LabProcesses

This package contains an (programming- as well as connection-) interface to serve as a base for the implementation of lab-process software. The first example of an implementaiton of this interface is for the ball-and-beam process, which is used in Lab1 FRTN35: frequency response analysis of the beam. The lab is implemented in BallAndBeam.jl, a package that makes use of LabProcesses.jl to handle the communication with the lab process and/or a simulated version thereof. This way, the code written for frequency response analysis of the beam can be run on another process implementing the same interface (or a simulated version) by changeing a single line of code :)

Installation

1. Start julia by typing julia in a terminal, make sure the printed info says it's v0.6+ running. If not, visit julialang.org to get the latest release.
2. Install LabProcesses.jl using command Pkg.clone("https://gitlab.control.lth.se/processes/LabProcesses.jl.git") Lots of packages will now be installed, this will take some time. If this is your first time using Julia, you might have to run julia> Pkg.init() before you install any packages.

How to implement a new process

1. Locate the file interface.jl. When the package is installed, you find its directory under ~/.julia/v0.6/LabProcesses/, if not, run julia> Pkg.dir("LabProcesses") to locate the directory. (Alternatively, you can copy all definitions from /interface_implementations/ballandbeam.jl instead. Maybe it's easier to work from an existing implementaiton.)
2. Copy all function definitions.
3. Create a new file under /interface_implementations where you paste all the copied definitions and implement them. See /interface_implementations/ballandbeam.jl for an example.
4. Above all function implementations you must define the process type, e.g,

   struct BallAndBeam <: PhysicalProcess
       h::Float64
       bias::Float64
   end
   BallAndBeam() = BallAndBeam(0.01, 0.0) # Constructor with default value of sample time

Make sure you inherit from PhysicalProcess or SimulatedProcess as appropriate. This type must contains fields that hold information about everything that is relevant to a particular instance of the process. Different ballandbeam-process have different biases, hence this must be stored. A simulated process would have to keep track of its state etc. in order to implement the measure and control methods. See Types in julia documentation for additional info regarding user defined types and (constructors)[https://docs.julialang.org/en/stable/manual/constructors/]. 5. Documentation of all interface functions is available in the file interface_documentation.jl

Control a process

The interface AbstractProcess defines the functions control(P, u) and measure(P). These functions can be used to implement your own control loops. A common loop with a feedback controller and a feedforward filter on the reference is implemented in the function run_control_2DOF, where the user can supply G_1 and G_4 in the diagram below, with the process P=G_2.

The macro @periodically might come in handy if you want to implement your own loop. Consider the following example, in which the loop body will be run periodically with a sample time of h seconds.

for (i,t) = enumerate(0:h:duration)
    @periodically h begin
        y[i] = measure(P)
        r[i] = reference(t)
        u[i] = calc_control(i,y,r)
        control(P, u[i])
    end
end

Often one finds the need to implement a stateful controller, i.e., a function that has a memory or state. To this end, the function sysfilter is provided. This function is used to implement control loops where a signal is filtered through a dynamical system, i.e., U(z) = C(z)E(z). Usage is demonstrated below, which is a simplified implementation of the block diagram above (transfer function- and signal names corresponds to the figure).

stateG1 = init_sysfilter(G1)
stateG4 = init_sysfilter(G4)
function control(i)
    rf = sysfilter!(stateG4, G4, r)
    e  = rf-y
    u  = sysfilter!(stateG1, G1, e)
end

G1 and G4 must here be represented by StateSpace types from ControlSystems.jl. TransferFunction types can easily be converted to a StateSpace by Gss = ss(Gtf). Continuous time systems can be discretized using Gd = c2d(Gc, h). (The sample time of a process is available through h = sampletime(P).)