Nicola Mimmo

Active Fault Tolerant Control of Nonlinear Systems: The Cart-Pole Example

Active fault tolerant control of nonlinear systems: The cart-pole example This paper describes the design of fault diagnosis and active fault tolerant control schemes that can be developed for nonlinear systems. The methodology is based on a fault detection and diagnosis procedure relying on adaptive filters designed via the nonlinear geometric approach, which allows obtaining the disturbance de-coupling property. The controller reconfiguration exploits directly the on-line estimate of the fault signal. The classical model of an inverted pendulum on a cart is considered as an application example, in order to highlight the complete design procedure, including the mathematical aspects of the nonlinear disturbance de-coupling method based on the nonlinear differential geometry, as well as the feasibility and efficiency of the proposed approach. Extensive simulations of the benchmark process and Monte Carlo analysis are practical tools for assessing experimentally the robustness and stability properties of the developed fault tolerant control scheme, in the presence of modelling and measurement errors. The fault tolerant control method is also compared with a different approach relying on sliding mode control, in order to evaluate benefits and drawbacks of both techniques. This comparison highlights that the proposed design methodology can constitute a reliable and robust approach for application to real nonlinear processes.

A control architecture for multiple drones operated via multimodal interaction in search & rescue mission

An architecture suitable for the control of multiple unmanned aerial vehicles deployed in Search & Rescue missions is presented in this paper. In the proposed system, a single colocated human operator is able to coordinate the actions of a set of robots in order to retrieve relevant information of the environment. This work is framed in the context of the SHERPA project whose goal is to develop a mixed ground and aerial robotic platform to support search and rescue activities in alpine scenario. Differently from typical human-drone interaction settings, here the operator is not fully dedicated to the drones, but involved in search and rescue tasks, hence only able to provide sparse and incomplete instructions to the robots. In this work, the domain, the interaction framework and the executive system for the autonomous action execution are discussed. The overall system has been tested in a real world mission with two drones equipped with on-board cameras.

Robust Trajectory Tracking for Underactuated VTOL Aerial Vehicles: Extended for Adaptive Disturbance Compensation

Abstract This work proposes a feedback control strategy to let the dynamics of an under-actuated Vertical Take-Off and Landing (VTOL) aerial vehicle to track a desired trajectory thanks to an adaptive robust compensation of the aerodynamic disturbances. The novelty of the proposed approach consists in employing an aerodynamic disturbance observer derived using the NonLinear Geometric Approach and Radial Basis Functions (RBF). The obtained estimation is directly employed by a nonlinear robust feedback law which relies on a cascade control paradigm in which the attitude dynamics and the position dynamics of the vehicle play the role of the inner and of the outer loop, respectively. The robustness of the proposed approach is also demonstrated by means of simulation results in which the aerodynamic model of a multi-propeller aircraft is considered.

A new longitudinal flight path control with adaptive wind shear estimation and compensation

This paper presents a novel approach to the longitudinal guidance and control issue for an aircraft in presence of wind shear. The main contribution concerns the adaptive estimation of the wind shear disturbances affecting the aircraft and the development of a control scheme suitable to compensate these effects during a precision approach procedure. The work proposes the design, based on the Nonlinear Geometric Approach, of three adaptive filters providing the estimate of the wind shear disturbance components. These estimates are exploited, in an original way, by a BackStepping based controller, thus resulting in an Adaptive BackStepping Controller. Simulation results, obtained by means of a detailed flight simulator implementing the real wind shear condition which caused the 1975 crash of Eastern Flight 066 at JFK airport and a Montecarlo robustness test, demonstrates the effectiveness of the proposed method.

Aircraft Nonlinear AFTC based on Geometric Approach and Singular Perturbations in case of actuator and sensor faults

Abstract The Singular Perturbation (SP) theory seems to be a very advantageous framework to describe the longitudinal aircraft dynamic and for designing advanced Flight Controls. In this paper, thanks to SP theory, a novel Active Fault Tolerant Flight Control (AFTFC) has been developed in order to accommodate faults occurring on all actuators and sensors. The proposed AFTFC is composed by two main subsystems: a Fault Detection and Diagnosis (FDD) module, that provides fault estimation, and a Controller that, exploiting this estimation, tracks a reference trajectory, even in presence of fault. The jointly use of the NonLinear Geometric Approach and SP allows the solution of the FDD problem, otherwise not possible for the considered fault scenario. The effectiveness of the proposed AFTFC system is highlighted by extended simulations exploiting a detailed wide–body aircraft flight simulator.

