We present a mathematical programming-based method for model predictive control of cyber-physical systems subject to signal temporal logic (STL) specifications. We describe the use of STL to specify a wide range of properties of these systems, including safety, response and bounded liveness. For synthesis, we encode STL specifications as mixed integer-linear constraints on the system variables in the optimization problem at each step of a receding horizon control framework. We prove correctness of our algorithms, and present experimental results for controller synthesis for building energy and climate control.

This article addresses the challenge of realizing the building automation and control system using a distributed network of embedded computers. A specification methodology and design space exploration framework are proposed to raise the level of abstraction at which building control systems are designed, to reduce design effort, and to lower implementation cost.

A hierarchical control architecture for balancing comfort and energy consumption in buildings is presented. The control design is based on a simplified, yet accurate model of the temperature within each room of the building. The model is validated against real measurements. The control architecture comprises a first level that regulates low level quantities such as air flow, and a second level that balances comfort (i.e. distance between the desired and actual temperature) and energy consumption (i.e. total energy consumed for the required level of comfort). We show the effectiveness of our approach by simulation using validated models.

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Abstract-Commercial buildings have inherent flexibility in how their HVAC systems consume electricity. We investigate how to take advantage of this flexibility. We first propose a means to define and quantify the flexibility of a commercial building. We then propose a contractual framework that could be used by the building operator and the utility to declare flexibility on the one side and reward structure on the other side. We then design a control mechanism for the building to decide its flexibility for the next contractual period to maximize the reward, given the contractual framework. Finally, we perform at-scale experiments to demonstrate the feasibility of the proposed algorithm.

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Abstract-We first demonstrate that the demand-side flexibility of the Heating Ventilation and Air Conditioning (HVAC) system of a typical commercial building can be exploited for providing frequency regulation service to the power grid using at-scale experiments. We then show how this flexibility in power consumption of building HVAC system can be leveraged for providing regulation service. To this end, we consider a simplified model of the power grid with uncertain demand and generation. We present a Model Predictive Control (MPC) scheme to direct the ancillary service power flow from buildings to improve upon the classical Automatic Generation Control (AGC) practice. We show how constraints such as slow and fast ramping rates for various ancillary service providers, and short-term load forecast information can be integrated into the proposed MPC framework. Finally, we provide extensive simulation results to illustrate the effectiveness of the proposed methodology for enhancing grid frequency regulation.