[julia-users] Re: Optimal Control using Dynamic Programming

If you formulate the problem as a Markov decision process, you can use POMDPs.jl which supports value iteration . The POMDPs.jl framework requires a functional problem definition, and some examples can be

[julia-users] Re: Optimal Control using Dynamic Programming

I'm also bias to recommend formulating a nonlinear programming problem and using JuMP with IPOPT. This approach has been successfully demonstrated in the chemical engineering controls/systems literature on some rather nasty large nonlinear systems. Here is a sample problem for nonlinear

Re: [julia-users] Re: Optimal Control using Dynamic Programming

If you want an uninitialized 61-by-61 array of double precision floating point numbers you can do Array(61, 61) If you want the array initialized to zero you can call zeros(61, 61) A few for loops should accomplish what you're after here. Depending how expenaive your cost function is to

Re: [julia-users] Re: Optimal Control using Dynamic Programming

I have 3 states and two inputs. State 1 is [10:1:20], state 2 is [85:0.2:95] and state 3 is [1:1:12]. The two inputs are [0 1] and [-1 0]. On Sep 25, 2015 1:00 PM, "Tony Kelman" wrote: > If you want an uninitialized 61-by-61 array of double precision floating > point numbers you

[julia-users] Re: Optimal Control using Dynamic Programming

you may find the Julia interface to apmonitor useful: https://groups.google.com/forum/#!searchin/julia-opt/apmonitor/julia-opt/y5sc_xtLJfk/PKNBik_A82AJ good luck, cdm On Thursday, September 24, 2015 at 10:25:19 PM UTC-7, NV wrote: > > Hi, > I am new to Julia. I need to solve an optimal

[julia-users] Re: Optimal Control using Dynamic Programming

Hello, as far as I know, there is no ready-made package for optimal control. There is one package on control design: https://github.com/JuliaControl/Control.jl And there are a lot of packages for solving optimization problems. Could you be a little bit more specific about your problem? How do

[julia-users] Re: Optimal Control using Dynamic Programming

The closest pre-made package for doing dynamic programming for optimal control would likely be one of the quantitative economics packages. If you have discrete decisions or want to grid your input space, it should be fairly straightforward to write out a cost-to-go matrix and apply the Bellman

[julia-users] Re: Optimal Control using Dynamic Programming

I'm biased, but for control problems with constraints I would pose it as a model predictive control problem and use JuMP.jl with the Ipopt.jl optimization solver. If you prefer to construct a cost to go map and do dynamic programming then I can't point you to any Julia code that I know of that

[julia-users] Re: Optimal Control using Dynamic Programming

The system is non-linear. I have a cost function, that I need to minimize to find the optimal control to move from one state to another. There are a few constraints that the states should satisfy even. On Friday, 25 September 2015 01:20:52 UTC-5, Uwe Fechner wrote: > > Hello, > as far as I

[julia-users] Re: Optimal Control using Dynamic Programming

Hi, I am trying to control the velocity of a system optimally. I have a cost function (DP formulation) to minimize subject to a few constraints. Thanks On Friday, 25 September 2015 00:25:19 UTC-5, NV wrote: > > Hi, > I am new to Julia. I need to solve an optimal control problem using >

Re: [julia-users] Re: Optimal Control using Dynamic Programming

Thank you for your inputs. My concern was about calculating the cost to go map. I have discretized the state space and have 61 possible states in each stages and there are 20 such stages. That roughly amounts to 61*61 values for one stage. I am overwhelmed by the amount of computations that this