Sanket Sanjay Diwale

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Data-driven modeling and feedback control play a vital role in several application areas ranging from robotics, control theory, manufacturing to management of assets, financial portfolios and supply chains. Many such problems in one way or another are rela ...

Airborne wind energy systems are built to exploit the stronger and more consistent wind available at high altitudes that conventional wind turbines cannot reach. This however requires a reliable controller design that can keep the airborne system flying fo ...

Wind resources tend to be significantly stronger and more consistent with increasing altitude. This effect creates a potential for power generation that can be reaped by an Airborne Wind Energy system positioned at elevations exceeding the height of conven ...

The necessary and sufficient conditions for existence of a generalized representer theorem are presented for learning Hilbert space - valued functions. Representer theorems involving explicit basis functions and Reproducing Kernels are a common occurrence ...

Many real-time optimization schemes maximize process performance by performing a model-based optimization. However, due to plant-model mismatch, the model-based solution is often suboptimal. In modifier adaptation, measurements are used to correct the mode ...

A novel manifold learning approach is presented to incorporate computationally efficient obstacle avoidance constraints in optimal control algorithms. The method presented provides a significant computational benefit by reducing the number of constraints r ...

A nonlinear adaptive path following controller for a kite based airborne wind energy system is presented. For a given desired geometric path, we provide necessary conditions for closed-loop convergence of the kite to a tube centered around the desired path ...

The present invention concerns a method of emulating gradient flow for solving a given problem as a charge distribution in a device (1) comprising: first type charge carrier regions (5) interfacing a second type charge carrier region (11) thereby forming c ...

A short technical subsection for Gaussian Process learning and Uncertainty propagation is presented as required in applications like Model Predictive Control, machine learning and optimization. ...

Sanket Sanjay Diwale

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Kernel methods and Model predictive approaches for Learning and Control

Optimization of an Airborne Wind Energy System using Constrained Gaussian Processes with Transient Measurements

Optimization of an Airborne Wind Energy System Using Constrained Gaussian Processes

A Generalized Representer Theorem for Hilbert Space - Valued Functions

Active Directional Modifier Adaptation with Trust Region - Application to Energy-Harvesting Kites

Manifold Learning and Optimal Control for Obstacle Avoidance in Autonomous Driving

A Nonlinear Adaptive Controller for Airborne Wind Energy Systems

Gradient flow emulation using drift diffusion processes

Gaussian Processes for System Identification, Control and Optimisation

Model Predictive Path-Following Control for Airborne Wind Energy Systems