A bounded positive nonlinear PI controller for double-pipe heat exchangers

"In this work, temperature regulation of double-pipe heat exchangers is considered. The positive (unidirectional) and bounded features of the flow rate input variable are taken into account in the analysis. As a result, a bounded positive PI-type control scheme, which achieves the regulation objective avoiding input saturation, is proposed. It turns out to be a simple algorithm that does not need to feed back the whole state vector, that does not depend on the exact value of the system parameters, and whose stabilization character is global in the closed-loop system state-space domain. Moreover, it may be applied to both flow configuration cases, i.e., countercurrent and parallel-flow heat exchangers. The analytical developments are corroborated through experimental and simulation results.

A generalized design methodology for the output feedback regulation of a special type of systems with bounded inputs

"In this work, a generalized design scheme for the output feedback regulation of a special type of systems with bounded inputs is proposed. It gives rise to a simple dynamic controller that guarantees the regulation objective avoiding input saturation, for any initial condition within a specific set that may comprehend the whole state space and that does not require any additional system data (apart from the output variable). Several processes, like double?pipe heat exchangers, bioreactors, and binary distillation columns, are shown to be part of the type of systems that may be regulated through the developed methodology. The efficiency of the proposed scheme is corroborated through experimental and simulation results.

Multi-agent model predictive control for transport phenomena processes

Throughout the last decades, control systems theory has thrived, promoting new areas of development, especially for chemical and biological process engineering. Production processes are becoming more and more complex and researchers, academics and industry professionals dedicate more time in order to keep up-to-date with the increasing complexity and nonlinearity. Developing control architectures and incorporating novel control techniques as a way to overcome optimization problems is the main focus for all people involved. Nonlinear Model Predictive Control (NMPC) has been one of the main responses from academia for the exponential growth of process complexity and fast growing scale. Prediction algorithms are the response to manage closed-loop stability and optimize results. Adaptation mechanisms are nowadays seen as a natural extension of prediction methodologies in order to tackle uncertainty in distributed parameter systems (DPS), governed by partial differential equations (PDE). Parameters observers and Lyapunov adaptation laws are also tools for the systems in study. Stability and stabilization conditions, being implicitly or explicitly incorporated in the NMPC formulation, by means of pointwise min-norm techniques, are also being used and combined as a way to improve control performance, robustness and reduce computational effort or maintain it low, without degrading control action. With the above assumptions, centralized (or single agent) or decentralized and distributed Model Predictive Control (MPC) architectures (also called multi-agent) have been applied to a series of nonlinear distributed parameters systems with transport phenomena, such as bioreactors, water delivery canals and heat exchangers to show the importance and success of these control techniques

Time-varying sliding mode controller for heat exchanger with dragonfly algorithm

This article proposes the design of a sliding mode controller with a time-varying sliding surface for the plate heat exchanger. A time-varying sliding mode controller (TVSMC) combines the benefit of the control system’s robustness and convergence rate. Using Lyapunov stability theory, the stability of the designed controller is proved. In addition, the controller parameters of the designed controller are specified optimally via the dragonfly algorithm (DA). The input constraint’s effect is considered in the controller design process by applying the concept of the auxiliary system. The bounded disturbances are applied to investigate the robustness of the proposed techniques. Moreover, the quasi-sliding mode controller (QSMC) is developed as a benchmark to evaluate the convergence behavior of the proposed TVSMC technique. The simulation results demonstrate the proposed TVSMC with the optimal parameters provided by the DA algorithm (TVSMC+DA) can regulate the temperature to the desired level under bounded disturbances. When compared to the QSMC method, the TVSMC+DA performs significantly faster convergence speed and greater reduction in chattering occurrence. The results clearly indicate that the proposed controller can enhance convergence properties while being robust to disturbances

Multivariable robust control of a simulated hybrid solid oxide fuel cell gas turbine plant

