Abstract-Energy and communication bandwidth are scarce resources in wireless sensor and actuator networks. Recent research efforts considered the control of physical processes over such resource limited networks. Most of the existing literature addressing this topic is dedicated to periodically sampled control loops and scheduled communication, because it simplifies the analysis and the implementation. We propose instead an aperiodic network transmission scheme that reduces the number of transmission instances for the sensor and control nodes, thereby reducing energy consumption and increasing network lifetime, without sacrificing on the control performance. As an added benefit, we show the possibility of dynamically allocating the network bandwidth based on the physical system state and the available resources. In order to allow timely, reliable, and energy efficient communication, we propose a new co-design framework for the wireless medium access control, compatible with the IEEE 802.15.4 standard. Furthermore, we validate our approach in a real wireless networked control implementation.

No abstract

No abstract

No abstract

Constraint-based control over wireless sensor networks (WSNs) require control strategies that achieve a desired closed-loop system performance while using minimal network resources. In addition to constraints associated with distributed control, WSNs have limitations on bandwidth, energy consumption, and transmission range. This paper introduces and experimentally evaluates a new receding-horizon approach for performing constraint-based control using a WSN. By leveraging the system controllability, the receding-horizon controller is formulated as a mixed-integer programming problem which, at each time step, simultaneously generates a control sequence and sensor selection schedule such that the desired performance is achieved while minimizing the energy required to perform data acquisition and control. For systems containing many sensors, a multi-step state estimator is employed to implement the receding-horizon controller using a conservative abstractionrelaxation approach that simplifies the original mixed-integer programming problem into a convex quadratic programming problem. A wireless process control test bed consisting of 8 coupled water tanks and 16 wireless sensors are used to experimentally evaluate the receding-horizon controller.