Nonlinear dynamic inversion for redundant systems using the EKF formalism

This paper presents an allocator for over-actuated systems based on the Extended Kalman Filter (EKF). The main advantages of the proposed approach are the greater flexibility in handling the constraints and its real-time capabilities. Based on the literature, theoretic convergence results, which ensure the convergence towards the local optimal values looked for, are presented. Another formulation of the kinematic equations of redundant systems that meet some constraints is also proposed in order to go through and/or avoid singularities. The two formulations are combined and applied to an academic example (a planar redundant manipulator arm)

A New Procedure for Tuning an Allocator and Designing a Robust High-Level Control Law for Over-Actuated Systems

This paper presents a new integrated procedure to tune a control law for overactuated mechanical systems that may encounter singularities. First, the allocator that divides the commands among the actuators is tuned thanks to a genetic optimization algorithm, that computes the optimal values of its parameters. Then, the open-loop system including the allocator is identified and a robust closed-loop controller is computed with the structured H_\infty method. Indeed, near singularities, the system and the allocator may create errors to deviate from these points or create delays to reconfigure the actuators, hence there is a need to create a closed-loop controller robust to these characteristics and to parameter variations. This procedure is carried out on a planar redundant robotic manipulator example. Simulation

Convergent EKF-based control allocation: general formulation and application to a Control Moment Gyro cluster

This paper addresses control allocation for redundant systems with the Extended Kalman Filter formalism. This method is compatible with the low computational power available in space environment, and presents a flexible framework to include constraints such as singularity avoidance. The convergence domain of the allocator is derived from the contraction theory framework, depending on specific parameters of the system. A general formulation is proposed to maximize the convergence domain with regard to these parameters. The method is applied to design a steering law of Control Moment Gyroscopes. Experimental tests show that the control allocation allows the actuators to work efficiently along nominal trajectories while avoiding singularities when necessary

A Contribution to the Design of Highly Redundant Compliant Aerial Manipulation Systems

Es ist vorhersehbar, dass die Luftmanipulatoren in den nächsten Jahrzehnten für viele Aufgaben eingesetzt werden, die entweder zu gefährlich oder zu teuer sind, um sie mit herkömmlichen Methoden zu bewältigen. In dieser Arbeit wird eine neuartige Lösung für die Gesamtsteuerung von hochredundanten Luftmanipulationssystemen vorgestellt. Die Ergebnisse werden auf eine Referenzkonfiguration angewendet, die als universelle Plattform für die Durchführung verschiedener Luftmanipulationsaufgaben etabliert wird. Diese Plattform besteht aus einer omnidirektionalen Drohne und einem seriellen Manipulator. Um den modularen Regelungsentwurf zu gewährleisten, werden zwei rechnerisch effiziente Algorithmen untersucht, um den virtuellen Eingang den Aktuatorbefehlen zuzuordnen. Durch die Integration eines auf einem künstlichen neuronalen Netz basierenden Diagnosemoduls und der rekonfigurierbaren Steuerungszuordnung in den Regelkreis, wird die Fehlertoleranz für die Drohne erzielt. Außerdem wird die Motorsättigung durch Rekonfiguration der Geschwindigkeits- und Beschleunigungsprofile behandelt. Für die Beobachtung der externen Kräfte und Drehmomente werden zwei Filter vorgestellt. Dies ist notwendig, um ein nachgiebiges Verhalten des Endeffektors durch die achsenselektive Impedanzregelung zu erreichen. Unter Ausnutzung der Redundanz des vorgestellten Luftmanipulators wird ein Regler entworfen, der nicht nur die Referenz der Endeffektor-Bewegung verfolgt, sondern auch priorisierte sekundäre Aufgaben ausführt. Die Wirksamkeit der vorgestellten Lösungen wird durch umfangreiche Tests überprüft, und das vorgestellte Steuerungssystem wird als sehr vielseitig und effektiv bewertet.:1 Introduction 2 Fundamentals 3 System Design and Modeling 4 Reconfigurable Control Allocation 5 Fault Diagnostics For Free Flight 6 Force and Torque Observer 7 Trajectory Generation 8 Hybrid Task Priority Control 9 System Integration and Performance Evaluation 10 ConclusionIn the following decades, aerial manipulators are expected to be deployed in scenarios that are either too dangerous for human beings or too expensive to be accomplished by traditional methods. This thesis presents a novel solution for the overall control of highly redundant aerial manipulation systems. The results are applied to a reference configuration established as a universal platform for performing various aerial manipulation tasks. The platform consists of an omnidirectional multirotor UAV and a serial manipulator. To ensure modular control design, two computationally efficient algorithms are studied to allocate the virtual input to actuator commands. Fault tolerance of the aerial vehicle is achieved by integrating a diagnostic module based on an artificial neural network and the reconfigurable control allocation into the control loop. Besides, the risk of input saturation of individual rotors is minimized by predicting and reconfiguring the speed and acceleration responses. Two filter-based observers are presented to provide the knowledge of external forces and torques, which is necessary to achieve compliant behavior of the end-effector through an axis-selective impedance control in the outer loop. Exploiting the redundancy of the proposed aerial manipulator, the author has designed a control law to achieve the desired end-effector motion and execute secondary tasks in order of priority. The effectiveness of the proposed designs is verified with extensive tests generated by following Monte Carlo method, and the presented control scheme is proved to be versatile and effective.:1 Introduction 2 Fundamentals 3 System Design and Modeling 4 Reconfigurable Control Allocation 5 Fault Diagnostics For Free Flight 6 Force and Torque Observer 7 Trajectory Generation 8 Hybrid Task Priority Control 9 System Integration and Performance Evaluation 10 Conclusio

