Anand Sanche

Bio: Anand Sanche is an academic researcher from CINVESTAV. The author has contributed to research in topics: Backstepping. The author has an hindex of 1, co-authored 1 publications receiving 51 citations.

Hovering quad-rotor control: A comparison of nonlinear controllers using visual feedback

Abstract: In this paper, we present a comparison of three control techniques: Nested Saturations, Backstepping and Sliding Modes. The control objective consists of obtaining the best control strategy to stabilize the position of a quad-rotor when using visual feedback. We propose a method to measure translational speed as well as the UAV 3D position in a local frame. The selected controllers were implemented and tested in real-time experiments. The obtained results demonstrate the performance of such methodologies applied to the quad-rotor system.

Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective

Abstract: Unmanned aerial vehicle (UAV) networks are playing an important role in various areas due to their agility and versatility, which have attracted significant attentions from both the academia and industry in recent years. As an integration of embedded systems with communication devices, computation capabilities and control modules, the UAV network could build a closed loop from data perceiving, information exchanging, decision making to the final execution, which tightly integrates cyber processes into physical devices. Therefore, the UAV network could be considered as a cyber physical system (CPS). Revealing coupling effects among the three interacted CPS components, i.e., communication, computation and control, is envisioned as the key to properly utilize all available resources and hence improve the performance of the UAV network. In this paper, we present a comprehensive survey on UAV networks from a CPS perspective. Firstly, we review the basics and advances of the three CPS components in UAV networks. Then we look inside to investigate how these components contribute to the system performance by classifying UAV networks into three hierarchies, i.e., cell level, system level, and system of system level. Furthermore, the coupling effects among these CPS components are explicitly illustrated, which could be enlightening to deal with the challenges in each individual aspect. New research directions and open issues are discussed at the end of this survey. With this intensive literature review, we intend to provide a novel insight into the state of the art in UAV networks.

Nonlinear Hierarchical Control for Unmanned Quadrotor Transportation Systems

Abstract: An unmanned quadrotor presents excellent mobility to fly freely in complex environments, which makes it an ideal choice for aerial transferring tasks. During the transferring process, it is very challenging to eliminate the swing, since there is no direct control on the payload. The quadrotor transportation system presents the great challenge of the cascaded underactuated–underactuated property, which makes it extremely difficult to simultaneously implement accurate quadrotor positioning and efficient payload swing suppression. In this paper, a nonlinear hierarchical control scheme is proposed for a quadrotor transportation system, which takes full advantage of the cascade property of the system and separates the controller design for the inner loop and the outer loop, respectively, to facilitate the design procedure. More specifically, for the outer loop subsystem, based on the proposed energy storage function, a virtual control vector is designed, which introduces a saturation function to make the desired attitude free of any singularities. For the inner loop, a coordinate-free geometric attitude tracking controller is designed on the Lie group to drive the quadrotor to its desired attitude. It is shown theoretically by Lyapunov techniques and LaSalle's invariance theorem that the equilibrium point of the overall system is asymptotically stable. As illustrated by experimental results, the proposed control law presents advantages such as high control precision, effective payload swing suppression, and so on.

Nonlinear Visual Control of Unmanned Aerial Vehicles in GPS-Denied Environments

Abstract: In this paper, we propose a nonlinear controller that stabilizes unmanned aerial vehicles in GPS-denied environments with respect to visual targets by using only onboard sensing. The translational velocity of the vehicle is estimated online with a nonlinear observer, which exploits spherical visual features as the main source of information. With the proposed solution, only four visual features have shown to be enough for the observer to operate in a real scenario. In addition, the observer is computationally light with constant numerical complexity, involving small-dimension matrices. The observer output is then exploited in a nonlinear controller designed with an integral backstepping approach, thus yielding a novel robust control system. By means of Lyapunov analysis, the stability of the closed-loop system is proved. Extensive simulation and experimental tests with a quadrotor are carried out to verify the validity and robustness of the proposed approach. The control system runs fully onboard on a standard processor, and only a low-cost sensing suite is employed. Tracking of a target whose speed exceeds 2 $\mathrm{m/s}$ is also considered in the real-hardware experiments.

Stable Path-Following Control for a Quadrotor Helicopter Considering Energy Consumption

Abstract: A substantial interest in aerial robots has grown in recent years. However, the energetic cost of flying is one of the key challenges nowadays. Rotorcrafts are heavier-than-air flying machines that use lift generated by one or several rotors (vertically oriented propellers), and because of this, they spend a large proportion of their available energy to maintain their own weight in the air. In this brief, this concept is used to evaluate the relationship between navigation speed and energy consumption in a miniature quadrotor helicopter, which travels over a desired path. A novel path-following controller is proposed in which the speed of the rotorcraft is a dynamic profile that varies with the geometric requirements of the desired path. The stability of the control law is proved using the Lyapunov theory. The experimental results using a real quadrotor show the good performance of the proposed controller, and the percentages of involved energy are quantified using a model of a lithium polymer battery that was previously identified.

Adaptive Position/Attitude Tracking Control of Aerial Robot With Unknown Inertial Matrix Based on a New Robust Neural Identifier

Abstract: This paper presents a novel adaptive controller for controlling an autonomous helicopter with unknown inertial matrix to asymptotically track the desired trajectory. To identify the unknown inertial matrix included in the attitude dynamic model, this paper proposes a new structural identifier that differs from those previously proposed in that it additionally contains a neural networks (NNs) mechanism and a robust adaptive mechanism, respectively. Using the NNs to compensate the unknown aerodynamic forces online and the robust adaptive mechanism to cancel the combination of the overlarge NNs compensation error and the external disturbances, the new robust neural identifier exhibits a better identification performance in the complex flight environment. Moreover, an optimized algorithm is included in the NNs mechanism to alleviate the burdensome online computation. By the strict Lyapunov argument, the asymptotic convergence of the inertial matrix identification error, position tracking error, and attitude tracking error to arbitrarily small neighborhood of the origin is proved. The simulation and implementation results are provided to evaluate the performance of the proposed controller.