Timothy I. Salsbury

A SURVEY OF CONTROL TECHNOLOGIES IN THE BUILDING AUTOMATION INDUSTRY

Abstract Advances in technology infrastructure such as communications, processing power, and data storage over the past several years have created new opportunities for the application of control and automation to many types of systems including those in buildings. This paper describes the state of the art for control in the building automation industry, and reviews new and emerging technologies. Issues specific to the building industry that impact the adoption of new control technology are also discussed.

A new approach for ARMA pole estimation using higher-order crossings

The paper describes a new method for estimating the poles of an ARMA model using higher-order crossings. The method involves transforming counts of crossing events into estimates of ARMA poles via the autocorrelation domain. An important advantage of the method is that the crossing counts are the only features that need to be stored from the original data. The poles of an ARM A model of a control loop correspond to the roots of the characteristic equation and are thus useful for evaluating control performance.

A new pulse modulation adaptive controller (PMAC) applied to HVAC systems

Abstract The paper proposes a new switching control law (pulse modulation adaptive controller, PMAC) that implements pulse-width–pulse-frequency modulation. Pulse durations are determined to maintain the amplitude of variation in the controlled variable at or below a user-defined level. In addition to providing quantifiable control performance, PMAC can reduce component wear by issuing fewer switches than conventional control schemes. The control law is developed around a first-order system characterization but incorporates an adaptive loop, which allows application to a wide range of non-first-order and also time-variant systems. Test results are presented from applying PMAC to both simulated and real HVAC systems.

Experimental study of economic model predictive control in building energy systems

This paper presents results from testing an economic model predictive control (EMPC) strategy in an office building located in Milwaukee, Wisconsin, USA. The control strategy includes an economic objective function that is designed to account for the combination of energy and demand costs under a time-of-use (TOU) rate structure. A min-max optimization problem is formulated and solved as a linear program. The tests were carried out with the controller sited in a remote location and with the loop being closed over the Internet. The results show that the EMPC strategy was successful at reducing energy costs compared to the baseline case for the considered building.

Model predictive control of building energy systems with balanced model reduction

This paper presents a model reduction method based on balanced realization for thermal and power models of buildings. System identification is firstly performed to obtain high-order state-space models. The purpose of model reduction is to simplify the model structure while preserving the major input-output relations, so as to lower the computational cost in the subsequent model predictive control (MPC) scheme. An economic objective function is designed to minimize the energy and demand charges of building energy systems. The effectiveness of the presented method is shown by simulation, and it is shown that the control performance is not significantly affected by using reduced models.

Optimization and sequencing of chilled-water plant based on extremum seeking control

Chilled-water plants with multiple chillers are the backbone of ventilation and air conditioning (VAC) systems for commercial buildings. Optimal operation and sequencing of such plant has great impact on building energy efficiency. Large variations in equipment characteristics and operating conditions make it difficult and expensive to obtain plant models required by model-based control/optimization approaches. For a variable primary flow (VPF) chilled-water plant with parallel chillers, a model-free optimization and sequencing strategy is proposed to maximize energy efficiency in real time, based on a penalty-function based multivariate extremum seeking control (ESC). The ESC takes the total power consumption (chiller compressors + cooling tower fan + condenser water pumps + input-saturation penalty) as feedback, while tower fan airflow, condenser water flows and evaporator leaving chilled-water temperature setpoint as manipulative inputs. A band-pass filter array replaces the high-pass filter in the standard ESC to reduce the cross-channel interference. The chiller sequencing is enabled with input saturation related signals. Simulation study is performed under several testing conditions using a Modelica based dynamic simulation model of a chilled-water plant with two parallel chillers, one cooling tower, one air-handling unit and one zone. Simulation results validate the effectiveness of the proposed strategy with significant energy saving demonstrated.

Extremum Seeking Based Control Strategy for a Chilled-Water Plant With Parallel Chillers

Chilled-water plants with multiple chillers are the backbone of ventilation and air conditioning (VAC) systems for commercial buildings. A penalty function based multivariate extremum seeking control (ESC) strategy is proposed in this paper for maximizing the energy efficiency in real time for a variable primary flow (VPF) chilled-water plant with parallel chillers. The proposed ESC algorithm takes the total power consumption (chiller compressors + cooling tower fan + condenser water pumps + penalty terms if inputs saturation occurs) as feedback, and tower fan air flow, condenser water flows and evaporator leaving chilled-water temperature setpoint as plant inputs (ESC outputs). A band-pass filter array is used in place of the conventional high-pass filter at the plant output so as to reduce the cross-channel interference. Chiller sequencing is also enabled with input saturation related signals. A Modelica based dynamic simulation model is developed for a chilled-water plant with two parallel chillers, one cooling tower, one air-handling unit and one zone. Simulation results under several testing conditions validate the effectiveness of the proposed model-free control strategy, as well as the significant energy saving.Copyright

Control performance assessment for building automation systems

Abstract This paper focuses on the application area of building automation systems and highlights the need for methods to assess the performance of SISO feedback loops. Several practical issues make it difficult to apply some of the more widely known performance assessment methods to systems in buildings. These issues are discussed and an alternative method is described that is designed to be more practicable for the buildings application area. The method involves extracting features from the setpoint error signal and it yields a normalized index that can be used to detect and diagnose tuning problems as well as valve stiction. The paper describes the method and demonstrates its utility on several building control loops.

Two new normalized EWMA-based indices for control loop performance assessment

Modern buildings can have hundreds if not thousands of control loops that regulate variables such as pressure, temperature, flow rate, etc. The amount of data available to operators can be overwhelming and, because of this, many faults and poorly controlled loops often go undetected until complaints arise from building occupants or a more serious failure occurs. Methods are thus needed that can convert big data sets from buildings into more managable metrics that can be used to identify problems. This paper proposes two new indices that quantify control performance in a normalized way so that different control loops can be compared on the same scale. These normalized indices can be used to generate a quick ranking of control loop performance so that poorly performing loops can be identified. The paper describes the new indices and presents results from both simulation and field tests.

The Smart Building

Buildings account for a large fraction of global energy use and have a correspondingly significant impact on the environment. Buildings are also ubiquitous in virtually every aspect of our lives from where we work, live, learn, govern, heal, and worship, to where we play. The application of control and automation to buildings can lead to significant energy savings, improved health and safety of occupants, and enhance life quality. The aim of this chapter is to describe what makes buildings smart, provide examples of common control strategies, and highlight emerging trends and open challenges. Today, the most prevalent use of automation in buildings is in heating, ventilating, and air-conditioning (HVAC) systems. This chapter reviews common control and automation methods for HVAC, but also describes how automation is being extended to other building processes. The number of controllable and interconnected systems is increasing in modern buildings and this is creating new opportunities for the application of automation to coordinate and manage operation. However, the chapter draws attention to the fact that the buildings industry is very large, fragmented, and cost-oriented, with significant economic and technical barriers that can, in some cases, impede the adoption and wide-scale deployment of new automation technologies.