Mobile Robot Lab Project to Introduce Engineering Students to Fault Diagnosis in Mechatronic Systems

This document is a self-archiving copy of the accepted version of the paper. Please find the final published version in IEEEXplore: http://dx.doi.org/10.1109/TE.2014.2358551This paper proposes lab work for learning fault detection and diagnosis (FDD) in mechatronic systems. These skills are important for engineering education because FDD is a key capability of competitive processes and products. The intended outcome of the lab work is that students become aware of the importance of faulty conditions and learn to design FDD strategies for a real system. To this end, the paper proposes a lab project where students are requested to develop a discrete event dynamic system (DEDS) diagnosis to cope with two faulty conditions in an autonomous mobile robot task. A sample solution is discussed for LEGO Mindstorms NXT robots with LabVIEW. This innovative practice is relevant to higher education engineering courses related to mechatronics, robotics, or DEDS. Results are also given of the application of this strategy as part of a postgraduate course on fault-tolerant mechatronic systems.This work was supported in part by the Spanish CICYT under Project DPI2011-22443

Active sensor fault tolerant output feedback tracking control for wind turbine systems via T-S model

This paper presents a new approach to active sensor fault tolerant tracking control (FTTC) for offshore wind turbine (OWT) described via Takagi–Sugeno (T–S) multiple models. The FTTC strategy is designed in such way that aims to maintain nominal wind turbine controller without any change in both fault and fault-free cases. This is achieved by inserting T–S proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators to be capable to estimate different generators and rotor speed sensors fault for compensation purposes. Due to the dependency of the FTTC strategy on the fault estimation the designed observer has the capability to estimate a wide range of time varying fault signals. Moreover, the robustness of the observer against the difference between the anemometer wind speed measurement and the immeasurable effective wind speed signal has been taken into account. The corrected measurements fed to a T–S fuzzy dynamic output feedback controller (TSDOFC) designed to track the desired trajectory. The stability proof with H∞ performance and D-stability constraints is formulated as a Linear Matrix Inequality (LMI) problem. The strategy is illustrated using a non-linear benchmark system model of a wind turbine offered within a competition led by the companies Mathworks and KK-Electronic

An active fault tolerant control approach to an offshore wind turbine model

The paper proposes an observer based active fault tolerant control (AFTC) approach to a non-linear large rotor wind turbine benchmark model. A sensor fault hiding and actuator fault compensation strategy is adopted in the design. The adapted observer based AFTC system retains the well-accepted industrial controller as the baseline controller, while an extended state observer (ESO) is designed to provide estimates of system states and fault signals within a linear parameter varying (LPV) descriptor system context using linear matrix inequality (LMI). In the design, pole-placement is used as a time-domain performance specification while H∞ optimization is used to improve the closed-loop system robustness to exogenous disturbances or modelling uncertainty. Simulation results show that the proposed scheme can easily be viewed as an extension of currently used control technology, with the AFTC proving clear “added value” as a fault tolerant system, to enhance the sustainability of the wind turbine in the offshore environment

Model Based Mission Assurance: NASA's Assurance Future

Model Based Systems Engineering (MBSE) is seeing increased application in planning and design of NASAs missions. This suggests the question: what will be the corresponding practice of Model Based Mission Assurance (MBMA)? Contemporaneously, NASAs Office of Safety and Mission Assurance (OSMA) is evaluating a new objectives based approach to standards to ensure that the Safety and Mission Assurance disciplines and programs are addressing the challenges of NASAs changing missions, acquisition and engineering practices, and technology. MBSE is a prominent example of a changing engineering practice. We use NASAs objectives-based strategy for Reliability and Maintainability as a means to examine how MBSE will affect assurance. We surveyed MBSE literature to look specifically for these affects, and find a variety of them discussed (some are anticipated, some are reported from applications to date). Predominantly these apply to the early stages of design, although there are also extrapolations of how MBSE practices will have benefits for testing phases. As the effort to develop MBMA continues, it will need to clearly and unambiguously establish the roles of uncertainty and risk in the system model. This will enable a variety of uncertainty-based analyses to be performed much more rapidly than ever before and has the promise to increase the integration of CRM (Continuous Risk Management) and PRA (Probabilistic Risk Analyses) even more fully into the project development life cycle. Various views and viewpoints will be required for assurance disciplines, and an over-arching viewpoint will then be able to more completely characterize the state of the project/program as well as (possibly) enabling the safety case approach for overall risk awareness and communication

Active fault tolerant control for nonlinear systems with simultaneous actuator and sensor faults

The goal of this paper is to describe a novel fault tolerant tracking control (FTTC) strategy based on robust fault estimation and compensation of simultaneous actuator and sensor faults. Within the framework of fault tolerant control (FTC) the challenge is to develop an FTTC design strategy for nonlinear systems to tolerate simultaneous actuator and sensor faults that have bounded first time derivatives. The main contribution of this paper is the proposal of a new architecture based on a combination of actuator and sensor Takagi-Sugeno (T-S) proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators together with a T-S dynamic output feedback control (TSDOFC) capable of time-varying reference tracking. Within this architecture the design freedom for each of the T-S estimators and the control system are available separately with an important consequence on robust L₂ norm fault estimation and robust L₂ norm closed-loop tracking performance. The FTTC strategy is illustrated using a nonlinear inverted pendulum example with time-varying tracking of a moving linear position reference. Keyword

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Fault Separation Based on An Excitation Operator with Application to a Quadrotor UAV

This paper presents an excitation operator based fault separation architecture for a quadrotor unmanned aerial vehicle (UAV) subject to loss of effectiveness (LoE) faults, actuator aging, and load uncertainty. The actuator fault dynamics is deeply excavated, containing the deep coupling information among the actuator faults, the system states, and control inputs. By explicitly considering the physical constraints and tracking performance, an excitation operator and corresponding integrated state observer are designed to estimate separately actuator fault and load uncertainty. Moreover, a fault separation maneuver and a safety controller are proposed to ensure the tracking performance when the excitation operator is injected. Both comparative simulation and flight experiments have demonstrated the effectiveness of the proposed scheme while maintaining high levels of tracking performance

An unknown input observer-EFIR combined estimator for electro-hydraulic actuator in sensor fault tolerant control application

This paper presents a novel unknown input observer (UIO) integrated extended finite impulse response (EFIR) estimator (UIOEFIR) and its application for an effective sensor fault tolerant control of an electro-hydraulic-actuator (EHA). The proposed estimator exploits the UIO structure in the EFIR filter. Thus, it requires only a small number of historical data (N) whilst ensuring threefold: i) Sensor fault and system-state estimation accuracy under time-correlated noise ii) The number of estimator-design-parameters is significantly minimized. iii) Robust residual generation. A Lyapunov-stability-based theory is carried out to study its convergence condition. Next, an EHAbased test rig has been setup and sensor FTC is performed by carrying this estimator as a part of fault diagnosis algorithm to evaluate its performance by both simulation and realtime experiments. Results highlight that under optimal setting (N = Nopt), the estimator performance is near-accurate to the very-well-developed Extended Kalman Filter-based unknown input observer in an undisturbed condition but significantly outperformed while dealing with time-correlated noise under the same control environment. The estimator also shows its robustness under below-optimal setting (downgrading Nopt by 50%.) while performing in real-time sensor fault-tolerant control