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Fault-tolerant control strategy for actuator faults using LPV techniques

Fault-tolerant control strategy for actuator faults using LPV techniques: Application to a two degree of freedom helicopter In this paper, a Fault Tolerant Control (FTC) strategy for Linear Parameter Varying (LPV) systems that can be used in the case of actuator faults is proposed. The idea of this FTC method is to adapt the faulty plant instead of adapting the controller to the faulty plant. This approach can be seen as a kind of virtual actuator. An integrated FTC design procedure for the fault identification and fault-tolerant control schemes using LPV techniques is provided as well. Fault identification is based on the use of an Unknown Input Observer (UIO). The FTC controller is implemented as a state feedback controller and designed using polytopic LPV techniques and Linear Matrix Inequality (LMI) regions in such a way as to guarantee the closed-loop behavior in terms of several LMI constraints. To assess the performance of the proposed approach, a two degree of freedom helicopter is used.

A fault-tolerant control strategy for non-linear discrete-time systems: application to the twin-rotor system

In this paper, an active FTC scheme is proposed. First, it is developed in the context of linear systems and then it is extended to non-linear systems with the differential mean value theorem. The key contribution of the proposed approach is an integrated FTC design procedure of the fault identification and fault-tolerant control schemes. Fault identification is based on the use of an observer. While, the FTC controller is implemented as a state feedback controller. This controller is designed such that it can stabilize the faulty plant using Lyapunov theory and LMIs. Finally, the last part of the paper shows application results regarding the Twin-Rotor MIMO System (TRMS) that confirm the high performance of the proposed approach.

Fault-Tolerant Control design using a virtual sensor 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 such that the nominal controller could be still used without need of retuning it. That is, the plant with the sensor fault is modified adding the virtual sensor block that masks this fault and allows the controller to see the same plant as before the fault. This virtual sensor is designed using polytopic LPV techniques and Linear Matrix Inequalities (LMIs). The LPV state feedback controller is designed for quadratic H2/H∞ performance using a polytopic representation of the system that leads to solve a finite number of algebraic LMIs. To assess the performance of the proposed approach a two degree of freedom helicopter is used.

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.

Fault-Tolerant Control design using LPV Admissible Model Matching: Application to a two-degree of freedom helicopter

In this paper, a new approach to design a Fault-Tolerant Control (FTC) based on Linear Parameter Varying (LPV) Admissible Model Matching (AMM) is proposed. The suggested strategy is an active technique that requires the fault to be detected and estimated by the FDI scheme. Then, the controller is redesigned accordingly. In this work, faults are expressed as a change in the system dynamics (in particular, in the model parameters). The main contribution of the proposed approach is to consider the fault as a scheduling variable in the LPV model that allows the controller reconfiguration. The range of the scheduling variables (fault magnitude and system operating point) allow to specify the set of admissible behaviors. The effectiveness and performances of the method have been illustrated in a two degree of freedom helicopter.

Robust fault detection for LPV systems using interval observers and zonotopes

In this paper, the problem of robust fault detection using an interval observer for dynamic systems characterized by LPV (linear parameter varying) models is presented. The observer faces the robustness problem using two complementary strategies. Modeling uncertainties are considered unknown but bounded by intervals. Their effect is addressed using an interval state observation method based on zonotope representation of the set of possible states. The observer gain is designed via pole placement using LMI formulation. The method is applied to a LPV representation of a Twin Rotor MIMO System.

A fault-tolerant control scheme for non-linear discrete-time systems: Application to the twin-rotor system

In this paper, an active FTC scheme is proposed. First, it is developed in the context of linear systems and then it is extended to non-linear systems with the differential mean value theorem. The key contribution of the proposed approach is an integrated FTC design procedure of the fault identification and fault-tolerant control schemes. Fault identification is based on the use of an observer. While, the FTC controller is implemented as a state feedback controller. This controller is designed such that it can stabilize the faulty plant using Lyapunov theory and LMIs. Finally, the last part of the paper shows application results regarding the Twin-Rotor MIMO System (TRMS) that confirm the high performance of the proposed approach.

Reliable Fault-Tolerant Control Design for LPV Systems using Admissible Model Matching

In the paper two power-invariant real and complex state space transformations for modeling multi-phase electrical machines in a compact and general form are proposed. In particular the paper deals with the modeling of multi-phase permanent magnet synchronous machines with an arbitrary number of phases and an arbitrary shape of the rotor flux. The dynamic model of the motor is obtained using a Lagrangian approach and in the frame of the Power-Oriented Graphs technique. The obtained models are equivalent from a mathematical point of view and can be directly implemented in Simulink. The complex transformed model is quite compact and uses a reduced order state vector. Some simulation results end the paper.

Fault-Tolerant Control using a Virtual Actuator using LPV Techniques: Application to a Two-Degree of Freedom Helicopter

Abstract In this paper, a Fault Tolerant Control (FTC) strategy using a virtual actuator for non-***linear systems represented as Linear Parameter Varying (LPV) models is proposed. The main idea of this FTC method is to adapt the faulty plant to the nominal controller instead of adapting the controller to the faulty plant. That is, the faulty plant together with the virtual actuator block allows the controller to see the same plant as before the fault. This virtual actuator is designed using polytopic LPV techniques and LMIs. To assess the performance of the proposed approach a two degree of freedom helicopter is used.

Adaptive Threshold Generation for Robust Fault Detection Using Interval LPV Observers

Abstract In this paper, adaptive threshold generation for robust fault detection of nonlinear system described by means of a Linear Parameter Varying (LPV) model is analyzed. Uncertainties due to parameter variations are considered unknown but bounded by intervals. Their effect is addressed using an interval LPV observer based on zonotopes. The design procedure of this observer is implemented via pole placement using LMIs. The optimal threshold is generated by evaluating the worst-case residuals energy evolution in the time domain. When this adaptive threshold is used, the minimum detectable fault is characterized. Finally, an application example based on a two-degree freedom helicopter will be used to assess the validity of the proposed approach.