Yulei Sun

Quasi-decentralized model-based networked control of process systems

Abstract This paper develops a quasi-decentralized control framework for plants with distributed, interconnected units that exchange information over a shared communication network. In this architecture, each unit in the plant has a local control system that communicates with the plant supervisor – and with other local control systems – through a shared communication medium. The objective is to design an integrated control and communication strategy that ensures the desired closed-loop stability and performance for the plant while minimizing network utilization and communication costs. The idea is to reduce the exchange of information between the local control systems as much as possible without sacrificing stability of the individual units and the overall plant. To this end, dynamic models of the interconnected units are embedded in the local control system of each unit to provide it with an estimate of the evolution of its neighbors when measurements are not transmitted through the network. The use of a model to recreate the interactions of a given unit with one of its neighbors allows the sensor suite of the neighboring unit to send its data in a discrete fashion since the model can provide an approximation of the unit’s dynamics. The state of each model is then updated using the actual state of the corresponding unit provided by its sensors at discrete time instances to compensate for model uncertainty. By formulating the networked closed-loop plant as a hybrid system, an explicit characterization of the maximum allowable update period (i.e., minimum cross communication frequency) between each control system and the sensors of its neighboring units is obtained in terms of the degree of mismatch between the dynamics of the units and the models used to describe them. The developed control strategy is illustrated using a network of interconnected chemical reactors with recycle.

Networked control of spatially distributed processes with sensor-controller communication constraints

This work presents a methodology for the design of a model-based networked control system for spatially distributed processes described by linear parabolic partial differential equations (PDEs) with measurement sensors that transmit their data to the controller/actuators over a bandwidth-limited communication network. The central design objective is to minimize the transfer of information from the sensors to the controller without sacrificing closed-loop stability. To accomplish this, a finite-dimensional model that captures the dominant dynamic modes of the PDE is embedded in the controller to provide it with an estimate of those modes when measurements are not transmitted through the network, and the model state is then updated using the actual measurements provided by the sensors at discrete time instances. Bringing together tools from switched systems, infinite-dimensional systems and singular perturbations, a precise characterization of the minimum stabilizing sensor-controller communication frequency is obtained under both state and output feedback control. The stability criteria are used to determine the optimal sensor and actuator configurations that maximize the networked closed-loop systems robustness to communication suspensions. The proposed methodology is illustrated using a simulation example.

Resource-aware scheduled control of distributed process systems over wireless sensor networks

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.

Monitoring and fault-tolerant control of distributed power generation: Application to solid oxide fuel cells

This paper presents a hierarchical structure for fault detection and fault-tolerant control of distributed energy resources (DERs). The structure consists of distributed monitoring and control systems that perform local fault diagnosis and control system reconfiguration, together with a supervisor that communicates with the local controllers and provides high-level oversight and contingency measures in the event that local fault recovery is not possible. To realize this structure, an observer-based output feedback controller is initially designed for each DER to regulate its output in the absence of faults. The design accounts explicitly for practical implementation issues such as measurement sampling and plant-model mismatch. Fault detection is performed by comparing the output of the observer with that of the DER, and using the discrepancy as a residual. An explicit characterization of the minimum allowable sampling rate that guarantees both closed-loop stability and residual convergence in the absence of faults is obtained and used as the basis for deriving (1) a time-varying threshold on the residual which can be used to detect faults for a given sampling period, and (2) controller reconfiguration laws that determine the feasible fall-back control configurations that preserve stability. Finally, the design and implementation of the fault detection and fault-tolerant control architecture are demonstrated using a simulated model of a solid oxide fuel cell plant.

Quasi-decentralized networked process control using an adaptive communication policy

This work presents a model-based quasi-decentralized networked control structure with a state-dependent communication policy for plants with interconnected units that exchange measurements over a shared, resource-constrained communication network. The objective is to find a strategy for establishing and terminating communication between the local control systems in a way that minimizes network resource utilization without jeopardizing closed-loop stability. To this end, a Lyapunov-based controller that enforces closed-loop stability in the absence of communication suspensions is initially designed. A set of dynamic models are included within each local control system to provide estimates of the states of the neighboring units when measurements are not transmitted through the network. To determine when communication must be re-established, the evolution of each Lyapunov function is monitored locally within each unit such that if it begins to breach a certain stability threshold at any time, the sensor suites of the neighboring units are prompted to send their data over the network to update their corresponding models. Communication is then suspended for as long as the Lyapunov function continues to decay. The underlying idea is to use the Lyapunov stability constraint for each unit as the basis for switching on or off the communication between a given unit and its neighbors. This formulation, which leads to a state-dependent time-varying communication rate, allows the plant to respond adaptively to changes in operating conditions. Finally, the results are illustrated through an application to a chemical plant example.

Quasi-decentralized control of process systems using wireless sensor networks with scheduled sensor transmissions

This paper develops a model-based networked control and scheduling framework for plants with interconnected units and distributed control systems that exchange information using a resource-constrained wireless sensor network (WSN). The framework aims to enforce closed-loop stability while simultaneously minimizing the rate at which each node in the WSN must collect and transmit measurements so as to conserve the limited resources of the wireless devices and extend the lifetime of the network as much as possible. Initially, the exchange of information between the local control systems is reduced by embedding, within each control system, dynamic models that provide forecasts of the evolution of the plant units when measurements are not transmitted through the WSN, and updating the state of each model when communication is re-established at discrete time instances. To further reduce WSN utilization, only a subset of the deployed sensor suites are allowed to transmit their data at any given time to provide updates to their target models. By formulating the networked closed-loop plant as a combined discrete-continuous system, an explicit characterization of the maximum allowable update period is obtained in terms of the sensor transmission schedule, the transmission times of the different sensor suites, the uncertainty in the models as well as the controller design parameters. It is shown that by judicious selection of the transmission schedule and the models, it is possible to enhance the savings in WSN resource utilization over what is possible with concurrent transmission condigurations. Finally, the results are illustrated using a network of chemical reactors with recycle.

