Damiano Rotondo

Robust quasi-LPV model reference FTC of a quadrotor UAV subject to actuator faults

Abstract A solution for fault tolerant control (FTC) of a quadrotor unmanned aerial vehicle (UAV) is proposed. It relies on model reference-based control, where a reference model generates the desired trajectory. Depending on the type of reference model used for generating the reference trajectory, and on the assumptions about the availability and uncertainty of fault estimation, different error models are obtained. These error models are suitable for passive FTC, active FTC and hybrid FTC, the latter being able to merge the benefits of active and passive FTC while reducing their respective drawbacks. The controller is generated using results from the robust linear parameter varying (LPV) polytopic framework, where the vector of varying parameters is used to schedule between uncertain linear time invariant (LTI) systems. The design procedure relies on solving a set of linear matrix inequalities (LMIs) in order to achieve regional pole placement and H∞ norm bounding constraints. Simulation results are used to compare the different FTC strategies.

An Interval NLPV Parity Equations Approach for Fault Detection and Isolation of a Wind Farm

In this paper, the problem of fault diagnosis of a wind farm is addressed using interval nonlinear parameter-varying (NLPV) parity equations. Fault detection is based on the use of parity equations assuming unknown but bounded description of the noise and modeling errors. The fault detection test is based on checking the consistency between the measurements and the model, by finding if the formers are inside the interval prediction bounds. The fault isolation algorithm is based on analyzing the observed fault signatures online and matching them with the theoretical ones obtained using structural analysis. Finally, the proposed approach is tested using the wind farm benchmark proposed in the context of the wind farm fault-detection-and-isolation/fault-tolerant-control competition.

Fault tolerant control of the wind turbine benchmark using virtual sensors/actuators

Abstract In this paper, the problem of Fault Tolerant Control (FTC) of the wind turbine benchmark is addressed. The paper proposes the use of virtual sensor/actuator approaches to deal with sensor and actuator faults, respectively. The paper suggests the reformulation of these FTC schemes that have been already proposed in state space form in input/output form. The FTC module will use the information from the Fault Detection and Isolation (FDI) module previously designed using set-membership techniques. A fault estimation scheme is also proposed based on batch least squares approach. The performance of the proposed FTC schemes will be assessed using the proposed fault scenarios considered in the FTC benchmark.

A Fault-Hiding Approach for the Switching Quasi-LPV Fault-Tolerant Control of a Four-Wheeled Omnidirectional Mobile Robot

This paper proposes a reference model approach for the trajectory tracking of a four-wheeled omnidirectional mobile robot. In particular, the error model is brought to a quasi-linear-parameter-varying (LPV) form suitable for designing an error-feedback controller. It is shown that, if polytopic techniques are used to reduce the number of constraints from infinite to finite, a solution within the standard LPV framework could not exist due to a singularity that appears in the possible values of the input matrix. Adding a switching component to the controller allows solving this problem. Moreover, a switching LPV virtual actuator is added to the control loop in order to obtain fault tolerance within the fault-hiding paradigm, keeping the stability and some desired performances under the effect of actuator faults without the need of retuning the nominal controller. The effectiveness of the proposed approach is shown and proved through simulation and experimental results.

Robust state-feedback control of uncertain LPV systems : an LMI-based approach

Abstract In this paper, the problem of designing an LPV state-feedback controller for uncertain LPV systems that can guarantee some desired bounds on the H ∞ and the H 2 performances and that satisfies some desired constraints on the closed-loop poles location is considered. In the proposed approach, the vector of varying parameters is used to schedule between uncertain LTI systems. The resulting idea consists in using a double-layer polytopic description so as to take into account both the variability due to the parameter vector and the uncertainty. The first polytopic layer manages the varying parameter and is used to obtain the vertex uncertain systems, where the vertex controllers are designed. The second polytopic layer is built at each vertex system so as to take into account the model uncertainties and add robustness into the design step. Under some assumptions, the problem reduces to finding a solution to a finite number of LMIs, a problem for which efficient solvers are available nowadays. The solution to the multiobjective design problem is found both in the case when a single fixed Lyapunov function is used and when multiple parameter-varying Lyapunov functions are used. The validity and performance of the theoretical results are demonstrated through a numerical example.

