interaction with fully actuated UAV. As this framework allows humans and UAVs to exchange forces as well as torques, we believe it will become the next generation platform for the aerial manipulation and human physical interaction with UAVs

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

Modelling, identification, and control of a quadrotor helicopter

In this dissertation, we focused on the study of an autonomous flight control of quadrotor helicopter. Robust nonlinear control design strategies using observer-based control are developed, which are capable of achieving reliable and accurate tracking control for quadrotor UAV containing dynamic uncertainties, external disturbances. In order to ease readability of this dissertation, detailed explanations of the mathematical model of quadrotor UAV is provided, including the Newton-Euler formalism, Lyapunov-based stability analysis methods, sliding mode control (SMC) and backstepping fundamentals, and observer-based nonlinear control tools. The tracking control problem of a quadrotor in the presence of model uncertainties and external disturbances is investigated. Particularly, this dissertation presents the design and experimental implementation of nonlinear controller of quadrotor with observer to estimate the uncertainties and external disturbances to meet the desired control objectives. Based on a nonlinear model which considers basic aerodynamic forces and external disturbances, the quadrotor UAV model is simulated to perform a variety of maneuvering such as take-off, landing, smooth translation and horizontal and circular trajectory motions. Backstepping and sliding mode techniques combined with observers are studied, tested and compared. Simulation and a real platform were developed to prove the ability of the observer-based controller to successfully perform certain missions in the presence of unknown external disturbances and can obtain good and satisfactory estimation

A new coordination framework for multi-UAV formation control

Unmanned Aerial Vehicles (UAVs) have become very popular in the last few decades. Nowadays these vehicles are used for both civilian and military applications which are dull, dirty and dangerous for humans. The remarkable advances in materials, electronics, sensors, actuators and batteries enable researchers to design more durable, capable, smart and cheaper UAVs. Consequently, a significant amount of research effort has been devoted to the design of UAVs with intelligent navigation and control systems. There are certain applications where a single UAV can not perform adequately. However, carrying out such tasks with a fleet of UAVs in some geometric pattern or formation can be more powerful and more efficient. This thesis focuses on a new coordination scheme that enables formation control of quadrotor type UAVs. Coordination of quadrotors is achieved using a virtual structure approach where orthogonal projections of quadrotors on a virtual plane are utilized to define coordination forces. This plane implies planar spring forces acting between the vehicles. Virtual springs are also augmented with dampers to suppress oscillatory motions. While the coordination among the aerial vehicles is achieved on a virtual plane, altitude control for each vehicle is designed independently. This increases maneuvering capability of each quadrotor along the vertical direction. Due to their robustness to the external disturbances such as wind gusts, integral backstepping controllers are designed to control attitude and position dynamics of individual quadrotors. Several coordinated task scenarios are presented and the performance of the proposed formation control technique is assessed by several simulations where three and five quadrotors are employed. Simulation results are quite promising