Partial and total actuator faults accommodation for input-affine nonlinear process plants

2010

Abstract This paper presents a method of design of a sensor faults tolerant control. The method is presented for the case of linear systems and then for the case of non linear systems described by Takagi-Sugeno models. The faults are initially estimated using a proportional integral observer. A mathematical transformation is used to conceive an augmented system in which the sensor fault appear as an unknown inputs.

International Journal of Applied Mathematics and Computer Science, 2008

The prospective work reported in this paper explores a new approach in order to enhance the performance of an Active Fault Tolerant Control System. This proposed technique is based on a modified recovery/trajectory control system which considered a reconfigurable reference input when performance degradation occurs on system due to faults in actuators dynamics. The added value of this work is to reduce the energy spent to achieve desired closed-loop performance. The feasibility of this work is illustrated using a three-tank system for slowly varying reference inputs corrupted by actuators faults.

A Fault Tolerant Control (FTC ) reconfigurable structure for a second order nonlinear process is developed. This structure is based on a Model Reference Adaptive Control (MRAC ) with a H ∞ Gain Scheduling controller designed using an Linear Parameter-Varying (LPV ) system: MRAC-H ∞ GS-LPV. The MRAC-H ∞ GS-LPV was compared with a structure named MRAC-LPV that is based on an MRAC design using an LPV system. A coupled-tank system is used as testbed in which different types of faults (abrupt-additive fault, gradualadditive fault and multiplicative fault) with different magnitudes and different operating points were tested. Results showed that the use of an H ∞ GS controller in combination with an MRAC improves the FTC performance because fault accommodation is faster. In addition, the structures based on Lyapunov theory were able to deal more efficiently with the faults and the changes in the operating points of the nonlinear model of the system. 5th Symposium on System Structure and Control Part of 2013

International Journal of Adaptive Control and Signal Processing, 2016

This paper investigates the problem of adaptive fault tolerant control for a class of dynamic systems with unknown un-modeled actuator faults. The fault model is assumed to be an unknown nonlinear function of control input, not in the traditional form in which the faults can be described as gain and/or bias faults. Using the property of the basic function of neural networks and the implicit function theorem, a novel neural networks-based fault tolerant controller is designed. Finally, the lateral dynamics of a front-wheeled steered vehicle is used to demonstrate the efficiency of the proposed design techniques.

2006

A fault-tolerant control strategy based on a robust model-based fault diagnosis approach is addressed. The approach considers the application of a robust control technique to integrate the control design and the fault diagnosis in the same framework. A model-based approach is used to estimate the nonlinear system's outputs and to synthesise the robust controller. The design objectives and the system's uncertainties are formulated in terms of H ∞ specifications and the problem is solved using the structured singular value (μ). The main purpose is to obtain a robust faulttolerant controller and a fault diagnosis system in a supervisory control framework. Residual signals are considered for fault diagnosis and fault accommodation purposes. This approach was applied to a nonlinear system: the Three-Tank benchmark plant.

Industrial & Engineering Chemistry Research, 2007

Most of the control schemes for chemical plants are developed under the assumption that the sensors and the actuators are free from faults. However, the occurrence of faults will cause degradation in the closed-loop performance, having an impact on safety, productivity, and plant economy. In this work, the main novelty is given by the enhancement produced through the integration of the fault detection and identification (FDI) system over a robust adaptive predictive control (RAPC) strategy specially thought to turn it as a faulttolerant control (FTC) scheme. Additionally, the FDI itself is original because of the sensor and actuator faults treatment. The biases in sensors are detected and quantified by using wavelet decomposition and the extra delays in actuators by applying online identification techniques to appropriately modify the controller action. It is important to remark that the extra time delay, detected particularly at the actuators, is a problem that occurs frequently in practice; however, the academic community has mostly omitted it up to now. This methodology can improve the overall performance for nonlinear stable plants because the FDI is specifically designed as a complement of those aspects that RAPC cannot handle at all. The control technique involves a commutation of a linear time-varying robust filter in the feedback path of the control loop in synchronization with an adaptive predictive controller. Through simulation studies of a continuous stirred tank reactor (CSTR) with jacket, where the integration between FDI and FTC has been implemented, it can be shown that the proposed methodology leads to significant improvement in comparison with the same control scheme without FDI, particularly when the fault magnitude increases.

