This work presents a hierarchical distributed model predictive control approach for multiple agents with cooperative negotiations based on fuzzy inference. Specifically, a fuzzy-based two-layer control architecture is proposed. In the lower control layer, there are pairwise negotiations between agents according to the couplings and the communication network. The resulting pairwise control sequences are sent to a coordinator in the upper control layer, which merges them to compute the final ones. Furthermore, conditions to guarantee feasibility and stability in the closed-loop system are provided. The proposed control algorithm has been tested on an eight-coupled tank plant via simulation.
Next-generation cellular networks are large-scale systems composed of numerous base stations interacting with many diverse users. One of the main challenges with these networks is their high energy consumption due to the expected number of connected devices. We handle this issue with a coalitional Model Predictive Control (MPC) technique for the case of next-generation cellular networks powered by renewable energy sources. The proposed coalitional MPC approach is applied to two simulated scenarios and compared with other control methods: the traditional best-signal level mechanism, a heuristic algorithm, and decentralized and centralized MPC schemes. The success of the coalitional strategy is considered from an energy efficiency perspective, which means reducing on-grid consumption and improving network performance (e.g., number of users served and transmission rates).
This paper presents a novel clustering model predictive control technique where transitions to the best cooperation topology are planned over the prediction horizon. A new variable, the so-called transition horizon, is added to the optimization problem to calculate the optimal instant to introduce the next topology. Accordingly, agents can predict topology transitions to adapt their trajectories while optimizing their goals. Moreover, conditions to guarantee recursive feasibility and robust stability of the system are provided. Finally, the proposed control method is tested via a simulated eight-coupled tanks plant.
This book chapter proposes a description of smart gateways and cyber-physical systems (CPS) for the industrial internet of things (I-IOT). It also presents a case study where a smart gateway is developed to be used in different types of industrial equipment for the shop floor. The case study is developed under the specifications of different industries in the region of Castelo Branco. It is a proof that the 4th industrial revolution will be the engine for SME innovation, independence of the regions and their financial strength. It is also proof that the cooperation between universities, industries and startups can evolve to break barriers and add value in the improvement of regional industries competitiveness. Topics that will be addressed on the chapter can be used for developers, students, researchers and enthusiasts to learn topics related to I-IOT, such as data acquisitions systems, wired and wireless communication devices and protocols, OPC servers and LabVIEW programming.
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