Model Predictive Control Strategy for Industrial Process

Model Predictive control (MPC) is shown to be particularly effective for the self-tuning control of industrial processes. It makes use of a truncated step response of the process and provides a simple explicit solution in the absence of constraints. Here we use Dynamic Matrix Control (DMC). DMC uses a set of basis functions to form the future control sequence. The industrial success of DMC has mainly come from its application to high dimension multivariable system without constraints. Here main objective of DMC controller is to drive the output as close to the set point as possible in a least square sense with the possibility of the inclusion of a penalty term on the input moves. Therefore, the manipulated variables are selected to minimize a quadratic objective that can consider the minimization of future error. Implementation of the internal model control is also shown here. The control strategy is to determine the best model for the current operating condition and activate the corresponding controller. Internal model control (IMC) continues to be a powerful strategy in complex, industrial processes control application. This structure provides a practical tool to influence dynamic performance and robustness to modeling error transparently in the design. It is particularly appropriate for the design and implementation of controllers for linear open loop stable system. A simulated example of the control of nonlinear chemical process is shown. The nonlinear chemical process study in this work is the exothermic stirred tank reactors system with the first order reaction. The reaction is assumed to be perfectly mixed and no heat loss occurs within the system. Using internal model control and dynamic matrix control has simulated control of the total process in CSTR. Simulation example provided to show the effectiveness of the proposed control strategy

High-Performance Integrated Window and Façade Solutions for California

The researchers developed a new generation of high-performance façade systems and supporting design and management tools to support industry in meeting California’s greenhouse gas reduction targets, reduce energy consumption, and enable an adaptable response to minimize real-time demands on the electricity grid. The project resulted in five outcomes: (1) The research team developed an R-5, 1-inch thick, triplepane, insulating glass unit with a novel low-conductance aluminum frame. This technology can help significantly reduce residential cooling and heating loads, particularly during the evening. (2) The team developed a prototype of a windowintegrated local ventilation and energy recovery device that provides clean, dry fresh air through the façade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15–40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35–54 percent without glare. (4) A control system incorporating physics-based equations and a mathematical solver was prototyped and field tested to demonstrate feasibility. Simulations estimated that total electricity costs could be reduced by 9-28 percent on sunny summer days through adaptive control of operable shading and daylighting components and the thermostat compared to state-of-the-art automatic façade controls in commercial building perimeter zones. (5) Supporting models and tools needed by industry for technology R&D and market transformation activities were validated. Attaining California’s clean energy goals require making a fundamental shift from today’s ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building façade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California

Improving the Accuracy and Scope of Control-Oriented Vapor Compression Cycle System Models

The benefits of applying advanced control techniques to vapor compression cycle systems are well know. The main advantages are improved performance and efficiency, the achievement of which brings both economic and environmental gains. One of the most significant hurdles to the practical application of advanced control techniques is the development of a dynamic system level model that is both accurate and mathematically tractable. Previous efforts in control-oriented modeling have produced a class of heat exchanger models known as moving-boundary models. When combined with mass flow device models, these moving-boundary models provide an excellent framework for both dynamic analysis and control design. This thesis contains the results of research carried out to increase both the accuracy and scope of these system level models. The improvements to the existing vapor compression cycle models are carried out through the application of various modeling techniques, some static and some dynamic, some data-based and some physics-based. Semiempirical static modeling techniques are used to increase the accuracy of both heat exchangers and mass flow devices over a wide range of operating conditions. Dynamic modeling techniques are used both to derive new component models that are essential to the simulation of very common vapor compression cycle systems and to improve the accuracy of the existing compressor model. A new heat exchanger model that accounts for the effects of moisture in the air is presented. All of these model improvements and additions are unified to create a simple but accurate system level model with a wide range of application. Extensive model validation results are presented, providing both qualitative and quantitative evaluation of the new models and model improvements.Air Conditioning and Refrigeration Project 17

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions

Computer program for analysis of split-Stirling-cycle cryogenic coolers

A computer program for predicting the detailed thermodynamic performance of split-Stirling-cycle refrigerators has been developed. The mathematical model includes the refrigerator cold head, free-displacer/regenerator, gas transfer line, and provision for modeling a mechanical or thermal compressor. To allow for dynamic processes (such as aerodynamic friction and heat transfer) temperature, pressure, and mass flow rate are varied by sub-dividing the refrigerator into an appropriate number of fluid and structural control volumes. Of special importance to modeling of cryogenic coolers is the inclusion of real gas properties, and allowance for variation of thermo-physical properties such as thermal conductivities, specific heats and viscosities, with temperature and/or pressure. The resulting model, therefore, comprehensively simulates the split-cycle cooler both spatially and temporally by reflecting the effects of dynamic processes and real material properties

A simplified dynamic systems approach for the energy rating of dwellings

The drive to reduce carbon emissions and energy utilisation, directly associated with dwellings and to achieve a zero carbon home, suggests that the assessment of energy ratings will have an increasingly prioritised role in the built environment. Created by the Building Research Establishment (BRE), the Standard Assessment Procedure (SAP) is the UK Government’s recommended method of assessing the energy ratings of dwellings. This paper describes a new, simplified dynamic method (hence known as IDEAS – Inverse Dynamics based Energy Analysis and Simulation) of assessing the controllability of a building and its servicing systems. The IDEAS method produces SAP Comparable results. Results suggest this design approach could enhance the SAP Methodology by the addition of advanced systems controllability and dynamic values

Model based fault diagnosis for hybrid systems : application on chemical processes

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Symbolic energy estimation model with optimum start algorithm implementation

The drive to reduce carbon emissions and energy utilisation, directly associated with dwellings and to achieve a zero carbon home, suggests that the assessment of energy ratings will have an increasingly prioritised role in the built environment. Created by the Building Research Establishment (BRE), the Standard Assessment Procedure (SAP) is the UK Government’s recommended method of assessing the energy ratings of dwellings. This paper describes a new, simplified dynamic method (hence known as IDEAS – Inverse Dynamics based Energy Analysis and Simulation) of assessing the controllability of a building and its servicing systems. The IDEAS method produces results that are comparable to SAP. An Optimum Start algorithm is explored in this paper to allow heating systems of different responsiveness and size to be integrated into the IDEAS framework. Results suggest that this design approach could enhance the SAP Methodology by the addition of advanced systems controllability and dynamic values

A holistic analysis method to assess the controllability of commercial buildings and their systems

This paper describes a novel design process for advanced MIMO (multiple inputs and multiple outputs) control system design and simulation for buildings. The paper describes the knowledge transfer from high technology disciplines such as aerospace flight control systems and the space industry to establish a three-step modelling and design process. In step 1, simplified, but holistic nonlinear and linearised dynamic models of the building and its systems is derived. This model is used to analyse the controllability of the building. In step 2, further synthesis of this model leads to the correct topology of the control system design. This is proved through the use of simulation using the simple building model. In step 3, the controller design is proved using a fully detailed building simulation such as ESP-r that acts as a type of virtual prototype of the building. The conclusions show that this design approach can help in the design of superior and more complex control systems especially for buildings designed with a Climate Adaptive Building (CAB) philosophy where many control inputs and outputs are used to control the building's temperature, concentration of CO2, humidity and lighting levels