Research Interest

A networked control system (NCS) is a control system wherein the control loops are closed through a communication network. The defining feature of an NCS is that control and feedback signals are exchanged among the system's components in the form of information packages through a network. In the presence of the communication network in the NCSs, the conventional control components include the sensor, the controller, and the actuator work as network nodes from the perspective of network topology.

A networked multi-agent system (NMAS) is a control system that is composed of multiple subsystems (called ‘agents’) that are physically separated. In this control structure, all agents communicate with each other (depending on the system’s topology) via their local controllers over the network. Based on the numbers of published research findings within the control community, NMAS-related studies have been noticeably active over the last few decades. The NMAS structure in particular has sparked the curiosity of researchers who are interested in finding a reliable control strategy, especially for large-scale process control systems that cover large geographical areas; these systems consist of many subsystems, sensors, and actuators. This structure increases the flexibility and scalability of the control system by allowing relatively easy and cheap expansion of the physical structure of the system. In terms of controller performance, the NMAS also helps to simplify large systems’ operations and makes them simpler and faster to accomplish.

Predictive control is a control algorithm based on a predictive model of the process. The model is used to predict the future output based on historical information about the process, as well as anticipated future input. It emphasizes the function of the model, not the structure of the model. Therefore, a state equation, transfer function, or even a step or impulse response can be used as the predictive model. The predictive model is capable of showing the future behavior of the system. Therefore, the designer can experiment with different control laws to see the resulting system output, using computer simulation. Predictive control is an algorithm of optimal control. It calculates future control action based on a penalty or a performance function.

Through digitization towards smart factories, Industrial Internet of Things, smart manufacturing, and advanced manufacturing improves responsiveness of the manufacturing, quality, and efficiency. By enabling the creation of networks that include the whole production process, factories may be transformed into intelligent environments. Smart machines, warehousing systems, and manufacturing facilities with end-to-end integration, encompassing incoming logistics, production, marketing, outgoing logistics, and service, are examples of linkages. Flexible Manufacturing System (FMS) in Industry 4.0 is expected to foster tighter collaboration among corporate partners (such as suppliers and customers) as well as among personnel, creating new potential for mutual benefit.