Robust fault estimation for stochastic Takagi-Sugeno fuzzy systems

Nowadays, industrial plants are calling for high-performance fault diagnosis techniques to meet stringent requirements on system availability and safety in the event of component failures. This paper deals with robust fault estimation problems for stochastic nonlinear systems subject to faults and unknown inputs relying on Takagi-Sugeno fuzzy models. Augmented approach jointly with unknown input observers for stochastic Takagi-Sugeno models is exploited here, which allows one to estimate both considered faults and full system states robustly. The considered unknown inputs can be either completely decoupled or partially decoupled by observers. For the un-decoupled part of unknown inputs, which still influence error dynamics, stochastic input-to-state stability properties are applied to take nonzero inputs into account and sufficient conditions are achieved to guarantee bounded estimation errors under bounded unknown inputs. Linear matrix inequalities are employed to compute gain matrices of the observer, leading to stochastic input-to-state-stable error dynamics and optimization of the estimation performances against un-decoupled unknown inputs. Finally, simulation on wind turbine benchmark model is applied to validate the performances of the suggested fault reconstruction methodologies

Robust finite-time fault estimation for stochastic nonlinear systems with Brownian motions

Motivated by real-time monitoring and fault diagnosis for complex systems, the presented paper aims to develop effective fault estimation techniques for stochastic nonlinear systems subject to partially decoupled unknown input disturbances and Brownian motions. The challenge of the research is how to ensure the robustness of the proposed fault estimation techniques against stochastic Brownian perturbations and additive process disturbances, and provide a rigorous mathematical proof of the finite-time input-to-stabilization of the estimation error dynamics. In this paper, stochastic input-to-state stability and finite-time stochastic input-to-state stability of stochastic nonlinear systems are firstly investigated based on Lyapunov theory, leading to simple and straightforward criteria. By integrating augmented system approach, unknown input observer technique, and finite-time stochastic input-to-state stability theory, a highly-novel fault estimation technique is proposed. The convergence of the estimation error with respect to un-decoupled unknown inputs and Brownian perturbations is proven by using the derived stochastic input-to-state stability and finite-time stochastic input-to-state stability theorems. Based on linear matrix inequality technique, the robust observer gains can be obtained in order to achieve both stability and robustness of the error dynamic. Finally, the effectiveness of the proposed fault estimation techniques is demonstrated by the detailed simulation studies using a robotic system and a numerical example

Integrated fault estimation and fault-tolerant control for stochastic systems with Brownian motions

This paper presents an integrated robust fault estimation and fault‐tolerant control technique for stochastic systems subjected to Brownian parameter perturbations. The augmented system approach, unknown input observer method, and optimization technique are integrated to achieve robust simultaneous estimates of the system states and the means of faults concerned. Meanwhile, a robust fault‐tolerant control strategy is developed by using actuator and sensor signal compensation techniques. Stochastic linear time‐invariant systems, stochastic systems with Lipschitz nonlinear constraint, and stochastic systems with quadratic inner‐bounded nonlinear constraint are respectively investigated, and the corresponding fault‐tolerant control algorithms are addressed. Finally, the effectiveness of the proposed fault‐tolerant control techniques is demonstrated via the drivetrain system of a 4.8 MW benchmark wind turbine, a 3‐tank system, and a numerical nonlinear model

High performance disturbance observer based control system design for permanent magnet synchronous AC machine applications