Quasi-decentralized state estimation and control of process systems over communication networks

This paper develops a quasi-decentralized state estimation and control architecture for plants with limited state measurements and distributed, interconnected units that exchange information over a shared communication network. The objective is to stabilize the plant while minimizing network resource utilization and communication costs. The networked control architecture is composed of a family of local control systems that transmit their data in a discrete (on/off) fashion over the network. Each control system includes a state observer that generates estimates of the local state variables from the measured outputs. The estimates are used to implement the local feedback control law and are also shared over the network with the control systems of the interconnected units to account for the interactions between the units. To reduce the exchange of information over the network as much as possible without sacrificing stability, dynamic models of the interconnected units are embedded in the local control system of each unit to provide it with an estimate of the evolution of its neighbors when data are not transmitted through the network. The state of each model is then updated using the state estimate generated by the observer of the corresponding unit and transmitted over the network when communication is re-established. By formulating the networked closed-loop plant as a switched system, an explicit characterization of the maximum allowable update period (i.e., minimum cross communication frequency) between the distributed control systems is obtained in terms of plant-model mismatch, controller and observer design parameters. It is shown that the lack of full state measurements imposes limitations on the maximum allowable update period even if the models used to recreate the plant units? dynamics are accurate. The results are illustrated using a chemical process example and compared with other networked control strategies. The comparison shows that the minimum communication frequency required using quasi-decentralized control is less than what is required by a centralized control architecture indicating that the former is more robust with respect to communication suspension.

Dynamic quasi-decentralized control of networked process systems with limited measurements

This work presents a quasi-decentralized net worked control structure with a dynamic communication logic for plants with limited state measurements and interconnected units that exchange information over a shared, resource constrained communication network. Initially, an observer based output feedback controller is synthesized for each unit, and Lyapunov techniques are used to explicitly characterize the closed-loop stability properties of each unit under continuous communication. This characterization is then used as the basis for developing a dynamic communication strategy that keeps the information transfer between the local control systems to a minimum without jeopardizing closed-loop stability. The key idea is to monitor the evolution of the observer-generated state estimates locally within each unit and suspend communication for as long as the expected stability threshold is met. During periods of communication suspension, each control system relies on a set of models that provide estimates of the states of the neighboring units. At times when the stability threshold is breached, communication is re-established and the neighboring units are prompted to send their data over the network to update the models. The stability threshold is determined using Lyapunov techniques and can be tightened or relaxed by proper controller and observer tuning. Finally, the stability and performance properties of the dynamic networked control structure are illustrated using a chemical plant example.

Networked control of Distributed Energy Resources: Application to solid oxide fuel cells

This paper presents a model-based networked control approach for managing Distributed Energy Resources (DERs) over communication networks. As a model system, we consider a solid oxide fuel cell (SOFC) plant that communicates with the central controller over a bandwidth-constrained communication network that is shared by several other DERs. The objective is to regulate the power output of the fuel cell while keeping the communication requirements with the controller to a minimum in order to reduce network utilization and minimize the susceptibility of the SOFC plant to possible communication disruptions in the network. Initially, an observer-based output feedback controller is designed to regulate the power output of the SOFC plant at a desired set-point by manipulating the inlet fuel flow rate. Network utilization is then reduced by minimizing the rate of transfer of information between the fuel cell and the supervisor without sacrificing stability or performance. To this end, a dynamic model of the fuel cell is embedded in the supervisor to approximate the dynamics of the fuel cell when measurements are not transmitted by the sensors, and the state of the model is updated using the observer-generated state estimate that is provided by the SOFC plant sensors at discrete time instances. An explicit characterization of the maximum allowable transfer time between the sensor suite of the fuel cell and the controller (i.e., the minimum allowable communication rate) is obtained in terms of model uncertainty and the choice of the control law. The characterization accounts for both stability and performance considerations. Finally, numerical simulations that demonstrate the implementation of the control architecture and its disturbance handling capabilities are presented.

Robust quasi-decentralized networked control of process systems

This paper presents a quasi-decentralized networked control methodology for the robust stabilization of multi-unit plants whose constituent subsystems communicate over a shared resource-constrained communication network and are subject to time-varying external disturbances. The objective is to stabilize the plant while keeping the communication requirements to a minimum in order to reduce the unnecessary utilization of network resources. Initially, a local robust feedback controller is synthesized for each unit to account for the effect of the disturbances. Then the exchange of information between the local control systems is reduced by embedding, within each control system, a set of dynamic models that provide forecasts of the evolution of the plant units when measurements are not transmitted through the shared network, and updating the state of each model when communication is reestablished at discrete time instances. By analyzing the resulting combined discrete-continuous closed-loop system, a necessary and sufficient condition for robust stability of the networked closed-loop plant is obtained. The stability condition can be used to explicitly characterize the interplays between the update period, the degree of plant-model mismatch, the selection of the controller design parameters, the size of the disturbances and the size of the achievable ultimate bound on the close-dloop state. Finally, the implementation of the robust networked control structure is demonstrated through an application to a chemical plant example.