Iterated function system

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Related publications (27)

Iterative Learning Control of a Parallel Delta Robot

Mohamed Bouri

In this work, an iterative learning control (ILC) is applied to a Delta robot in order to improve the tracking precision at high dynamic movement. Delta robot is a parallel manipulator designed for high-speed pick and place operations. Since the dynamic of ...

SPRINGER2019

Optimal Design of Heat-Integrated Water Allocation Networks

François Maréchal, Ivan Daniel Kantor, Maziar Kermani

Industrial operations consume energy and water in large quantities without accounting for potential economic and environmental burdens on future generations. Consumption of energy (mainly in the form of high pressure steam) and water (in the form of proces ...

2019

Expectation propagation in the large data limit

Guillaume Philippe Ivan Joseph Dehaene

Expectation propagation (EP) is a widely successful algorithm for variational inference. EP is an iterative algorithm used to approximate complicated distributions, typically to find a Gaussian approximation of posterior distributions. In many applications ...

Wiley2018

Exploratory Topology Modelling of Form-Active Hybrid Structures

Mark Pauly, Anders Holden Deleuran

The development of novel form-active hybrid structures (FAHS) is impeded by a lack of modelling tools that allow for exploratory topology modelling of shaped assemblies. We present a flexible and real-time computational design modelling pipeline developed ...

Elsevier Science Bv2016

A Primal-dual Framework For Mixtures Of Regularisers

Volkan Cevher, Cosimo Aprile, Quoc Tran Dinh, Luca Baldassarre, Baran Gözcü

Effectively solving many inverse problems in engineering requires to leverage all possible prior information about the structure of the signal to be estimated. This often leads to tackling constrained optimization problems with mixtures of regularizers. Pr ...

2015

A consensus algorithm for networks with process noise and quantization error

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

In this paper we address the problem of quantized consensus where process noise or external inputs corrupt the state of each agent at each iteration. We propose a quantized consensus algorithm with progressive quantization, where the quantization interval ...

IEEE2015

Use of Transient Measurements for Real-Time Optimization via Modifier Adaptation

Dominique Bonvin, Grégory François

Real-time optimization (RTO) methods use measurements to offset the effect of uncertainty and drive the plant to optimality. Explicit RTO schemes, which are characterized by solving a static optimization problem repeatedly, typically require multiple itera ...

2013

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