A middleware framework for market-based actuator coordination in sensor and actuator networks
Proceedings of the 5th international conference on Pervasive services
GA-based modified adaptive fuzzy sliding mode controller for nonlinear systems
Expert Systems with Applications: An International Journal
Feedback scheduling of priority-driven control networks
Computer Standards & Interfaces
On the Continuous Control of the Acrobot via Computational Intelligence
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Fuzzy adaptive control for the actuators position control and modeling of an expert system
Expert Systems with Applications: An International Journal
Fuzzy target tracking control of autonomous mobile robots by using infrared sensors
IEEE Transactions on Fuzzy Systems
Demand-driven power saving by multiagent negotiation for HVAC control
Joint Proceedings of the Workshop on AI Problems and Approaches for Intelligent Environments and Workshop on Semantic Cities
Hi-index | 0.00 |
In recent years, the public has been paying ever greater attention to problems associated with energy production and consumption. Energy-supply issues rightly constitute one of the most important issues that we face. In the absence of any viable alternative energy supply, a strategy that would result in energy savings is a legitimate goal. In this paper, we propose a genetic algorithm-based method by which electrical operators in a cyber physical system could be scheduled and controlled. Our method accounts for not only process output but also environmental variation. We propose that the electrical operators be of the same function but with different capabilities. One set of sensors would be placed dispersedly around the to-be-affected area for measuring the output of the processes. Another set of sensors would collect the environmental variation value for prediction purposes. The simulation results show that the application of our proposed GA-based Actuator Control (GAAC) method to the aforementioned cyber physical system can minimize its power consumption while accomplishing the desired set point.