Supervisory Event-Triggered Control of Uncertain Process Networks: Balancing Stability and Performance

This work presents a methodological framework for the design of a resource-aware supervisory control system for process networks with model uncertainty and communication resource constraints. The developed framework aims to balance the objective of closed-loop stabilization of the overall network with that of meeting the local performance requirements of the component subsystems while keeping the rate of data transfer between the local control systems to a minimum. First, a quasi-decentralized networked control structure, with a set of local model-based controllers communicating with one another over a shared communication medium at discrete times, is designed. A Lyapunov stability analysis of the closed-loop system is then carried out, and the results are used to derive appropriate bounds on the local model state estimation errors as well as the dissipation rates of the local control Lyapunov functions. These bounds are used as stability and performance thresholds to trigger communication between the local control systems and a higher-level supervisor that coordinates the transfer of state measurements between the distributed control systems. A breach of the local stability and performance thresholds generates alarm signals which are transmitted to the supervisor to determine which subsystems should communicate with one another. The supervisor employs a composite Lyapunov function to assess the impact of the local threshold breaches on the stability of the overall closed-loop system. The supervisory communication logic takes account of the evolution of the local and composite Lyapunov functions in order to balance the stability and local performance requirements. Finally, the developed framework is demonstrated using a representative chemical process network and compared with other unsupervised event-based control approaches. It is shown that the supervisory event-based control approach leads to a more judicious utilization of network resources that helps improve closed-loop process performance in the presence of unexpected disturbances and input rate constraints

Forecast-Triggered Model Predictive Control of Constrained Nonlinear Processes with Control Actuator Faults

This paper addresses the problem of fault-tolerant stabilization of nonlinear processes subject to input constraints, control actuator faults and limited sensor–controller communication. A fault-tolerant Lyapunov-based model predictive control (MPC) formulation that enforces the fault-tolerant stabilization objective with reduced sensor–controller communication needs is developed. In the proposed formulation, the control action is obtained through the online solution of a finite-horizon optimal control problem based on an uncertain model of the plant. The optimization problem is solved in a receding horizon fashion subject to appropriate Lyapunov-based stability constraints which are designed to ensure that the desired stability and performance properties of the closed-loop system are met in the presence of faults. The state-space region where fault-tolerant stabilization is guaranteed is explicitly characterized in terms of the fault magnitude, the size of the plant-model mismatch and the choice of controller design parameters. To achieve the control objective with minimal sensor–controller communication, a forecast-triggered communication strategy is developed to determine when sensor–controller communication can be suspended and when it should be restored. In this strategy, transmission of the sensor measurement at a given sampling time over the sensor–controller communication channel to update the model state in the predictive controller is triggered only when the Lyapunov function or its time-derivative are forecasted to breach certain thresholds over the next sampling interval. The communication-triggering thresholds are derived from a Lyapunov stability analysis and are explicitly parameterized in terms of the fault size and a suitable fault accommodation parameter. Based on this characterization, fault accommodation strategies that guarantee closed-loop stability while simultaneously optimizing control and communication system resources are devised. Finally, a simulation case study involving a chemical process example is presented to illustrate the implementation and evaluate the efficacy of the developed fault-tolerant MPC formulation

Integrating robustness, optimality and constraints in control of nonlinear processes

Abstract This work focuses on the development of a uni"ed practical framework for control of single-input}single-output nonlinear processes with uncertainty and actuator constraints. Using a general state-space Lyapunov-based approach, the developed framework yields a direct nonlinear controller design method that integrates robustness, optimality, and explicit constraint-handling capabilities, and provides, at the same time, an explicit and intuitive characterization of the state-space regions of guaranteed closed-loop stability. This characterization captures, quantitatively, the limitations imposed by uncertainty and input constraints on our ability to steer the process dynamics in a desired direction. The proposed control method leads to the derivation of explicit analytical formulas for bounded robust optimal state feedback control laws that enforce stability and robust asymptotic referenceinput tracking in the presence of active input constraints. The performance of the control laws is illustrated through the use of a chemical reactor example and compared with existing process control strategies

Resource-Aware Scheduled Control of Distributed Process Systems over Wireless Sensor Networks

Abstract-This paper presents an integrated model-based networked control and sensor scheduling framework for spatially-distributed processes modeled by parabolic PDEs controlled over a resource-constrained wireless sensor network (WSN). The framework aims to enforce closed-loop stability with minimal information transfer over the WSN. Based on an approximate finite-dimensional system that captures the dominant dynamics of the PDE, a feedback controller is initially designed together with a state observer a copy of which is embedded within each sensor. Information transfer over the WSN is reduced by embedding within the controller and the sensors a finite-dimensional model. Communication is suspended periodically for extended time periods during which the model is used by the controller to generate the necessary control action and by the observers to generate state estimates. Communication is then re-established at discrete times according to a certain scheduling strategy in which only one sensor is allowed to transmit its state estimate at a time to update the states of the models, while the rest are kept dormant. A hybrid system formulation is used to explicitly characterize the interplays between the communication rate, the sensor transmission schedule, the model uncertainty and the spatial placement of the sensors. Finally, the proposed methodology is illustrated through an application to a diffusion-reaction process example

Fault-tolerant control of fluid dynamic systems via coordinated feedback and switching. Computers and Chemical Engineering, 2003, 27(12): 1913∼1924 8 Yang H, Jiang B. Fault tolerant control based on progressive accommodation. Control Engineering of China,

Abstract This work addresses the problem of designing a fault-tolerant control system for fluid dynamic systems modeled by highlydissipative partial differential equations (PDEs) with constrained control actuators. The proposed approach is predicated upon the idea of coordinating feedback controller synthesis and switching between multiple, spatially-distributed control actuator configurations. Using appropriate finite-dimensional approximations of the PDE system, a stabilizing feedback controller is designed for a given actuator configuration, and an explicit characterization of the constrained stability region is obtained. Switching laws are then derived, on the basis of these stability regions, to orchestrate the switching between the control actuator configurations, in a way that guarantees constraint satisfaction and preserves closed-loop stability of the infinite-dimensional system in the event of actuator failures. The results are demonstrated through an application of the proposed methodology to the suppression of wave formation in falling liquid films via the stabilization of the zero solution of the one-dimensional Kuramoto Á/ Sivashinsky equation (KSE), with periodic boundary conditions, subject to actuator constraints and failures.

A reachable set-based scheme for the detection of false data injection cyberattacks on dynamic processes

Recent cyberattacks targeting process control systems have demonstrated that reliance on information technology-based approaches alone to address cybersecurity needs is insufficient and that operational technology-based solutions are needed. An attack detection scheme that monitors process operation and determines the presence of an attack represents an operational technology-based approach. Attack detection schemes may be designed to monitor a process operated at or near its steady–state to account for the typical operation of chemical processes. However, transient operation may occur; for example, during process start-up and set–point changes. Detection schemes designed or tuned for steady-state operation may raise false alarms during transient process operation. In this work, we present a reachable set-based cyberattack detection scheme for monitoring processes during transient operation. Both additive and multiplicative false data injection attacks (FDIAs) that alter data communicated over the sensor–controller and controller–actuator communication links are considered. For the class of attacks considered, the detection scheme does not raise false alarms during transient operations. Conditions for classifying attacks based on the ability of the detection scheme to detect the attacks are presented. The application of the reachable set-based detection scheme is demonstrated using two illustrative processes under different FDIAs. For the FDIAs considered, their detectability with respect to the reachable set-based detection scheme is analyzed