This work presents a systematic approach to the multivariable robust control of a hybrid fuel cell gas turbine plant. The hybrid configuration under investigation built by the National Energy Technology Laboratory comprises a physical simulation of a 300kW fuel cell coupled to a 120kW auxiliary power unit single spool gas turbine. The public facility provides for the testing and simulation of different fuel cell models that in turn help identify the key difficulties encountered in the transient operation of such systems. An empirical model of the built facility comprising a simulated fuel cell cathode volume and balance of plant components is derived via frequency response data. Through the modulation of various airflow bypass valves within the hybrid configuration, Bode plots are used to derive key input/output interactions in transfer function format. A multivariate system is then built from individual transfer functions, creating a matrix that serves as the nominal plant in an Hinfinity robust control algorithm. The controller\u27s main objective is to track and maintain hybrid operational constraints in the fuel cell\u27s cathode airflow, and the turbo machinery states of temperature and speed, under transient disturbances. This algorithm is then tested on a Simulink/MatLab platform for various perturbations of load and fuel cell heat effluence.;As a complementary tool to the aforementioned empirical plant, a nonlinear analytical model faithful to the existing process and instrumentation arrangement is evaluated and designed in the Simulink environment. This parallel task intends to serve as a building block to scalable hybrid configurations that might require a more detailed nonlinear representation for a wide variety of controller schemes and hardware implementations

The 25 kWe solar thermal Stirling hydraulic engine system: Conceptual design

The conceptual design and analysis of a solar thermal free-piston Stirling hydraulic engine system designed to deliver 25 kWe when coupled to a 11 meter test bed concentrator is documented. A manufacturing cost assessment for 10,000 units per year was made. The design meets all program objectives including a 60,000 hr design life, dynamic balancing, fully automated control, more than 33.3 percent overall system efficiency, properly conditioned power, maximum utilization of annualized insolation, and projected production costs. The system incorporates a simple, rugged, reliable pool boiler reflux heat pipe to transfer heat from the solar receiver to the Stirling engine. The free-piston engine produces high pressure hydraulic flow which powers a commercial hydraulic motor that, in turn, drives a commercial rotary induction generator. The Stirling hydraulic engine uses hermetic bellows seals to separate helium working gas from hydraulic fluid which provides hydrodynamic lubrication to all moving parts. Maximum utilization of highly refined, field proven commercial components for electric power generation minimizes development cost and risk

Thermodynamic Model for Performance Analysis of a Stirling Engine Prototype

In this study, the results of simulations generated from different thermodynamic models of Stirling engines are compared, including characterizations of both instantaneous and indicated operative parameters. The aim was to develop a tool to guide the decision-making process regarding the optimization of both the performance and reliability of Stirling engines, such as the 2.9 kW GENOA 03 unit—the focus of this work. The behavior of the engine is characterized using two different approaches: an ideal isothermal model, the simplest of those available, and analysis using the ideal adiabatic model, which is more complex than the first. Some of the results obtained with the referred ideal models deviated considerably from the expected values, particularly in terms of thermal efficiency, so a set of modifications to the ideal adiabatic model are proposed. These modifications, mainly related to both heat transfer and fluid friction phenomena, are intended to overcome the limitations due to the idealization of the engine working cycle, and are expected to generate results closer to the actual behavior of the Stirling engine, despite the increase in the complexity derived from the modelling and simulation processes.Ministerio de Economía y Competitividad ENE2013-43465-

The Fifth Annual Thermal and Fluids Analysis Workshop

The Fifth Annual Thermal and Fluids Analysis Workshop was held at the Ohio Aerospace Institute, Brook Park, Ohio, cosponsored by NASA Lewis Research Center and the Ohio Aerospace Institute, 16-20 Aug. 1993. The workshop consisted of classes, vendor demonstrations, and paper sessions. The classes and vendor demonstrations provided participants with the information on widely used tools for thermal and fluid analysis. The paper sessions provided a forum for the exchange of information and ideas among thermal and fluids analysts. Paper topics included advances and uses of established thermal and fluids computer codes (such as SINDA and TRASYS) as well as unique modeling techniques and applications