Fault Estimation and Virtual Actuator FTC Approach for LPV Systems

Abstract In this paper, a Fault Tolerant Control (FTC) strategy using a virtual actuator for Linear Parameter Varying (LPV) systems is proposed. The main idea of this FTC method is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty actuator is modified adding the virtual actuator block that masks the fault. The suggested strategy is an active FTC strategy that reconfigures the virtual actuator on-line taking into account faults and operating point changes. In order to implement the virtual actuator approach, a fault estimation is required. In this work, the fault estimation is formulated as a parameter estimation problem. The LPV virtual actuator is designed using polytopic LPV techniques and Linear Matrix Inequalities (LMIs). To assess the performance of the proposed approach an aeronautical application is used.

Quasi-LPV modelling and non-linear identification of a Twin Rotor System

This paper describes the experimental identification of the parameters of the Twin Rotor MIMO System (TRMS) non-linear model using data collected from the real lab set-up. From this non-linear model, a quasi-linear parameter varying (quasi-LPV) model has also been derived using a state transformation. This quasi-LPV model is approximated with a polytopic model using the bounding box approach. Such a model can later be used for control design. The model parameters have been calibrated by means of non-linear least-squares identification approach. Once the calibrated non-linear model has been obtained, a simulator has been built and validated against real data showing satisfactory results when compared to real data.

Fault estimation and virtual sensor FTC approach for LPV systems

In this paper, a Fault Tolerant Control (FTC) strategy using a virtual sensor for Linear Parameter Varying (LPV) systems is proposed. The main idea of this FTC method is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty sensor is modified adding the virtual sensor block that masks the sensor fault. The suggested strategy is an active FTC strategy that reconfigures the virtual sensor on-line taking into account faults and operating point changes. In order to implement the virtual sensor approach, a fault estimation is required. Here, this fault estimation is provided by formulating it as a parameter estimation problem. Then, a block/batch least square approach is used to estimate additive and multiplicative faults. The LPV virtual sensor is designed using polytopic LPV techniques and Linear Matrix Inequalities (LMIs). To assess the performance of the proposed approach a two degree of freedom helicopter simulator is used.

Robust unknown input observer for state and fault estimation in discrete-time Takagi–Sugeno systems

ABSTRACT In this paper, a robust unknown input observer (UIO) for the joint state and fault estimation in discrete-time Takagi–Sugeno (TS) systems is presented. The proposed robust UIO, by applying the framework, leads to a less restrictive design procedure with respect to recent results found in the literature. The resulting design procedure aims at achieving a prescribed attenuation level with respect to the exogenous disturbances, while obtaining at the same time the convergence of the observer with a desired bound on the decay rate. An extension to the case of unmeasurable premise variables is also provided. Since the design conditions reduce to a set of linear matrix inequalities that can be solved efficiently using the available software, an evident advantage of the proposed approach is its simplicity. The final part of the paper presents an academic example and a real application to a multi-tank system, which exhibit clearly the performance and effectiveness of the proposed strategy.

Automated generation and comparison of Takagi-Sugeno and polytopic quasi-LPV models

In the last decades, gain-scheduling control techniques have consolidated as an efficient answer to analysis and synthesis problems for non-linear systems. Among the approaches proposed in the literature, the linear parameter varying (LPV) and Takagi-Sugeno (TS) paradigms have proved to be successful in dealing with the different trials that the analyzer, or the designer, of a gain-scheduled control system has to face. Despite the strong similarities between the two paradigms, research on LPV and TS systems has been performed in an independent way and some results that could be useful for both paradigms were obtained only for one of them. However, in recent works, some clues that there is a very close connection between LPV and TS worlds have been presented. The present paper openly addresses the presence of strong analogies between LPV and TS models, in an attempt to establish a bridge between these two worlds, so far considered different. In particular, this paper addresses the modeling problem, presenting two methods for the automated generation of LPV and TS systems, and introducing some measures in order to compare the obtained models. A mathematical example is used to illustrate the proposed methods.