Control-Scheduling Codesign for NCS based Fuzzy Systems

Abstract

In the present paper, a fuzzy codesign approach is proposed to deal with the controller and scheduler design for a networked control system which is physically distributed with a shared communication network. The proposed fuzzy controller is applied to generate the control with different sampling-actuation periods, the configuration supposes a strict actuation period disappears the jitter. The proposed fuzzy scheduling is designed to select the sampling-actuation period. So, the fuzzy codesign reduces the rate of transmission when the system is stable through the scheduler while the controller adjusts the control signal. The fuzzy codesign guarantees the stability of all the system if the network uncertainties do not exceed an upper bound and is a low computational cost method implemented with an embedded system. An unstable, nonlinear system is used to evaluate the proposed approach and compared to a hybrid control, the results show greater robustness to multiple lost packets and time delays much larger than the sampling period. (This paper is an extension of [20]. Reprinted (partial) and extended, with permission based on License Number 4275590998661 IEEE, from "Electrical Engineering, Computing Science and Automatic Control, 2017 14th International Conference on")

Scheduling strategy for networked control system based on variable sampling period and deadband feedback

“…The relative importance of each closed loop in NCS is not considered Fuzzy priority scheduling [21][22][23] The priority changes dynamically with the system output error…”

“…The verification results show that the proposed variable sampling scheduling strategy has improved the performance of the system and reduced the data transmission time and transmission error. In the research, 23 a fuzzy controller is designed to generate different control periods of sampling drive. A strict control period is assumed to eliminate packet jitter.…”

Scheduling of Dynamic Multi-Objective Flexible Enterprise Job-Shop Problem Based on Hybrid QPSO

“…The work flow of the FJSP is illustrated as Figure 1 below. In the existing studies, the FJSP covers both singleobjective problems and multi-objective problems [8]- [10].…”