Complexity Dynamics and Fuzzy Optimal Prescribed-Time Control of a Large Network of Bidirectionally Coupled FO PMSG

Attaining both fast synchronization with high precision and operational stability in multimachine power systems remains a mammoth technical challenge. This article investigates complexity dynamics and fuzzy optimal prescribed-time control of a network of bidirectionally coupled fractional-order (FO) permanent magnet synchronous generator (PMSG). First, a mathematical model of a large network of bidirectionally coupled FO PMSG with few neighboring node connections and coupling strength is established based on the topological layout of a wind farm. Complexity dynamics reveal that this network can exhibit chimera and global synchronization states under varying conditions, including different FOs and coupling strengths. To achieve global synchronization, preset tracking precision within a prescribed-time, security constraint, and operational flexibility in this safety-critical network, a fuzzy optimal prescribed-time control strategy comprising a feedforward neural prescribed-time controller and a feedback safe optimal controller is proposed, using a type-3 fuzzy neural network (FNN) to address system uncertainty. Furthermore, we develop a hardware-in-the-loop simulation platform based on the STM32F767IGT6 microcontroller, featuring: 12-bit digital to analog converter (DAC) for waveform generation to oscilloscope, direct memory access (DMA)-controlled data transmission bypassing CPU intervention, and timer-configured overflow and event triggering mechanisms. Finally, extensive results further validate the feasibility and effectiveness of our scheme.