One of the main benefits of the research conducted in the DyCon’s working packages is the development of computational contents that include **algorithms, articles, tutorials, visualizations, sample codes and software** that will be integrated in this web. All those computational contents can be accessed and downloaded through the following index where you can see those contents ordered by the DyCon’s working packages which they are related to:

WP1: Control of parameter dependent problems (PDC)

**Greedy Control**

Control of a parameter dependent system in a robust manner

WP2: Long time horizon control and the turnpike property (LTHC)

**Turnpike property for functionals involving L**

^{1}−normWe want to study the following optimal control problem...

**Numerical aspects of LTHC of Burgers equation**

Numerical approximation of the inverse design problem for the Burgers equation

**Long time control and the Turnpike property**

The turnpike property improves the numerical methods used to solve optimal control problems

WP3: Control under constraints (CC)

**IpOpt and AMPL use to solve time optimal control problems**

How to use IpOpt to solve time optimal control problems

WP4: Inverse design and control in the presence of singularities (SINV)

**Conservation laws in the presence of shocks**

Tracking control of 1D scalar conservation laws in the presence of shocks

WP5: Models involving memory terms and hybrid PDE+ODE systems (MHM)

**Finite element approximation of the 1-D fractional Poisson equation**

A finite element approximation of the one-dimensional fractional Poisson equation with applications to numerical control

**Control of PDEs involving non-local terms**

The problem of controllability of fractional (in time) Partial Differential Equations

WP6: From finite to infinite-dimensional models (FI)

**Kolmogorov equation**

Various numerical approximation methods are discussed with the aim of recoving the large time asymptotic properties of the hypoelliptic Kolmogorov model

**Optimal control applied to collective behaviour**

"Guidance by repulsion” model describing the behaviour of two agents, a driver and an evader