access icon free Stabilisation of event-triggered-based neural network control system and its application to wind power generation systems

© The Institution of Engineering and Technology
Received 06/03/2019, Accepted 20/01/2020, Revised 04/10/2019, Published 12/02/2020

This study addresses the event-triggered (ET)-based stabilisation problem of neural-network-based control system (NNBCS) and illustrates the direct application to wind power generation system. In this regard, the novel ET-based controller algorithm is designed for NNBCS instead of sampled data controller (sampling will be initiated at a fixed rate regardless whether it is required or not) which reduces the computation complexity by avoiding the unnecessary details over the transmission. The novel stability and stabilisation conditions are expressed in terms of linear matrix inequalities that are derived through constructing the time-dependent Lyapunov functional candidate. For deepening the knowledge in the outcomes of the proposed conditions, the study numerically evaluates the dynamic models such as variable-speed wind turbine drive system, permanent magnet synchronous motors model and traditional inverted pendulum model and validates the effectiveness of the proposed controller scheme. Finally, a comparison result shows the superiority of the derived conditions.

Inspec keywords: control system synthesis; sampled data systems; neurocontrollers; Lyapunov methods; linear matrix inequalities; nonlinear control systems; synchronous motors; wind power plants; machine control; power system stability; pendulums; wind turbines; stability

Other keywords: NNBCS; neural-network-based control system; controller algorithm; time-dependent Lyapunov functional; power generation system; variable-speed wind turbine drive system; sampled data controller; event-triggered-based stabilisation problem; event-triggered-based neural network control system

Subjects: Discrete control systems; Stability in control theory; Algebra; Control of electric power systems; Neurocontrol; Algebra, set theory, and graph theory; Algebra; Wind power plants; Nonlinear control systems; Wind energy; Control system analysis and synthesis methods; Synchronous machines

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