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This article is concerned with a fault-tolerant control (FTC) scheme for feedback control systems with multiplicative faults by optimizing system performance with the aid of a reinforcement learning (RL) approach. To be specific, initially, based on the Youla–Kučera (YK) and dual YK parameterizations, a new performance-driven FTC method is proposed and its capability in dealing with multiplicative faults is proven. Then, data-driven implementation of this method using RL is elaborated. This implementation shows that RL can be applied efficiently by utilizing both plant model and data to recover the fault-induced system performance degradation. Finally, a benchmark study on an inverted pendulum system demonstrates the application of the proposed performance-driven FTC method. [ABSTRACT FROM AUTHOR]

This paper mainly focuses on the design and implementation of iterative estimation methods, and their applications to obtain the optimal fault detection for industrial control systems. More specifically, to generate residual signals with a minimum variance, minimum variance estimation is first addressed in terms of recursive least square (RLS) and Kalman filter by iterative interactions with the process environment. The optimal fault detection is then realized to provide the timely and optimal detection of potential problems by adopting these real-time minimum variance estimation schemes. Finally, the effectiveness of our schemes is demonstrated with a numerical example and experimental studies in the laboratory three-tank system. [ABSTRACT FROM AUTHOR]

This paper studies the configurations of fault-tolerant controllers for affine nonlinear systems. The design philosophy is highlighted by the observer and residual generator based controller parametrization and the integration of a fault diagnosis system. To be specific, a novel interpretation for the design of fault-tolerant controllers is first introduced with the combination of any stabilizing controller and a residual-driven dynamic compensator. It allows us to attain the separate design of system stability performance and fault tolerance. Under such circumstances, the whole design procedures finally realize the maintenance and life-circle management of affine nonlinear systems. In the end, a design scheme of the fault-tolerant control framework is proposed. [ABSTRACT FROM AUTHOR]

This paper proposes a scheme to achieve real-time stability performance monitoring (SPM) and designs performance recovery controllers (PRCs) for feedback control systems with multiplicative faults. To be specific, a stability performance indicator is presented with the aid of stable image representation (SIR) for multiplicative faults through coprime factorization techniques. On this basis, a systematically hierarchical SPM and PRC scheme is proposed with three thresholds derived to evaluate the performance degradation degree. Subsequently, an integrated model-based and data-driven SIR-based PRC is presented to recover system stability performance. The embedded PRC parameters are adaptive to system variations by means of identifying the SIR of the faulty plant through a dual parity vector. Besides, some QR-decomposition based data-driven techniques are provided for the implementation of PRC to improve computation efficiency. Finally, the effectiveness of the proposed approach is demonstrated on a boost circuit model. [ABSTRACT FROM AUTHOR]

This paper addresses L 2 observer-based fault detection issues for a class of nonlinear systems in the presence of parametric and dynamic uncertainties, respectively. To this end, three different types of uncertain affine nonlinear system models studied in this paper are described first. Then, the integrated design schemes of L 2 observer-based fault detection systems are derived with the aid of Hamilton–Jacobi inequalities (HJIs), respectively. Numerical examples are also provided in the end to demonstrate the effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

This note addresses parameterization issues of nonlinear observer-based fault detection (FD) systems which are composed of a residual generator, a residual evaluator and a threshold. Our study consists of two steps. In the first step, with the aid of nonlinear factorization and input-output operator techniques, we prove that any stable residual generator can be parameterized by a cascade connection of the process kernel representation and a post-filter that represents the parameter system. In the second step, based on the state-space representation of the parameterized residual generators, we investigate the so-called \mathcal L\infty- and \mathcal L2- classes of observer-based FD systems. This leads to the parameterization of the threshold settings for both classes of FD systems and, associated with them, to the characterization of the existence conditions. [ABSTRACT FROM PUBLISHER]

The delicate control of effluent quality in wastewater engineering becomes imperative for fulfilling its role in protecting the ecological environment and promoting the water recycling. In this paper, an adaptive multivariable self-healing control strategy for the wastewater treatment process (WWTP) operating under complicated environments and facing abnormal conditions. The control goal is to meet the strict effluent standards of the WWTP and to optimize the abnormal conditions by analyzing the process operating status in the event of sudden sensor failures. Therein, a new residual-triggered threshold decision method is designed and integrated into a dynamical detection mechanism to identify such sensor failures. After locating the failures, a multivariable self-healing control scheme incorporating failure compensation information is activated to guarantee the process output tracking and improve the self-recovery capability of faulty performance in the WWTP. Extensive experiments are carried out on a standardized wastewater treatment platform, and the regulation results on the key component concentrations indicate that the proposed control scheme can ensure excellent control performance and reduce the impact of sensor failures. [ABSTRACT FROM AUTHOR]