Event-triggered control has been recently proposed as an alternative to the more traditional periodic execution of control tasks. In a typical event-triggered implementation, the control signals are kept constant until the violation of a condition on the state of the plant triggers the recomputation of the control signals. The possibility of reducing the number of recomputations, and thus of transmissions, while guaranteeing desired levels of control performance, makes event-triggered control very appealing in the context of sensor/actuator networks. In particular, by reducing the network traffic we also reduce the energy expenditures of battery powered wireless sensor nodes. In this paper we present a decentralized event-triggered implementation, over sensor/actuator networks, of centralized nonlinear controllers.

Finite-state models of control systems were proposed by several researchers as a convenient mechanism to synthesize controllers enforcing complex specifications. Most techniques for the construction of such symbolic models have two main drawbacks: either they can only be applied to restrictive classes of systems, or they require the exact computation of reachable sets. In this paper, we propose a new abstraction technique that is applicable to any nonlinear sampled-data control system as long as we are only interested in its behavior in a compact set. Moreover, the exact computation of reachable sets is not required. The effectiveness of the proposed results is illustrated by synthesizing a controller to steer a vehicle.

Event-triggered and self-triggered control have been recently proposed as an alternative to the more traditional periodic execution of control tasks. The possibility of reducing the number of executions while guaranteeing desired levels of performance makes event-triggered and self-triggered control very appealing in the context of sensor/actuator networks. In this setting, reducing the number of times that a feedback control law is executed implies a reduction in transmissions and thus a reduction in energy expenditures. In this paper we introduce two novel distributed implementations of event-triggered and self-triggered policies over sensor/actuator networks and discuss their performance in terms of energy expenditure.

Wide deployment of wireless sensor and actuator networks in cyber-physical systems requires systematic design tools to enable dynamic tradeoff of network resources and control performance. In this paper, we consider three recently proposed aperiodic control algorithms which have the potential to address this problem. By showing how these controllers can be implemented over the IEEE 802.15.4 standard, a practical wireless control system architecture with guaranteed closed-loop performance is detailed. Event-based predictive and hybrid sensor and actuator communication schemes are compared with respect to their capabilities and implementation complexity. A two double-tank laboratory experimental setup, mimicking some typical industrial process control loops, is used to demonstrate the applicability of the proposed approach. Experimental results show how the sensor communication adapts to the changing demands of the control loops and the network resources, allowing for lower energy consumption and efficient bandwidth utilization.