A Multiobjective Solution Approach to Fault Detection and Isolation of LPV Systems

This paper describes a new method for detecting sensor faults using sliding mode observers. In general, required capabilities of FDI(Fault Detection and Isolation) filters are sensitivity of occurring faults and robustness against disturbances. A FDI filter that proposed in this paper can estimate faults even if disturbances exist. Moreover, we discretize continuous-time FDI filters into discrete-time FDI filters using difference equations and apply the FDI filter to a vibration experimental system. An example demonstrates the effectiveness of the proposed method in comparison with conventional methods.

International audience

Sensor fault detection and isolation filter for polytopic LPV systems: A winding machine application

Modeling and fault diagnosis design for HVAC systems using recurrent neural networks

This paper investigates the guaranteed cost control problem for a class of linear parameter-varying (LPV) systems with Markovian switching under partly known transition rates. A key point of this work relaxes Markovian jump systems whose subsystems are described by linear time-invariant (LTI) dynamics to LPV systems with Markovian switching whose subsystems are described by LPV dynamics. Meanwhile, the special assumption of completely known transition rates is relaxed to more general case that transition rates are partly known. Moreover, the proposed control technique for the LPV systems with Markovian switching is used to solve the guaranteed cost control problem of turbofan-engine. Firstly, a guaranteed cost controller is designed, and the design problem can be reduced to a set of linear matrix inequalities (LMIs) feasibility problem. Then, a turbofan-engine example is given to demonstrate the applicability of the main results.

This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults. The considered nonlinear systems are described as affine fuzzy models, and the system outputs are chosen as the premise variables of fuzzy models. Different from the existing results, the influence of sensor faults on premise variables is considered. As a result, the well-known parallel distributed compensation scheme cannot be used for FDI filters design. By using the structural information encoded in the fuzzy rules, the affine fuzzy system is represented by multiple operating-regime-based models in fault-free case and faulty cases. In the multiple-model scheme, a bank of piecewise FDI filters are constructed, each of them is based on the affine fuzzy model that describes the system in the presence of a specified fault. The fault-dependent residual signals generated from the filters are used for detecting and isolating the specified fault. The FDI filter design conditions are obtained in the formulation of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and merits of the proposed method.

As commonly known, sensor errors and faulty signals may potentially lead structures in vibration to catastrophic failures. This paper presents a new approach to deal with sensor errors/faults in vibration control of structures by using the Fault detection and isolation (FDI) technique. To demonstrate the effectiveness of the approach, a space truss structure with semi-active devices such as Magneto-Rheological (MR) damper is used as an example. To address the problem, a Linear Matrix Inequality (LMI) based fixed-order H FDI filter is introduced and designed. Modeling errors are treated as uncertainties in the FDI filter design to verify the robustness of the proposed FDI filter. Furthermore, an innovative Fuzzy Fault Tolerant Controller (FFTC) has been developed for this space truss structure model to preserve the pre-specified performance in the presence of sensor errors or faults. Simulation results have demonstrated that the proposed FDI filter is capable of detecting and isolating sensor errors/faults and actuator faults e.g., accelerometers and MR dampers, and the proposed FFTC can maintain the structural vibration suppression in faulty conditions.

Linear Parameter Varying (LPV) system shows preferable performance in dealing with NonLinear (NL) systems and systems with time-varying parameters, based on a kind of wheel-legged robot with two-wheel and balance as Inverted Pendulum, this paper proposes a gain scheduling control method for balancing using LPV system on Equivalent model with Center Of Mass (COM). In order to ensure the stability and responsive of the system with possible values for all variable parameters, Higher Order Singular Value Decomposition (HOSVD) is used for constructing polytopic LPV system, then the robust controller is designed for the vertex systems forthputting Linear Matrix Inequality (LMI) approach, and the gain scheduling controller for global system is obtained by convex combination of vertex LTI systems. The simulation results show that the system can achieve the expected indicators.

Stability analysis and stabilization of LPV systems with jumps and (piecewise) differentiable parameters using continuous and sampled-data controllers

A novel distributed fault detection and isolation (FDI) methodology for a network of nonhomogeneous multi-agent systems is proposed in this paper. An FDI filter is designed such that the effects of the disturbances and control inputs on the residual signals are minimized (for the purpose of fault detection) subject to the constraint that the transfer matrix function from the faults to the residuals is equal to a pre-assigned diagonal transfer matrix (for the purpose of fault isolation). It is shown that by using this approach each agent not only can detect and isolate its own faults but also is able to detect and isolate faults of its neighboring agents. Moreover, the method covers isolation of possibly simultaneous occurring faults in the system. Sufficient conditions for solvability of the problem are obtained in terms of linear matrix inequality (LMI) feasibility conditions. Extended LMIs characterization is used to reduce the conservativeness of the solution by introducing additional variables, to eliminate the coupling of the Lyapunov matrices with the system matrices. Simulation results illustrate the effectiveness of the proposed design methodology.

Multiobjective fault detection and isolation for flexible air-breathing hypersonic vehicle

Linear parameter-varying (LPV) systems are usually described in either state-space or input-output form. When analyzing system equivalence between different representations it appears that the time-shifted versions of the scheduling signal (dynamic dependence) need to be taken into account. Therefore, representations used previously to define and specify LPV systems are not equal in terms of dynamics. In order to construct a parametrization-free description of LPV systems that overcomes these difficulties, a behavioral approach is introduced that serves as a basis for specifying system theoretic properties. LPV systems are defined as the collection of trajectories of system variables (like inputs and outputs) and scheduling variables. LPV kernel, input-output, and state-space system representations are introduced with appropriate equivalence transformations.

In recent years, automatic crane device is used in scenes of handling of objects at warehouse. Stacker crane is an example of automatic crane device. It has a Traveling body, a Forking mechanism and a Lifting mechanism. A Traveling body makes a Lifting body move along the horizontal axis. A Lifting mechanism makes a Forking mechanism move along vertical axis. It is able to carry a load into rack or takes out a load from the rack by using Forking mechanism. But, in action of Forking mechanism, vibration of Forking mechanism and variation of characteristic frequency of Forking mechanism causes several problems. In this study, the stacker crane is described in LPV (Linear Parameter Varying) system. And, using DMM (Dual Model Matching) method provides the LPV controller that can adjust plant that explained by LPV system. The results of simulation show the effectiveness of LPV controller when DMM controlled is applied.

Fault Detection and Isolation (FDI) methods have been developed over the past thirty years but only in the last several years they have been applied to complex real applications. This paper presents a synthesis of H∞ FDI filters for the longitudinal motion of the Boeing 747-100/200 aircraft. The filters are synthesized to detect and isolate faults in the elevator actuator and pitch rate sensor while attenuating disturbances and noise on the fault signals. They are synthesized for open-loop LTI models of the aircraft. Closed-loop simulations with a highfidelity nonlinear model in the presence of gust and noise are performed to validate the disturbance rejection and robust properties of the H∞ LTI FDI filters.

A method for designing FDI filters for polytopic LPV models