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Event-triggered output feedback control for distributed networked systems
Magdi S Mahmoud1, Muhammad Sabih1, Moustafa Elshafei1
1Systems Engineering Department, King Fahd University of Petroleum and Minerals, P.O. Box 5067, Dhahran 31261, Saudi Arabia.
ISA Transactions
|December 29, 2015
Summary
This study introduces an event-triggered output-feedback control for distributed systems, reducing communication load. It uses a linear matrix inequality (LMI) approach for systems with partial state information.
Area of Science:
- Control Engineering
- Networked Systems
- Systems Theory
Background:
- Distributed networked control systems (DNCS) face challenges in communication efficiency and control under partial state information.
- Event-triggered communication strategies offer a promising solution to reduce network load compared to time-triggered systems.
Purpose of the Study:
- To develop an event-triggered output-feedback control scheme for distributed systems with partial state availability.
- To formulate the control design problem as a linear matrix inequality (LMI) feasibility problem.
Main Methods:
- The proposed scheme utilizes local observers within subsystems to estimate states.
- Information is shared among neighboring subsystems only when a local error threshold is exceeded.
- The control design is framed as a linear matrix inequality (LMI) feasibility problem, enabling systematic solution.
Main Results:
- The event-triggered output-feedback control scheme effectively manages communication in distributed systems.
- The LMI formulation provides a feasible approach for designing controllers for systems with partial state information.
- Demonstrated effectiveness through a coupled cart example from existing literature.
Conclusions:
- The developed event-triggered output-feedback control is a viable strategy for enhancing communication efficiency in DNCS.
- The LMI-based design approach offers a robust method for addressing control problems with limited state information.
- This work contributes to the advancement of efficient and decentralized control strategies for networked systems.
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