Shreekant Gayaka

Global stabilization of a chain of integrators with input saturation and disturbances: A new approach

In this paper, the problem of global stabilization for a chain of integrators in presence of input saturation and disturbances is solved. A novel and elegant approach to solve this problem, in absence of disturbances, was proposed by Teel [1] using saturation functions and coordinate transformation. With Teels work as foundation, many results have been proposed to improve the performance of tracking/stabilizing controllers for chain of integrators. However, in presence of disturbances, the coordinate transformation can considerably shrink the region where the controller is unsaturated. In this work, we present a modified backstepping like approach to solve the global stabilization problem which does not rely on coordinate transformation. Comparative studies performed using a third order integrator chain proves the effectiveness of the proposed scheme.

Fault Detection, Identification and Accommodation for an Electro-hydraulic System: An Adaptive Robust Approach

Abstract In the present work, we use an adaptive robust approach for fault detection and accommodation in electro-hydraulic systems. It is well known fact that any realistic model of a hydraulic system suffers from significant extent of uncertain nonlinearities and parametric uncertainties. An adaptive robust scheme is robust to such uncertainties and tracks the change in parameters reliably. Consequently, such a scheme becomes a natural choice for designing robust fault detection algorithms for electro-hydraulic systems. In this paper, we present the main results obtained by using adaptive robust state reconstruction and adaptive robust observers for fault detection in electro-hydraulic systems. Furthermore, the useful information about faults contained in the residual is used for designing an active fault-tolerant controller. We give an outline of the stability analysis for the faulty closed loop system, which shows that all states remain bounded and desired performance is restored to acceptable limits after the occurrence of fault. Simulation results show the effectiveness of the proposed scheme.

An Adaptive Robust Scheme for Multiple Actuator Fault Accommodation

In this paper, we solve the problem of output tracking for linear systems in presence of unknown actuator failures using discontinuous projection based output feedback adaptive robust control (ARC) scheme. The faulty actuators are characterized as unknown inputs stuck within certain bounds at unknown instants of time. This problem is of prime importance for safety critical missions like flight control system. Many existing techniques to solve this problem use model reference adaptive control (MRAC), which is not well suited for handling various disturbances and modeling errors inherent to any realistic system model. In comparison, the backstepping based output feedback ARC approach used here can effectively deal with such uncertainties. Simulation studies are carried out on a linearized Boeing 747 model, which shows the effectiveness of the proposed scheme. Furthermore, we compare our simulation results with that of MRAC in presence of disturbances, which clearly illustrates the superior performance of the proposed ARC based actuator fault compensation scheme.Copyright

Adaptive robust actuator fault-tolerant control in presence of input saturation

In this article, we solve the problem of unknown actuator fault accommodation for a class of uncertain nonlinear systems, with explicit consideration of input saturation. A review of the existing literature reveals that fault-tolerant controllers are often designed without any regard to actuator saturation, and it is assumed that they will not saturate in spite of faults. In reality, however, considerable amount of control effort needs to be expended for suppressing the transients due to actuator faults, which can easily saturate the working actuators. In the present work, an indirect adaptive robust fault-tolerant controller is proposed which explicitly takes into account the actuator limits. Furthermore, the indirect design ensures that adaptation mechanism is not affected adversely due to actuator saturation. Finally, simulation studies performed on a nonlinear hypersonic aircraft model are presented to demonstrate the effectiveness of the proposed scheme in dealing with actuator faults in presence of input saturation.

Global stabilization of a chain of integrators with input saturation and disturbances

In this paper, the problem of global stabilization for a chain of integrators in presence of input saturation and disturbances is solved. A novel and elegant approach to solve this problem, in absence of disturbances, was proposed by Teel [1] using saturation functions and coordinate transformation. With Teels work as foundation, many results have been proposed to improve the performance of tracking/stabilizing controllers for chain of integrators. However, in presence of disturbances, the coordinate transformation can considerably shrink the region where the controller is unsaturated. In this work, we present a modified backstepping like approach to solve the global stabilization problem which does not rely on coordinate transformation. Comparative studies performed using a third order integrator chain proves the effectiveness of the proposed scheme.

