Search

This manuscript introduces a perturbation-free extremum-seeking control strategy specifically designed to enhance the operational performance of wind turbines under optimal conditions. The strategy employed utilizes a perturbation-free extremum-seeking approach to ensure the wind turbine farm operates at maximum power efficiency while also reducing power output fluctuations. By employing this control system, the wind turbine generators are maintained at their optimal power output level, effectively navigating through disturbances such as tower shadow, wind shear, and the erratic nature of wind speeds without introducing external perturbations.The algorithm is adept at managing the blade pitch angles and the turbines’ rotational speed, ensuring a controlled and efficient operation. Furthermore, this paper outlines a perturbation-free method to optimize energy production and decrease fatigue loads, thereby extending the operational lifespan of a wind turbine. The superior operational efficiency of the wind turbine array generators achieved through this approach underscores its effectiveness.The robustness and effectiveness of this perturbation-free control system are validated through comprehensive simulation tests on an array comprising four wind turbine generators. The outcomes of these simulations solidly back the extremum-seeking control system’s proficiency in reaching maximum power output without relying on perturbative methods, highlighting its innovative contribution to wind turbine efficiency optimization.

Heart dynamics are usually unknown and require the application of real-time control technique because of the fatal nature of most cardiac arrhythmias. The problem of controlling the heart dynamics in a real-time manner is formulated as an adaptive learning output-tracking problem. For a class of nonlinear dynamic systems with unknown nonlinearities and nonaffine control input, a Lyapunov-based technique is used to develop a control law. An adaptive learning algorithm is exploited that guarantees the stability of the closed-loop system and convergence of the output tracking error to an adjustable neighborhood of the origin. In addition, good approximation of the unknown nonlinearities is also achieved by incorporating a persistent exciting signal in the parameter update law. The effectiveness of the proposed method is demonstrated by an application to a cardiac conduction system modelled by two coupled driven oscillators.

This paper proposes a nonlinear finite-time converging observer for a class of nonlinear systems. The estimate is recovered from the present and delayed estimates provided by two independent dynamical systems converging to a function of the state with linear error dynamics. The estimation is carried out using only the Jacobian matrix of both transformations determined by solving two systems of partial derivative equations. The results are illustrated on a bioreactor model.

Abstract Soil C is the largest C pool in forest ecosystems that contributes to C sequestration and mitigates climate change. Tree diversity enhances forest productivity, so diversifying the tree species composition, notably in managed forests, could increase the quantity of organic matter being transferred to soils and alter other soil properties relevant to the C cycle. A ten‐year‐old tree diversity experiment was used to study the effects of tree identity and diversity (functional and taxonomic) on soils. Surface (0–10 cm) mineral soil was repeatedly measured for soil C concentration, C:N ratio, pH, moisture, and temperature in twenty‐four tree species mixtures and twelve corresponding monocultures (replicated in four blocks). Soil pH, moisture, and temperature responded to tree diversity and identity. Greater productivity in above‐ and below‐ground tree components did not increase soil C concentration. Soil pH increased and soil moisture decreased with functional diversity, more specifically, when species had different growth strategies and shade tolerances. Functional identity affected soil moisture and temperature, such that tree communities with more slow‐growing and shade‐tolerant species had greater soil moisture and temperature. Higher temperature was measured in communities with broadleaf‐deciduous species compared to communities with coniferous‐evergreen species. We conclude that long‐term soil C cycling in forest plantations will likely respond to changes in soil pH, moisture, and temperature that is mediated by tree species composition, since tree species affect these soil properties through their litter quality, water uptake, and physical control of soil microclimates.