Andrea Cristofaro

Fault tolerant control allocation using unknown input observers

This paper focuses on the use of unknown input observers for detection and isolation of actuator and effector faults with control reconfiguration in overactuated systems. The proposed approach consists in tuning the observer parameters in order to make the filters decoupled from faults affecting selected groups of actuators or effectors. The control allocation actively uses input redundancy in order to make relevant faults observable. The case study of an overactuated marine vessel supports theoretical developments.

On estimation of wind velocity, angle-of-attack and sideslip angle of small UAVs using standard sensors

It is proposed to estimate wind velocity, Angle-Of-Attack (AOA) and Sideslip Angle (SSA) of a fixed-wing Unmanned Aerial Vehicle (UAV) using only kinematic relationships with a Kalman Filter (KF), avoiding the need to know aerodynamic models or other aircraft parameters. Assuming that measurements of airspeed and attitude of an UAV are available as inputs, a linear 4th order time-varying model of the UAVs longitudinal speed and the 3-D wind velocity is used to design a Kalman-filter driven by a GNSS velocity measurement airspeed sensor. An observability analysis shows that the states can be estimated along with an airspeed sensor calibration factor provided that the flight maneuvers are persistently exciting, i.e. the aircraft changes attitude. The theoretical analysis of the KF shows that global exponential stability of the estimation error is achieved under these conditions. The method is tested using experimental data from three different UAVs, using their legacy autopilot to provide basic estimates of UAV velocity and attitude. The results show that convergent estimates are achieved with typical flight patterns indicating that excitation resulting from the environment and normal flight operation is sufficient. Wind velocity estimates correlate well with observed winds at the ground. The validation of AOA and SSA estimates is preliminary, but indicate some degree of correlation between the AOA estimate and vertical accelerometer measurements, as would be expected since lift force can be modeled as a linear function of AOA in normal flight.

Robust Stabilization of Multi Input Plants With Saturating Actuators

This technical note proposes the use of a time-varying sliding surface for stabilizing linear, possibly unstable, Multi-Input plants subject to saturating actuators, in the presence of bounded matched uncertainties. The present work generalizes our previous contributions in several different directions. First, the constructive procedure is generalized, and a result about asymptotical stabilization is given, under the usual assumption of the saturation threshold being larger than the bound on uncertainties. Another goal of the technical note is to widen the set of plants considered including linear Multi-Input systems. Simulation results show both the effectiveness of the control technique and the low computational burden required.

Icing detection and identification for unmanned aerial vehicles: Multiple model adaptive estimation

The accretion of ice layers on wings and control surfaces modifies the shape of the aircraft and, consequently, alters performance and controllability of the vehicle. In this paper we propose a multiple model adaptive estimation framework to detect icing affecting unmanned aerial vehicles using the following sensors: pitot tube (airspeed sensor), GPS and IMU. A case-study is provided as support and validation of theoretical results.

Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

This paper describes a concept for a collision avoidance system for ships, which is based on model predictive control. A finite set of alternative control behaviors are generated by varying two parameters: offsets to the guidance course angle commanded to the autopilot and changes to the propulsion command ranging from nominal speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, compliance with the Convention on the International Regulations for Preventing Collisions at Sea and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon, and the optimal control behavior is selected. Robustness to sensing error, predicted obstacle behavior, and environmental conditions can be ensured by evaluating multiple scenarios for each control behavior. The method is conceptually and computationally simple and yet quite versatile as it can account for the dynamics of the ship, the dynamics of the steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions.

Output invisible control allocation with steady-state input optimization for weakly redundant plants

In this paper, the problem of control allocation is revisited focusing on weakly redundant plants, that is plants having more inputs than outputs but such that no input can be equivalently substituted by a combination of the others. Considering the case of asymptotically constant references, it is shown that input allocation can be used to optimize the steady state input, without altering (even during transients) the output response induced by any a priori given controller. Moreover, a general structure for the allocator is proposed, consisting of a series connection of a steady-state optimizer and an annihilator.

Icing detection in unmanned aerial vehicles with longitudinal motion using an LPV unknown input observer

This paper proposes a linear parameter varying (LPV) unknown input observer for the diagnosis of actuator faults and icing in unmanned aerial vehicles (UAVs). The accretion of ice layers on wings and control surfaces modifies the shape of the aircraft and alters the performance and controllability of the vehicles. The correct detection of this phenomenon is of paramount importance for the efficient implementation of de-icing techniques. The advantage of deriving the unknown input observer within the LPV framework is the possibility to deal with the nonlinearities of the UAV model by embedding them within some varying parameters. Results obtained with a Zagi Flying Wing simulator are used to validate the effectiveness of the proposed approach.

An unknown input observer approach to icing detection for unmanned aerial vehicles with linearized longitudinal motion

The accretion of ice layers on wings and control surfaces modifies the shape of the aircraft and, consequently, alters performance and controllability of the vehicle. In this paper we propose an Unknown Input Observers framework to design icing diagnosis filters. A case-study is provided as support and validation of theoretical results.

Stabilization of discrete-time linear systems with saturating actuators using sliding modes: Application to a twin-rotor system

This paper investigates the stabilization problem for discrete-time linear controllable systems subject to actuator saturation. In the case of completely known plants, a control design technique based on a time varying sliding surface is proposed ensuring stabilization under the assumption of availability of all state measurements. Further, in the presence of matched disturbances with known constant bound, a discrete time sliding mode controller is proposed ensuring plant practical stabilization, and a conservative estimate of the attraction domain is given. Theoretical results have been validated by experimental data using a twin-rotor system.

Fault-tolerant control allocation with actuator dynamics: Finite-time control reconfiguration

This paper focuses on fault tolerant control allocation for overactuated systems with actuator dynamics. The proposed scheme for fault detection and isolation is based on unknown input observers and the main contribution of the paper consists in the presentation of a finite-time control reconfiguration technique which provides a successful recovering of system performances in spite of actuator faults. Simulation results support theoretical developments.