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonAn electrical machine is one of the main workforces in different industries and serves them in various applications. Machine drive control design involves many technical issues for efficient and robust exploitation. Over several decades, Permanent Magnet Synchronous Motor (PMSM) is getting preferred for industrial applications over its counterpart Squirrel Cage Induction Motor (SCIM) drive, because of their higher efficiency, power density, and higher torque to inertia ratio. In the prospective that PMSM drives are considered the drives of the future, there are still technical challenges and issues related to PMSM control. Many studies have been devoted to PMSM control in the past, but there are still some open research areas that bring worldwide researchers’ interests back to PMSM drive control. One of the approaches that may facilitate better performance, higher efficiency, and robust and reliable work of the control system is the disturbance observer-based control (DOBC) with linear and nonlinear output feedback control for PM synchronous machine applications. DOBC is adopted due to its ability to reject external and internal disturbances with improving tracking performance in the variable speed wind energy conversion system (WECS) to maximize power extraction. The high order disturbance observer (HODO) is utilized to estimate the aerodynamic torque-based wind speed without the use of a traditional anemometer, which reduces the overall cost and improves the reliability of the whole system. Also, this method has been designed to improve the angular shaft speed tracking of the PMSM system under load torque disturbance and speed variations. The model-based linear and nonlinear feedback control are used in the proposed control systems. The sliding mode control (SMC) with switching output feedback control law and integral SMC with linear feedback and state-dependent Riccati equation (SDRE) based approaches have been designed for the systems. The SDRE control accounts for the nonlinear multivariable structure of the WECS and is approximated with Taylor series expansion terms. The chattering inherited from SMC is eliminated by the continuous approximation technique. The sliding mode is guaranteed by eliminating the reaching mode in the proposed integral SMC. The model-free cascaded linear feedback control system based on the proportional-integral (PI) controllers use a back-calculation algorithm anti-windup scheme. The proposed speed controllers are synthesized with HODO to compensate for the external disturbance, model uncertainty, noise, and modelling errors. Moreover, servomechanism-based SDRE control, a near-optimal control system is designed to suppress the model uncertainty and noise without the use of disturbance observers. The proposed control systems for PMSM speed regulation have demonstrated a significant improvement in the angular shaft speed-tracking performance at the transients. Their performances have been tested under speed, load torque variations, and model uncertainty. For example, HODO-based SMC with switching output feedback control law (SOFCL) has demonstrated improvement by more than 78% than the PI-PI control system of the PMSM. The performance of the HODOs-based Integral SMC with SDRE nonlinear feedback is improved by 80.5% under external disturbance, model uncertainty, and noise than Integral SMC with linear feedback in the WECS. The HODO-based SDRE control with servomechanism has shown an 80.2% improvement of mean absolute percentage error under disturbances than Integral SMC with linear feedback in the WECS. The PMSM speed tracking performance of the proposed HODO-based discrete-time PI-PI control system with back-calculation algorithm anti-windup scheme is improved by 87.29% and 90.2% in the speed commands and load torque disturbance variations scenarios respectively. The simulations for testing the proposed control system of the PMSM system and WECS have been implemented in Matlab/Simulink environment. The PMSM speed control experimental results have been obtained with Lucas-Nuelle DSP-based rapid control prototyping kit.Center for International Program “Bolashak” of the Ministry of Education and Science Republic of Kazakhsta

Detection of replay attacks in cyber-physical systems using a frequency-based signature

This paper proposes a frequency-based approach for the detection of replay attacks affecting cyber-physical systems (CPS). In particular, the method employs a sinusoidal signal with a time-varying frequency (authentication signal) into the closed-loop system and checks whether the time profile of the frequency components in the output signal are compatible with the authentication signal or not. In order to carry out this target, the couplings between inputs and outputs are eliminated using a dynamic decoupling technique based on vector fitting. In this way, a signature introduced on a specific input channel will affect only the output that is selected to be associated with that input, which is a property that can be exploited to determine which channels are being affected. A bank of band-pass filters is used to generate signals whose energies can be compared to reconstruct an estimation of the time-varying frequency profile. By matching the known frequency profile with its estimation, the detector can provide the information about whether a replay attack is being carried out or not. The design of the signal generator and the detector are thoroughly discussed, and an example based on a quadruple-tank process is used to show the application and effectiveness of the proposed method.Peer ReviewedPostprint (author's final draft

Robust fault tolerant control of induction motor system

Research into fault tolerant control (FTC, a set of techniques that are developed to increase plant availability and reduce the risk of safety hazards) for induction motors is motivated by practical concerns including the need for enhanced reliability, improved maintenance operations and reduced cost. Its aim is to prevent that simple faults develop into serious failure. Although, the subject of induction motor control is well known, the main topics in the literature are concerned with scalar and vector control and structural stability. However, induction machines experience various fault scenarios and to meet the above requirements FTC strategies based on existing or more advanced control methods become desirable. Some earlier studies on FTC have addressed particular problems of 3-phase sensor current/voltage FTC, torque FTC, etc. However, the development of these methods lacks a more general understanding of the overall problem of FTC for an induction motor based on a true fault classification of possible fault types.In order to develop a more general approach to FTC for induction motors, i.e. not just designing specific control approaches for individual induction motor fault scenarios, this thesis has carried out a systematic research on induction motor systems considering the various faults that can typically be present, having either “additive” fault or “multiplicative” effects on the system dynamics, according to whether the faults are sensor or actuator (additive fault) types or component or motor faults (multiplicative fault) types.To achieve the required objectives, an active approach to FTC is used, making use of fault estimation (FE, an approach that determine the magnitude of a fault signal online) and fault compensation. This approach of FTC/FE considers an integration of the electrical and mechanical dynamics, initially using adaptive and/or sliding mode observers, Linear Parameter Varying (LPV, in which nonlinear systems are locally decomposed into several linear systems scheduled by varying parameters) and then using back-stepping control combined with observer/estimation methods for handling certain forms of nonlinearity.In conclusion, the thesis proposed an integrated research of induction motor FTC/FE with the consideration of different types of faults and different types of uncertainties, and validated the approaches through simulations and experiments