Development of a Scalable Distributed Model Predictive Control System for Hydronic Networks with Bilinear and Hybrid Dynamics

Abstract

Hydronic heating and cooling systems are growing in complexity as the buildings and other infrastructure systems they serve demand greater efficiency and become larger. Increasing the scale and interconnectivity of these systems yields higher probabilities of component failure along with computational tractability issues. This paper presents a distributed hydronic control architecture featuring scalable computations and resiliency to component failure in both the cyberand physical-domains. In this agent-based control system, an agent is defined as a set of co-located components in the cyber-and physical-domains which together have sensations, actions, and/or goals. The proposed architecture consists of three types of agents: pumps, valves, and loads. Respectively, these agents solve a convex constraint satisfaction problem, a steady-state hybrid control problem, and a scalar bilinear model predictive control problem. The network on which these agents transfer thermal energy and on which they communicate are co-designed to share the same graph representation. The resulting coordinated behavior achieves the global control objective: maintain the thermal loads at safe temperatures while minimizing pump power. Analytical analysis, simulations, and laboratory experiments are employed to investigate the controller. The results demonstrate steady-state robustness to component failures in the cyber-2-physical domains, superiority to benchmarks, and suitable although not guaranteed to be optimal real-time performance.

Run-Time Efficiency of Bilinear Model Predictive Control Using Variational Methods, With Applications to Hydronic Cooling

“…These properties and the promising experimental outcomes present designers with new insight into effective design of model predictive controllers, especially those run as part of wirelessly networked control systems. For example, the BLEC controller presented herein has been extended from the simple and load scenario to a redundant network of pumps, valves, and [29].…”

“…1) Bilinear State Equation Model: Solving (28) for u * with Hamiltonian (27) using the bilinear state (7) and the monotonic co-state equation asymptotically approaching the origin (30) yield an optimal control that switches between two modes, i.e., a bang-bang type control, and satisfies (29).…”

Development Method and Support Tools of Distributed System Based on Web Service

“…The proposed architecture consists of three types of agents: pumps, valves, and loads. These agents solve the convex constraint satisfaction problem, the steady-state mixed control problem, and the scalar bilinear model predictive control problem [7], respectively. Starikov A proposed the modern concept of Virtual Furniture Design Bureau (VFDB).…”