Passivity-based nonlinear control of CSTR via asymptotic observers.

International audienceThis work makes use of a passivity-based approach (PBA) and tools from Lyapunov theory to design a nonlinear controller for the asymptotic stabilization of a class of non isothermal Continuous Stirred Tank Reactors (CSTR) around any desired stationary point. The convergence and stability proofs are derived in the port Hamiltonian framework. Asymptotic observers that do not require knowledge of reaction kinetics are also proposed for a system with incomplete state measurement. Numerical simulations are given to illustrate the application of the theoretical results to a CSTR with multiple steady states

An EnergyPlus whole building energy model calibration method for office buildings using occupant behavior data mining and empirical data

This paper proposes a method comprising procedures to calibrate an EnergyPlus whole building energy model. An occupant behavior data mining procedure is developed and tested in an office building. Workday occupancy schedules are generated by mining the office appliance energy consumption data. Hourly and monthly power, energy, and temperature data are collected and used for lighting, equipment and HVAC systems energy performance calibration. The result shows a 1.27% mean bias error for the total annual energy use intensity. The proposed calibration method provides a scientific and systematic framework to conduct high accuracy EnergyPlus model calibration

Inventory control of particulate processes

Abstract In this work we address the problem of designing model-based controllers for particulate processes described by population balance (PB) models. We focus on PB models that are solved by numerical discretization, for which many standard control methodologies are not suitable due to the high order of these models. We interpret discretized PB models as chemical reaction networks and suggest to combine inventory control with techniques of stability of chemical reaction networks to design the controller. Inventory control is based on the idea of manipulating process flows so that certain extensive variables defining the system, called inventories, follow their setpoints. The whole system is stabilized by controlling the dominant inventories. The discretized PB is exploited in all aspects of controller design, from determining the controlled inventories to the final implementation of the control law. The methodology is illustrated with an industrial leaching reactor, the Silgrain ® process. We show that the discretized PB model takes the form of a Feinberg-Horn-Jackson zero-deficiency network, allowing us to prove stabilization of the whole system. The performance of standard inventory control and robust inventory control are investigated by simulation, with satisfactory results even in the presence of modeling errors