(264e) Networked Monitoring and Fault-Tolerant Control of Nonlinear Process Systems

Abnormal situations cost U.S. industries over $20 billion each year, making fault handling a critical area of research. It is important to design systems capable of detecting and handling such process or control system abnormalities. The occurrence of faults in chemical processes poses a number of challenges in process monitoring (and subsequently in fault-tolerant control) and has been studied using both model-based and data-based approaches. Specifically, the problem of using fundamental process models for the purpose of detecting faults has been studied extensively in the context of linear systems; and recently, some existential results in the context of nonlinear systems have been derived. The analytical (model-based) approach to fault detection relies on the use of fundamental models for the construction of residuals, that capture some measure of the difference between the normal and "faulty" dynamics, to achieve fault detection and isolation. Statistical and pattern recognition techniques for data analysis and interpretation, on the other hand, use past plant data to construct indicators that identify deviations from normal operation, and help in detecting faults. Recently, model-based monitoring systems which utilize asynchronous measurements from sensor networks have been developed.

In a previous work [1], we introduced a two-tier control architecture for nonlinear process systems with both continuous and asynchronous sensing and/or actuation to augment preexisting, local control networks with additional networked sensors and actuators. This class of systems arises naturally in the context of process control systems based on point-to-point wired links integrated with networked wired/wireless communication and utilizing multiple heterogeneous measurements (e.g., temperature and concentration). In this architecture, the local, pre-existing control system uses continuous sensing and actuation and an explicit control law (for example, the local controller may be a classical controller, like a proportional-integral-derivative controller, or a nonlinear controller designed via geometric or Lyapunov-based control methods for which an explicit formula for the calculation of the control action is available). In addition, a networked control system was designed using Lyapunov-based model predictive control to profit from both the continuous and the asynchronous measurements as well as from additional networked control actuators. The two-tier control architecture preserves the stability properties of the local control system while improving the closed-loop performance.

This work focuses on the networked monitoring and reconfiguration of two-tier networked control systems applied to a general nonlinear processes in the presence of control actuator faults. Specifically, a general class of nonlinear process systems is first considered and is controlled by a two-tier networked control system integrating a local control system using continuous sensing/actuation with a networked control system using asynchronous sensing/actuation. To deal with control actuator faults that may occur in the closed-loop system and eliminate the ability of the networked control system to stabilize the process, a networked fault detection and isolation (FDI) and fault-tolerant control (FTC) system is designed which detects and isolates actuator faults and determines how to reconfigure the two-tier networked control system to handle the actuator faults and ensure closed-loop stability. The FDI/FTC system uses continuous and asynchronous measurements and deals with faults in the actuators of both the local and networked control systems. A detailed mathematical analysis is carried out to determine precise conditions under which the proposed networked FDI/FTC scheme guarantees closed-loop system stability. The method is demonstrated using a reactor-separator process consisting of two continuously stirred tank reactors and a flash tank separator with recycle stream.

[1] J. Liu, D. Munoz de la Pena, B. J. Ohran, P. D. Christofides, and J. F. Davis. A two-tier control architecture for nonlinear process systems with continuous/asynchronous feedback, in Proceedings of 2009 American Control Conference, 2009.