47072-G9
Diagnosis and Manaement of Faults in Distributed Chemical Processes
One of the central problems at the interface of process control and operations is the development of systematic methods for the diagnosis and handling of faults. The motivation for studying this problem stems in part from the vulnerability of automated industrial processes to malfunctions in the control actuators, measurement sensors and process equipment, as well as the increased emphasis placed on safety, reliability and profitability in the operation of industrial processes. Despite the substantial and growing body of literature on this problem, most of the previous research work in this area has focused on spatially homogeneous processes modeled by systems of ordinary differential equations. Yet, there are many important industrial processes -- such as transport-reaction and particulate processes -- that are characterized by spatial variations and are more appropriately modeled by Partial Differential Equations (PDEs). Major bottlenecks in the design of fault diagnosis and fault-tolerant control systems for distributed processes include the infinite-dimensional nature of the models describing the dynamics of these processes, as well as the complex nonlinearities and uncertainties that characterize these models.
To overcome these problems, the research work of my group focuses on developing general methodologies for the integration of fault diagnosis and fault management in distributed processes by bringing together tools from model reduction, nonlinear and robust control techniques, and hybrid system theory. Exploiting the inherently low-dimensional dynamic behavior of certain classes of distributed parameter systems, we have been able to formulate and solve the problem on the basis of appropriate low-order models that are suitable for the design of practically implementable control and diagnosis algorithms, and are amenable to rigorous closed-loop analysis. The diagnosis and control algorithms have been successfully applied to simulated models of transport-reaction and particulate processes.
(1) Fault detection, isolation and reconfiguration in transport-reaction processes
In this direction, our research efforts have focused on the development of integrated fault detection and isolation (FDI) and fault-tolerant control (FTC) architectures for transport-reaction processes modeled by highly dissipative nonlinear PDEs with control constraints and control actuator faults. Specifically, we first developed a model-based fault-tolerant control architecture that brings together model-based fault detection, spatially distributed feedback and supervisory control to orchestrate switching between different actuator configurations in the event of faults. The architecture was subsequently generalized to address the problem of actuator fault isolation and incorporate performance considerations in the control reconfiguration logic. Practical implementation issues such as the availability of only a limited number of measurements were accounted for by incorporating a state estimation scheme into the control structure and modifying the FDI and switching logic appropriately. Finally, the problem of designing integrated FDI-FTC architectures that are robust with respect to model uncertainty and measurement errors has been addressed using a performance-based approach that unites FDI and robust control techniques and leads naturally to an explicit characterization of the regions where robust FDI is feasible under uncertainty and constraints. The theoretical results have been successfully applied to simulated models of diffusion- convection-reaction processes. Our work in this area has been recognized by a number of awards to my doctoral student, Sathyendra Ghantasala, including (1) a Best Presentation In Session Award at the 2007 American Control Conference, and (2) travel grants from the American Automatic Control Council and the AIChE Computing and Systems Technology Division to present results from our work at the 2007 American Control Conference and the 2007 AIChE Annual Meeting, respectively.
(2) Fault detection, isolation and compensation in particulate processes
In addition to transport-reaction processes, our work has also focused on the design of integrated FDI-FTC systems for particulate processes described by population balance models with control constraints, actuator faults and limited measurements. This problem is motivated by the need to minimize the impact of control system failures on the achievable particle size distribution, which is critical to maintaining the desired end product quality in particulate processes. The proposed methodology has been generalized to multi-input particulate processes to incorporate fault isolation capabilities and account explicitly for the presence of model uncertainty, and has been applied successfully to simulated models of continuous crystallizers with and without a fines trap.
In addition to being the first studies in process control to address the fault diagnosis and fault-tolerant control problems for distributed processes in an integrated fashion, a key feature of our approach is the explicit linkage, via singular and regular perturbation techniques, between the detection and isolation tasks on the one hand, and the structure of the distributed parameter system, on the other. This linkage facilitates the derivation of appropriate alarm thresholds for implementing the reduced-order model-based FDI-FTC architectures on the infinite-dimensional system. We are currently applying the developed diagnosis and control architectures to nonlinear distributed parameter models of low-density polyethylene reactors and proton-exchange membrane fuel cells.