International Journal of Robust and Nonlinear Control, 2022

In this paper, the fault-tolerant control (FTC) problem is investigated for a class of non-affine output-constrained multi-input multiple output (MIMO) nonlinear systems with actuator faults. The controlled systems contain unknown nonlinear functions, unknown external disturbance and immeasurable states. The fuzzy logic systems and a robust compensation function are employed to deal with the unknown nonlinear functions and non-affine nonlinear actuator fault problems. Then, the state observer and the nonlinear disturbance observer are developed for estimating the immeasurable states and unknown compounded disturbance, respectively. By using the barrier Lyapunov function method and in the unified framework of adaptive backstepping output feedback control design, a novel adaptive fuzzy fault-tolerant controller design scheme is developed. It is shown that all the variables of the closed-loop system are semi-globally uniformly bounded (SGUUB). Moreover, the system outputs cannot violate their predefined bounds in the presence of the non-affine nonlinear faults. A simulation is given to validate the effectiveness of the proposed approach.

2023

The adaptive fault tolerant control (FTC) problem is investigated for a class of high-order strict-feedback nonlinear systems with the actuator faults, and an adaptive fault tolerant control strategy is proposed in this paper. Compared with the traditional first-order strict-feedback nonlinear systems, high-order strict-feedback nonlinear systems are more general, but more difficult to handle. In particular, this system occurs actuator failure, which generates the additional terms. To address the unknown nonlinearities in the system, radial basis function neural networks are introduced to approximate the unknown continuous nonlinear functions. Based on Lyapunov stability theory, it is proved that the tracking error converges to a small adjustable neighborhood of the origin with all signals in the closed-loop system being bounded. Finally, a numerical example is used to verify the effectiveness of the control scheme proposed in this paper. INDEX TERMS High-order strict-feedback nonlinear systems, fault-tolerant control, adaptive control.

International Journal of Control, Automation and Systems, 2013

The goal of this paper is to describe a novel fault tolerant tracking control (FTTC) strategy based on robust fault estimation and compensation of simultaneous actuator and sensor faults. Within the framework of fault tolerant control (FTC) the challenge is to develop an FTTC design strategy for nonlinear systems to tolerate simultaneous actuator and sensor faults that have bounded first time derivatives. The main contribution of this paper is the proposal of a new architecture based on a combination of actuator and sensor Takagi-Sugeno (T-S) proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators together with a T-S dynamic output feedback control (TSDOFC) capable of time-varying reference tracking. Within this architecture the design freedom for each of the T-S estimators and the control system are available separately with an important consequence on robust L 2 norm fault estimation and robust L 2 norm closed-loop tracking performance. The FTTC strategy is illustrated using a nonlinear inverted pendulum example with time-varying tracking of a moving linear position reference.

AIAA Guidance, Navigation and Control Conference and Exhibit, 2008

In this paper, the problem of controlling systems with failures and faults is introduced, and an overview of recent work on direct adaptive control for compensation of uncertain actuator failures is presented. Actuator failures may be characterized by some unknown system inputs being stuck at some unknown (fixed or varying) values at unknown time instants, that cannot be influenced by the control signals. The key task of adaptive compensation is to design the control signals in such a manner that the remaining actuators can automatically and seamlessly take over for the failed ones, and achieve desired stability and asymptotic tracking. A certain degree of redundancy is necessary to accomplish failure compensation. The objective of adaptive control design is to effectively use the available actuation redundancy to handle failures without the knowledge of the failure patterns, parameters, and time of occurrence. This is a challenging problem because failures introduce large uncertainties in the dynamic structure of the system, in addition to parametric uncertainties and unknown disturbances. The paper addresses some theoretical issues in adaptive actuator failure compensation: actuator failure modeling, redundant actuation requirements, plant-model matching, error system dynamics, adaptation laws, and stability, tracking, and performance analysis. Adaptive control designs can be shown to effectively handle uncertain actuator failures without explicit failure detection. Some open technical challenges and research problems in this important research area are discussed.