Mariusz Buciakowski

Actuator fault diagnosis and fault-tolerant control: Application to the quadruple-tank process

The paper focuses on an important problem related to the modern control systems, which is the robust fault-tolerant control. In particular, the problem is oriented towards a practical application to quadruple-tank process. The proposed approach starts with a general description of the system and fault-tolerant strategy, which is composed of a suitably integrated fault estimator and robust controller. The subsequent part of the paper is concerned with the design of robust controller as well as the proposed fault-tolerant control scheme. To confirm the effectiveness of the proposed approach, the final part of the paper presents experimental results for considered the quadruple-tank process.

An H∞ approach to fault estimation of non-linear systems: Application to one-link manipulator.

The paper is focused on the problem of robust fault estimation of non-linear discrete-time systems. The general unknown input observer scheme and the H∞ framework are applied to design a robust fault estimation methodology. The main advantage of the proposed approach is its simplicity resulting from the boiling down of designing methodology to solving a set of linear matrix inequalities, which can be efficiently done by the application of modern computational packages. The resulting approach guaranties that a prescribed disturbance attenuation level is achieved with respect to the fault estimation error while guaranteeing the convergence of the observer with a possibly large decay rate of the state estimation error. The final part of the paper presents an illustrative example regarding the application of the proposed approach to faults estimation of the one-link manipulator.

Adaptive fault tolerant control: Application to a DC servo motor

The paper concerns a problem of robust adaptive fault tolerant control for linear discrete-time systems. The first part concerns the design problem of a robust observer, which can be used for simultaneous state and fault estimation along with decoupling of the so-called unknown input, which can represent modelling uncertainty as well as disturbances acting on the system. The appealing property of the proposed approach is that the effect of undecoupled part of disturbances can be further suitably minimized. The second part presents the problem of a robust fault-tolerant control design, which is suitably integrated with state and fault estimation scheme in order to cope with the fault effect. The subsequent part deals with the laboratory DC servo motor, while the final part shows experimental results, which clearly confirm the effectiveness of proposed approach.

Robust multiple sensor fault-tolerant control for dynamic non-linear systems: Application to the aerodynamical twin-rotor system

Abstract The paper deals with the problem of designing sensor-fault tolerant control for a class of non-linear systems. The scheme is composed of a robust state and fault estimator as well as a controller. The estimator aims at recovering the real system state irrespective of sensor faults. Subsequently, the fault-free state is used for control purposes. Also, the robust sensor fault estimator is developed in a such a way that a level of disturbances attenuation can be reached pertaining to the fault estimation error. Fault-tolerant control is designed using similar criteria. Moreover, a separation principle is proposed, which makes it possible to design the fault estimator and control separately. The final part of the paper is devoted to the comprehensive experimental study related to the application of the proposed approach to a non-linear twin-rotor system, which clearly exhibits the performance of the new strategy.

Adaptive Actuator Fault Estimation for DC Servo Motor

The paper present the problem of robust adaptive actuator fault estimation for linear discrete-time systems. The main part of this paper presents problem of design a robust observer that will be able to estimate state vector of the system, actuator fault and decoupling the effect of an unknown input. For that purpose, the structure for robust observer was proposed. The first part of the paper deals with the design of observer. The observer is designed in such a way that a prescribed attenuation level is achieved with respect to the fault estimation error and state estimation error. The subsequent part of the paper deals with laboratory system of DC servo motor that will be used in experiment. The final part of the paper shows the experimental results for DC servo motor system, which confirm the effectiveness of the proposed approach.

A quadratic boundedness approach to a neural network-based simultaneous estimation of actuator and sensor faults

The paper is devoted to the problem of a neural network-based robust simultaneous actuator and sensor faults estimator design for the purpose of the fault diagnosis of nonlinear systems. In particular, the methodology of designing a neural network-based fault estimator is developed. The main novelty of the approach is associated with possibly simultaneous sensor and actuator faults under imprecise measurements. For this purpose, a linear parameter-varying description of a recurrent neural network is exploited. The proposed approach guaranties a predefined disturbance attenuation level and convergence of the estimator. In particular, it uses the quadratic boundedness approach to provide uncertainty intervals of the achieved estimates. The final part of the paper presents an illustrative example concerning the application of the proposed approach to the multitank system fault diagnosis.

Simultaneous estimation of multiple actuator anc sensor faults for Takagi-Sugeno fuzzy systems

The paper is devoted to the problem of a Takagi-Sugeno(TS)-based robust simultaneous actuator and sensor faults estimator design for the purpose of the Fault Diagnosis (FD) of non-linear systems. The proposed methodology of designing a TS-based H∞ fault estimator is developed in this paper. The main novelty of the approach is associated with possibly of simultaneous sensor and actuator faults estimation. The developed approach guaranties a predefined disturbance attenuation level and convergence of the designed estimator. The illustrative part of the paper shows an example of the application of the developed approach in the task of the fault diagnosis of the multi-tank system.

Robust Guaranteed Cost Control for Nonlinear System Using Product Reduction Algorithm

The paper presents a robust Guaranteed Cost Control (GCC) for nonlinear system using Product Reduction Algorithm (PRA). The proposed approach starts with a general description of the nonlinear system with nonlinear term in the state equation and assumptions regarding to a nonlinear function. The subsequent part of the paper is concerned with the design of the robust controller using Linear Matrix Inequalities (LMIs). Next, an algorithm to solve linear optimization problem base on PRA is proposed. The final part presents results obtained for the two–tank system.

Guaranteed cost estimation and control for nonlinear system using LMI optimization

In the paper, a methodology for the guaranteed cost estimation and control for nonlinear system discrete-time systems is proposed. To solve such a challenging problem, the article starts with a general description of the system and assumptions regarding its nonlinearities. The subsequent part of the paper describes the design methodology of the robust observer and controller for the predefined cost function using linear matrix inequalities. The final part of the paper presents an illustrative example oriented towards a practical application to the multiple tank system, which illustrates the performance of the proposed approach.

Robust adaptive simultaneous state and fault estimation for nonlinear systems: Application to an aerodynamical system

The paper is concerned with the task of robust adaptive fault estimation and an unknown input decoupling for nonlinear systems using a quadratic boundedness approach. In particular, the fault estimation strategy and decoupling of the unknown input is based on an unknown input observer. The above methods are used to describe a robust fault and state observer problem by a set of linear matrix inequalities, which are efficiently handled by freely available solvers. The proposed approach allows obtaining a feasible set of joint state and fault estimation errors. Based on this knowledge, the confidence intervals of the system state and actuator fault, which supports diagnostic decisions, are proposed. The final part of the paper presents an illustrative example concerning an aerodynamical twin-rotor system, which exhibits the performance of the proposed approach.