Particle swarm optimization based networked control system design with uncertainty

Ti-Hung Chen,Ming-Feng Yeh,Wen-Yo Lee

doi:10.1051/matecconf/201711901051

Ti-Hung Chen, Ming-Feng Yeh + Show 1 more

Open Access

https://doi.org/10.1051/matecconf/201711901051

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Abstract

This study discusses the design of state feedback control for networked control system (NCS) with uncertainty, where the feedback controller is used to solve the latency and the packet dropout caused by NCS. The conventional design approach generally adopts Lyapunov stability theorem to analyse the stability of NCSs and then Lyapunov-Krasovskii stability criterion is solved to obtain the control gain matrix. Rather than using complex Lyapunov-Krasovskii stability criterion and solving difficult linear matrix inequality (LMI) problem in the control design, this study attempts to utilize particle swarm optimization (PSO) algorithm to search an optimal feedback control gain for the NCS. Finally, the computer simulation is illustrated the proposed control strategy and demonstrated the control performance.

Highlights

Nowadays, increasing attention has been paid to design of networked control systems (NCSs) in which the components are spatially distributed and connected via a share communication network [1,2,3,4,5,6,7,8,9,10]
In NCSs, data is transmitted in atomic unit called data packets
The system states and output signals are sampled by the sensors, transmitted to the controllers over the network, and the controller signals are transmitted to the actuators by the data packets

Summary

Introduction

Nowadays, increasing attention has been paid to design of networked control systems (NCSs) in which the components (e.g., sensors, actuators, and controllers) are spatially distributed and connected via a share communication network [1,2,3,4,5,6,7,8,9,10]. Particle swarm optimization (PSO) algorithm, proposed by Kennedy and Eberhart in 1995 [13], was inspired by the social behavior of bird flocking and fish schooling. It works by maintaining a swarm of particles that move around in the search space influenced by the improvements discovered by the other particles. With the help of randomly searching ability of PSO algorithm, this study attempts to utilize PSO algorithm to search the optimal control gain matrix for the NCS with uncertainty, instead of solving complex LMI or eigenvalue problem.

Problem formulations

PSO based NCS design

Simulation result

Conclusions