Fault Tolerant Control Schemes for Nonlinear Models of Aircraft and Spacecraft Systems

Abstract This paper explains the design method of an innovative active fault tolerant control scheme and the achieved results regarding its application to aerospace nonlinear models. The proposed method keeps the already in–place control and guidance laws and adds a feedback loop that accommodates the fault. The kernel of this active fault tolerant control consists of the fault detection and diagnosis module designed by using the nonlinear geometric approach. Thanks to this approach fault estimates are analytically decoupled from both the other faults and disturbances. The novel active fault tolerant control has been tested by using high fidelity simulators of aircraft and spacecraft systems, whilst the performances show the method robustness with respect to disturbance effects and measurement errors. The results obtained demonstrate how the proposed design methodology could be a successful approach for the reliable design of fault tolerant control schemes in real aircraft and spacecraft applications.

Avionic Air Data Sensors Fault Detection and Isolation by means of Singular Perturbation and Geometric Approach

Singular Perturbations represent an advantageous theory to deal with systems characterized by a two-time scale separation, such as the longitudinal dynamics of aircraft which are called phugoid and short period. In this work, the combination of the NonLinear Geometric Approach and the Singular Perturbations leads to an innovative Fault Detection and Isolation system dedicated to the isolation of faults affecting the air data system of a general aviation aircraft. The isolation capabilities, obtained by means of the approach proposed in this work, allow for the solution of a fault isolation problem otherwise not solvable by means of standard geometric techniques. Extensive Monte-Carlo simulations, exploiting a high fidelity aircraft simulator, show the effectiveness of the proposed Fault Detection and Isolation system.

Fault diagnosis and fault tolerant control strategies for aerospace systems

This work presents two active fault tolerant control systems for aerospace applications. The former case study regards an aircraft longitudinal autopilot and the latter one a satellite attitude control system, both in case of faults affecting the actuators. The main features of the presented active fault tolerant control schemes are the fault detection and diagnosis module and its design technique, i.e. the nonlinear geometric approach. Such approach allows, using adaptive filters in the fault detection and diagnosis module, fault detection, isolation and estimation. The fault estimates, obtained by different methods including recursive least squares and neural network, are exploited by a controller reconfiguration mechanism. In particular, by means of the nonlinear geometric approach, relying on nonlinear differential algebra, it is possible to obtain fault estimates decoupled from wind components in case of aircraft and aerodynamic disturbances in case of spacecraft, thus giving to the overall control system very good robustness properties and performances. The effectiveness of the designed solutions is shown by means of high fidelity simulators, in different flight conditions and in the presence of faults on actuators, turbulence, measurement noise, and modelling errors.

Internal model-based control for loitering maneuvers of UAVs

In this paper we present a modular control architecture for unmanned aerial vehicles. Given a stabilizing control law, we aim to improve the performances of the vehicle by means of an internal model regulator. To simplify the design procedure, which especially in the nonlinear case might be fairly complicated, we show how it is possible to compose the separate control modules (stabilization and internal model) in an easy and reliable structure. The proposed technique will be tested on the loitering benchmark: in other words, the UAV is required to follow a target and perform a dynamic trajectory around it.

Adaptive FTC based on control allocation and fault accommodation for satellite reaction wheels

This paper proposes an active fault tolerant control scheme to cope with faults or failures affecting the flywheel spin rate sensors or satellite reaction wheel motors. The active fault tolerant control system consists of a fault detection and diagnosis module along with a control allocation and fault accommodation module directly exploiting the on-line fault estimates. The use of the nonlinear geometric approach and radial basis function neural networks allows to obtain a precise fault isolation, independently from the knowledge of aerodynamic disturbance parameters, and to design generalised estimation filters, which do not need a priori information about the internal model of the signal to be estimated. The adaptive control allocation and sensor fault accommodation can handle both temporal faults and failures. Simulation results illustrate the convincing fault correction and attitude control performances of the proposed system.