A New Method for Multisensor Data Fusion Based on Wavelet Transform in a Chemical Plant

Abstract This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet "db4" functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter for the final state estimation. The recent data are recursively utilized to apply wavelet transform and extract the variance of the updated data, which makes it suitable to be applied to both static and dynamic systems corrupted by noisy environments. The method has suitable performance in state estimation in comparison with the other alternative algorithms. A three-tank benchmark system has been adopted to comparatively demonstrate the performance merits of the method compared to a known algorithm in terms of efficiently satisfying signal-tonoise (SNR) and minimum square error (MSE) criteria

A passive fault-tolerant control strategy for a non-linear system: An application to the two tank conical non-interacting level control system

In practical engineering systems, unknown actuator, sensor or system component faults frequently occur, which results from component and interconnection failures, degrade control performance, system stability, and profitability, and even arise hazardous situation. To avoid abnormal activity like faults and maintain system control performance subject to faults occurring into the system, the Fault-tolerant Control (FTC) is a realistic approach to address the unwanted situation. The two-tank conical system is widely used in chemical and food process industries because of its greater advantages. The non-interacting configuration of the two-tank conical system is highly nonlinear due to its shape and varying area of the tank thought the height of the tank, as a consequence level control of this system is extremely difficult. The paper attributes to design a Passive Fault-tolerant Control Strategy (PFTCS) for a Two-tank conical Non Interacting Level Control System (TTCNILCS) subject to the major system (leak), sensor, and actuator faults with external process disturbances. PFTC will increase system control performance and system stability acceptable level in the presence of sensor, system, and actuator faults. The simulation results demonstrate the proposed PFTC strategy has definite fault tolerant ability against the system and actuator faults also it has good disturbance rejection capability. To verify the efficacy of the proposed PFTC strategy Mean Square Error (MSE) and Root Mean Square Error (RMSE) Integral Absolute Error (IAE) indices are used

Data-based fault-tolerant model predictive controller an application to a complex dearomatization process

The tightening global competition during the last few decades has been the driving force for the optimisation of industrial plant operations through the use of advanced control methods, such as model predictive control (MPC). As the occurrence of faults in the process measurements and actuators has become more common due to the increase in the complexity of the control systems, the need for fault-tolerant control (FTC) to prevent the degradation of the controller performance, and therefore the better optimisation of the plant operations, has increased. Traditionally, the most actively studied fault detection and diagnosis (FDD) components of the FTC strategies have been based on model-based approaches. In the modern process industries, however, there is a need for the data-based FDD components due to the complexity and limited availability of mechanistic models. Recently, active FTC strategies using fault accommodation and controller reconfiguration have become popular due to the increased computation capacity, easier adaptability and lower overall implementation costs of the active FTC strategies. The main focus of this thesis is on the development of an active data-based fault-tolerant MPC (FTMPC) for an industrial dearomatization process. Three different parallel-running FTC strategies are developed that utilise the data-based FDD methods and the fault accommodation- and controller reconfiguration-based FTC methods. The performances of three data-based FDD methods are first compared within an acknowledged testing environment. Based on the preliminary performance testing, the best FDD method is selected for the final FTMPC. Next, the performance of the FTMPC is validated with the simulation model of the industrial dearomatization process and finally, the profitability of the FTMPC is evaluated based on the results of the evaluation. According to the testing, the FTMPC performs efficiently and detects and prevents the effects of the most common faults in the analyser, flow and temperature measurements, and the controller actuators. The reliability of the MPC is increased and the profitability of the dearomatization process is enhanced due to the lower off-spec production