Fault detection for nonlinear systems in presence of input unmodeled dynamics

This paper presents the problem of fault detection in the presence of input unmodeled dynamics. There are mainly two sources of uncertainties for a system in addition to external disturbances: parametric uncertainties and unmodeled dynamics. For nonlinear systems, the problem of fault detection and isolation has been studied under the assumption that modeling uncertainty can be bounded by an a priori known function. Many robust algorithms have been designed based on this assumption. But, the problem of fault detection in the presence of dynamic uncertainties for nonlinear systems has not been addressed by many researchers. The goal of this work is to focus on the problem of actuator fault detection in the presence of input unmodeled dynamics. We use state-estimation errors as residuals for fault detection and monitoring the system for any off-nominal behavior. A rigorous analysis is done to understand the effects of unmodeled dynamics on the process of fault detection. Based on the analysis, we derive a threshold function for the purpose of fault detection, which can decouple the effects of fault and unmodeled dynamics. Finally, simulations are performed to show the effectiveness of the proposed method.

Accommodation of partial actuator faults using output feedback based adaptive robust control

This work considers the problem of partial actuator fault accommodation. The faulty actuators are characterized by a loss in efficiency, which can potentially lead to system instability or degraded system performance. Conventional model reference adaptive control has been used to solve this problem in the literature, which provides a natural setting to solve such problems by virtue of its online learning capabilities. Unfortunately, such techniques can lead to unbounded states when output disturbances and other modeling uncertainties are considered. In the present work, we make the problem more practical by explicitly taking into account these factors. Furthermore, we assume that faults occur at unknown instants of time and only limited state information is available. For solving this problem, we develop an output feedback adaptive robust control (ARC) based technique, which can effectively deal with all the constraints and uncertainties present in the system. The technique combines the output feedback based adaptive backstepping with robust control techniques and uses discontinuous projection to ensure the unknown parameter estimates stay within a known convex set. Comparative simulation studies are performed on a linearized Boeing 747 model to evaluate performance of the proposed scheme versus conventional MRAC based technique.

An Output Feedback Based Adaptive Robust Fault Tolerant Control Scheme for a Class of Nonlinear Systems

In this paper we present an output feedback based Adaptive Robust Fault Tolerant Control (ARFTC) strategy to solve the problem of output tracking in presence of actuator failures, disturbances and modeling uncertainties for a class of nonlinear systems. The class of faults addressed here include stuck actuators, actuator loss of efficiency or a combination of the two. We assume no a priori information regarding the instant of failure, failure pattern or fault size. The ARFTC combines the robustness of sliding mode controllers with the online learning capabilities of adaptive control to accommodate sudden changes in system parameters due to actuator faults. Comparative simulation studies are carried out on a nonlinear hypersonic aircraft model, which shows the effectiveness of the proposed scheme over back-stepping based robust adaptive fault-tolerant control.Copyright

A Multivariable Approach to EGR-VGT Actuator Control Problem

The combined use of Variable Geometry Turbine (VGT) and Exhaust Gas Recirculation (EGR) gives us an opportunity to reduce emissions, without compromising the need to generate more power. In the present work, a multivariable approach is used to tackle the EGR-VGT actuator control problem. A linear multivariable controller is designed using Lyapunovs Indirect Method, based on the Jacobian matrix of the system. Then, some stronger conditions are sought to be satisfied by the Jacobian matrix, which would ensure the Global Asymptotic Stability of the system. These conditions are derived using Nonlinear Contraction Analysis. Finally, simulations are performed on a simplified model with three states to evaluate the performance of the controllers.Copyright

Fault Detection for a Class of Nonlinear Systems in Presence of Unmodeled Dynamics and Parametric Uncertainties Using Adaptive Robust Observers

The goal of this work is to present some theoretical results which can be used for increasing fault sensitivity of a detection scheme, without sacrificing robustness. Robustness against modeling uncertainties and fault sensitivity are two contradicting demands, and typically, one is achieved at the expense of the other. The main reason for this trade-off is the use of a worst case scenario bound for modeling uncertainties at the residual evaluation stage. Many robust fault detection algorithms have been proposed based on the assumption that an a priori known functional bound exists for modeling uncertainties. In the present work, we look into the two main sources of modeling uncertainties, parametric uncertainties and unmodeled dynamics, and carefully examine their effect on residual evaluation. Finally, based on our analysis, and certain assumptions about the unmodeled dynamics and parametric uncertainties, we propose a threshold for residual generation and evaluation, and analytically prove its superior robustness and sensitivity properties.Copyright