Satellite Attitude Control with a six-Control Moment Gyro Cluster tested under Microgravity Conditions

International audienceThe attitude control of a satellite equipped with a six-Control Moment Gyro (CMG) cluster is studied, taking into account CMG failure cases and constraints like actuator saturation and real-time aspects. The design of the steering law that allocates the required torques among the actuators is made complex by singularities (gimbal angles of the CMGs where no torque can be created along an axis). This paper describes the problem of a constrained allocation applied to the CMG system, and explains the selected solution. An experimental setup with six CMGs has been designed. It calculates in real-time the attitude guidance laws and control loop. Agile manoeuvres simulating nanosatellite attitude reorientations have been successfully carried out during a European Space Agency (ESA) parabolic flight campaign. The results show that the steering law performs as expected even in case of CMG failures

Model-based fault diagnosis for aerospace systems: a survey

http://pig.sagepub.com/content/early/2012/01/06/0954410011421717International audienceThis survey of model-based fault diagnosis focuses on those methods that are applicable to aerospace systems. To highlight the characteristics of aerospace models, generic nonlinear dynamical modeling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented. An extensive bibliographical review supports a description of the key points of fault detection methods that rely on analytical redundancy. The approaches that best suit the constraints of the field are emphasized and recommendations for future developments in in-flight fault diagnosis are provided

Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans

The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product

MODELING AND INTELLIGENT CONTROL OF A DRONE

This thesis tackles the modeling, design, and control of a Quadrotor unmanned aerial vehicle, with a focus on intelligent control and smart applications such as obstacle avoidance, robust trajectory tracking, visual soft landing, and disturbance compensation. It details the mathematical modeling opted for the simulation and the control. Furthermore, It describes the classic control methodology for both linear and nonlinear control techniques with interpreted simulations; The methodology is subsequently applied to develop an open-source autonomous quadrotor miniature model. In addition, advanced control theory has been applied using Adaptive Linear Quadratic Gaussian, Model predictive control, and intelligent Radial basis functions neural network for the robust tracking of generated trajectory for either obstacle avoidance or bio-inspired soft landing on a specially designed landing pad. The thesis depicts as well the adaptive optimal observation by an enhanced Kalman filter combined with Madgwick sensor’s data fuse. Control laws were mainly either mathematically derived or adaptively generated based on stability analysis using Lyapunov theory, The simulation incorporated several analytical comparisons to prove efficiency and compare the performance

Joint Localization Based on Split Covariance Intersection on the Lie Group

This paper presents a pose fusion method that accounts for the possible correlations among measurements. The proposed method can handle data fusion problems whose uncertainty has both independent part and dependent part. Different from the existing methods, the uncertainties of the various states or measurements are modeled on the Lie algebra and projected to the manifold through the exponential map, which is more precise than that modeled in the vector space. The dealing of the correlation is based on the theory of covariance intersection, where the independent and dependent parts are split to yield a more consistent result. In this paper, we provide a novel method for correlated pose fusion algorithm on the manifold. Theoretical derivation and analysis are detailed first, and then the experimental results are presented to support the proposed theory. The main contributions are threefold: (1) We provide a theoretical foundation for the split covariance intersection filter performed on the manifold, where the uncertainty is associated on the Lie algebra. (2) The proposed method gives an explicit fusion formalism on SE(3) and SE(2), which covers the most use cases in the field of robotics. (3) We present a localization framework that can work both for single robot and multi-robots systems, where not only the fusion with possible correlation is derived on the manifold, the state evolution and relative pose computation are also performed on the manifold. Experimental results validate its advantage over state-of-the-art methods