A Supervisory Approach to Fault-Tolerant Control of Linear Multivariable Systems

Abstract

Coventional control schemes are developed under the assumption that the sensors and actuators are free from faults. However, the occurrence of faults will cause degradation in the closed-loop performance and also will have an impact on safety, productivity, and plant economy. In the present work, we have proposed a fault-tolerant control scheme (FTCS) by integrating a fault detection and identification (FDI) technique with conventional control. The principal component of our proposed FTCS is a compensation strategy (supervisory system) which uses the information provided by the FDI to appropriately modify the controller as well as the model used in FDI. This allows online application of the FTCS without causing significant degradation in the closed-loop performance due to the occurrences of biases in sensors and actuators or due to changes in unmeasured disturbance variables and due to moderate change in process parameters. Through stochastic simulation studies of a continuous stirred tank reactor process, we demonstrate that our proposed FTCS leads to significant improvement in the closed-loop performance in comparison to a conventional control scheme, especially as the fault magnitude increases. The proposed compensation scheme also allows identification of multiple faults that occur sequentially in time and is also found to be robust with respect to moderate plant−model mismatch.

Fault tolerant control for a dearomatisation process

“…Active FTC strategies utilising model predictive control (MPC) have been studied by e.g. Maciejowski [17], Pranatyasto and Qin [25] and Prakash et al [24]. More recently Jarvinen et al [11] showed that the inherent accommodation properties of model predictive control (MPC) can readily be exploited to implement different types of FTC strategies, providing the necessary FDI information is available.…”

Unknown input modeling and robust fault diagnosis using black box observers

“…Therefore, a simple statistical test referred to as the fault detection test (FDT) is applied at each time instant to estimate the time of occurrence of a fault. If FDT is rejected at some time t, the occurrence of a fault is further confirmed by applying a cumulative statistical test known as the fault confirmation test (FCT) on the innovation sequence in the time interval ½t; t þ N (see [4,8] for details). If this test rejects the null hypothesis (no fault hypothesis) then the occurrence of the fault at time t is confirmed.…”

“…In addition, as discussed in Prakash et al [4], the state estimates are corrected for the bias in the state estimates introduced due to delay of N sampling instants in identifying the fault.…”

“…To maintain good control performance despite the occurrence of any type of soft fault, an active fault tolerant control scheme (FTCS) has been developed by Prakash et al [4] and Patwardhan et al [8] by appropriately integrating the GLR based FDI method with controller. Typically, a conventional feedback controller with integral action can satisfactorily deal with actuator biases, disturbances and process parameter changes in the absence of input constraints.…”

“…Among the various approaches proposed in the literature, analytical redundancy based methods are found to be most suitable for devising an active fault tolerant scheme, since the information it provides facilitates explicit corrective measure. Recently, Prakash et al [4,5] have developed an active fault tolerant control scheme (FTCS), which integrates a model based FDI methodology based on generalized likelihood ratio (GLR) method [6,7] with a controller, through an on-line compensation mechanism. The prime requirement of GLR method is the availability of a process model (estimator) for normal operation and fault modes, describing the process behavior for each hypothesized fault.…”