In recent years, reinforcement learning (RL) has attracted significant attention from both
industry and academia due to its success in solving some complex problems. This paper …

Wind power plays a vital role in the global effort towards net zero. A recent figure shows that
93GW new wind capacity was installed worldwide in 2020, leading to a 53% year-on-year …

Many industrial processes utilize proportional-integral-derivative (PID) controllers due to
their practicality and often satisfactory performance. The proper controller parameters …

Deep reinforcement learning (RL) is an optimization-driven framework for producing control
strategies for general dynamical systems without explicit reliance on process models. Good …

With the emerging monitoring technologies, condition-based maintenance is nowadays a
reality for the wind energy industry. This is important to avoid unnecessary maintenance …

Wind turbine (WT) pitch control is a challenging issue due to the non-linearities of the wind
device and its complex dynamics, the coupling of the variables and the uncertainty of the …

This paper presents an adaptive neuro-fuzzy PID controller based on twin delayed deep
deterministic policy gradient (TD3) algorithm for nonlinear systems. In this approach, the …

In this paper, an online optimization approach of a fractional-order PID controller based on a
fractional-order actor-critic algorithm (FOPID-FOAC) is proposed. The proposed FOPID …

The increasing threat of cancer to human life and the improvement in survival rate of this
disease due to effective treatment has promoted research in various related fields. This …

El control del ángulo de las palas de las turbinas eólicas es complejo debido al
comportamiento no lineal de los aerogeneradores, ya las perturbaciones externas a las que …