Feedback Scheduling Of Networked Control Systems And Collaborative Design

Networked control system is the multidisciplinary combination of computer network, communication technology and control science, etc, which is popular in many fields. Such as industrial automation, mobile robotics, aircraft and spacecraft, etc. However, the insertion of network brings many new issues inevitably.From the control and scheduling co-design perspective in this thesis, the key issues of feedback scheduling for networked control systems are studied. The main research contributions are as follows:(1) Scheduling of networked control systems is analyzed. Several classical scheduling algorithms are introduced such as RM, EDF and MEF-TOD. Simulation shows that the sampling period impacts the system performance greatly. Then deficiencies of the traditional open-loop scheduling algorithms are summarized, the feedback scheduling and co-design algorithms are introduced detailedly.(2) Considering network utilization, the control performance and schedulable, the existed static scheduling optimization algorithm is improved. Simulation illustrates the effectiveness of this algorithm. For the defects of open-loop scheduling algorithms, the idea of feedback is introduced into networked control systems, the design scheme of feedback scheduler as well as the evaluation indicators of the system performance is proposed.(3) For multiple control loops sharing the limited bandwidth in network control systems, a centralized fuzzy feedback scheduling algorithm is designed which considers the error and error variation of control loops. Then the priority of control loops is adjusted dynamically based on the logic relations and fuzzy control rules of fuzzy inference system. Simulation results show that this algorithm is effective.(4) For the system performance deteriorating under the limited bandwidth resource, a co-design algorithm combined sampling period with priority is proposed according to the control and scheduling co-design idea. The sampling period is adjusted dynamically using the control error via the proposed algorithm, and the priority is allocated according to IAE. Simulation results show that the system performance is improved obviously.