This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based

sampling techniques. The proposed control scheme preserves all well-known individual advantages of

GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an

important reduction of actuation load meanwhile the control system performance is maintained within

an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial

process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish

a tradeoff between control performance and the number of actuations. The performance of the proposed

control algorithm is first verified for a first-order plus delay process and afterwards it is uated by

using a case study based on the greenhouse temperature control problem.-This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based

sampling techniques. The proposed control scheme preserves all well-known individual advantages of

GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an

important reduction of actuation load meanwhile the control system performance is maintained within

an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial

process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish

a tradeoff between control performance and the number of actuations. The performance of the proposed

control algorithm is first verified for a first-order plus delay process and afterwards it is　uated by

using a case study based on the greenhouse temperature control problem.