Flight Evaluation of an LPV Sliding Mode Observer for Sensor FTC

This brief develops a sliding mode sensor fault-tolerant control scheme for a class of linear parameter varying (LPV) systems. It incorporates a sliding mode observer that reconstructs the unknown sensor faults based on only the system inputs and outputs. The reconstructed sensor faults are used to compensate for the corrupted sensor measurements before they are used in the feedback controller. Provided accurate fault estimates can be computed; near nominal control performance can be retained without any controller reconfiguration. Furthermore, the closed-loop stability of the fault-tolerant control (FTC) scheme, involving both a sliding mode controller and a sliding mode observer, is rigorously analyzed. The proposed scheme is validated using the Japan Aerospace Exploration Agency’s Multipurpose Aviation Laboratory (MuPAL- α ) research aircraft. These flight tests represent the first validation tests of a sliding mode sensor FTC scheme on a full-scale aircraft

Interval Sliding Mode Observer based Fault Accommodation for Non-minimum Phase LPV Systems with Online Control Allocation

This paper proposes an interval sliding mode observer (ISMO) based sliding mode actuator fault accommodation (FA) framework for non-minimum phase linear-parameter-varying (LPV) systems involving online control allocation (CA) problem. Firstly, a specifically designed coordinate transformation is introduced to deal with the non-minimum phase issue. Then, for the transformed system, an ISMO is proposed to estimate the set of admissible values for the states of the faulty LPV systems. It is constructed based on the designed interval bounds for the scheduling-parameter-related uncertainties and fault-related items. The observer is designed by combining the interval observer and the sliding mode observer techniques. A fault-tolerant control (FTC) law with an online CA scheme is subsequently designed by stabilizing the proposed ISMO instead of the original faulty LPV system, which guarantees that the unmeasurable states of the original LPV system converge to zero asymptotically, the measurable outputs converge to zero in finite time, and further, the actual control efforts are allocated to all actuators optimally and satisfy prescribed performance. Finally, a simulation based on the inverter used in China Railway High-speed (CRH) is presented to illustrate the effectiveness of the proposed framework

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

Linear parameter-varying sliding mode control of state delayed systems with application to delta wing vortex coupled dynamics

In this thesis a new linear parameter-varying sliding mode control (LPVSMC) approach is developed for linear parameter-varying time-delayed systems (LPVTDS). This approach combines sliding mode control (SMC), linear parameter-varying (LPV) control theory, and time delay stability analysis to solve an LPVTDS control problem. A new linear parameter-varying sliding surface is proposed to achieve the control objectives. The time-varying parameters of the sliding surface are calculated according to a parameter-dependent Lyapunov-Krasovskii functional analysis which ensures asymptotic stability of the closed-loop system. It is anticipated that this method will lead to significant improvement over existing SMC approaches in aerospace applications with parameter variations

Flight evaluation of an LPV sliding mode observer for sensor FTC

This brief develops a sliding mode sensor fault-tolerant control scheme for a class of linear parameter varying (LPV) systems. It incorporates a sliding mode observer that reconstructs the unknown sensor faults based on only the system inputs and outputs. The reconstructed sensor faults are used to compensate for the corrupted sensor measurements before they are used in the feedback controller. Provided accurate fault estimates can be computed; near nominal control performance can be retained without any controller reconfiguration. Furthermore, the closed-loop stability of the fault-tolerant control (FTC) scheme, involving both a sliding mode controller and a sliding mode observer, is rigorously analyzed. The proposed scheme is validated using the Japan Aerospace Exploration Agency's Multipurpose Aviation Laboratory (MuPAL-α) research aircraft. These flight tests represent the first validation tests of a sliding mode sensor FTC scheme on a full-scale aircraft

Actuator and sensor fault estimation based on a proportional-integral quasi-LPV observer with inexact scheduling parameters

© 2019. ElsevierThis paper presents a method for actuator and sensor fault estimation based on a proportional-integral observer (PIO) for a class of nonlinear system described by a polytopic quasi-linear parameter varying (qLPV) mathematical model. Contrarily to the traditional approach, which considers measurable or unmeasurable scheduling parameters, this work proposes a methodology that considers inexact scheduling parameters. This condition is present in many physical systems where the scheduling parameters can be affected by noise, offsets, calibration errors, and other factors that have a negative impact on the measurements. A H8 performance criterion is considered in the design in order to guarantee robustness against sensor noise, disturbance, and inexact scheduling parameters. Then, a set of linear matrix inequalities (LMIs) is derived by the use of a quadratic Lyapunov function. The solution of the LMI guarantees asymptotic stability of the PIO. Finally, the performance and applicability of the proposed method are illustrated through a numerical experiment in a nonlinear system.Peer ReviewedPostprint (author's final draft

On-line estimation approaches to fault-tolerant control of uncertain systems

This thesis is concerned with fault estimation in Fault-Tolerant Control (FTC) and as such involves the joint problem of on-line estimation within an adaptive control system. The faults that are considered are significant uncertainties affecting the control variables of the process and their estimates are used in an adaptive control compensation mechanism. The approach taken involves the active FTC, as the faults can be considered as uncertainties affecting the control system. The engineering (application domain) challenges that are addressed are: (1) On-line model-based fault estimation and compensation as an FTC problem, for systems with large but bounded fault magnitudes and for which the faults can be considered as a special form of dynamic uncertainty. (2) Fault-tolerance in the distributed control of uncertain inter-connected systems The thesis also describes how challenge (1) can be used in the distributed control problem of challenge (2). The basic principle adopted throughout the work is that the controller has two components, one involving the nominal control action and the second acting as an adaptive compensation for significant uncertainties and fault effects. The fault effects are a form of uncertainty which is considered too large for the application of passive FTC methods. The thesis considers several approaches to robust control and estimation: augmented state observer (ASO); sliding mode control (SMC); sliding mode fault estimation via Sliding Mode Observer (SMO); linear parameter-varying (LPV) control; two-level distributed control with learning coordination

Mathematical control of complex systems 2013

Mathematical control of complex systems have already become an ideal research area for control engineers, mathematicians, computer scientists, and biologists to understand, manage, analyze, and interpret functional information/dynamical behaviours from real-world complex dynamical systems, such as communication systems, process control, environmental systems, intelligent manufacturing systems, transportation systems, and structural systems. This special issue aims to bring together the latest/innovative knowledge and advances in mathematics for handling complex systems. Topics include, but are not limited to the following: control systems theory (behavioural systems, networked control systems, delay systems, distributed systems, infinite-dimensional systems, and positive systems); networked control (channel capacity constraints, control over communication networks, distributed filtering and control, information theory and control, and sensor networks); and stochastic systems (nonlinear filtering, nonparametric methods, particle filtering, partial identification, stochastic control, stochastic realization, system identification)

Interval Prediction for Continuous-Time Systems with Parametric Uncertainties

The problem of behaviour prediction for linear parameter-varying systems is considered in the interval framework. It is assumed that the system is subject to uncertain inputs and the vector of scheduling parameters is unmeasurable, but all uncertainties take values in a given admissible set. Then an interval predictor is designed and its stability is guaranteed applying Lyapunov function with a novel structure. The conditions of stability are formulated in the form of linear matrix inequalities. Efficiency of the theoretical results is demonstrated in the application to safe motion planning for autonomous vehicles.Comment: 6 pages, CDC 2019. Website: https://eleurent.github.io/interval-prediction