Update index.md

docs/src/index.md

@@ -22,12 +22,16 @@ 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](https://gitlab.control.lth.se/processes/LabProcesses.jl/blob/master/src/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.
+### 1.
+Locate the file [interface.jl](https://gitlab.control.lth.se/processes/LabProcesses.jl/blob/master/src/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](https://gitlab.control.lth.se/processes/LabProcesses.jl/blob/master/src/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
+### 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](https://gitlab.control.lth.se/processes/LabProcesses.jl/blob/master/src/interface_implementations/ballandbeam.jl) for an example.
-4. Above all function implementations you must define the process type, e.g,
+### 4.
+Above all function implementations you must define the process type, e.g,
 ```julia
 struct BallAndBeam <: PhysicalProcess
     h::Float64
@@ -42,7 +46,8 @@ 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](https://docs.julialang.org/en/stable/manual/types/#Composite-Types-1)
 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](https://gitlab.control.lth.se/processes/LabProcesses.jl/blob/master/src/interface_documentation.jl)
+### 5.
+Documentation of all interface functions is available in the file [interface_documentation.jl](https://gitlab.control.lth.se/processes/LabProcesses.jl/blob/master/src/interface_documentation.jl)
 
 # How to control a process
 The interface `AbstractProcess` defines the functions `control(P, u)` and `measure(P)`.
@@ -150,12 +155,8 @@ the user is unsure about a reasonable value.
 ## Non-linear process
 Your first option is to linearize the process and proceed like above.
 Other options include
-1. Make `control` perform forward Euler, i.e., `x' = f(x,u)*h` for a general
-system model ``x' = f(x,u); y = g(x,u)`` and sample time ``h``.
-2. Integrate the system model using some fancy method like Runge-Kutta. See
-[DifferentialEquations.jl](http://docs.juliadiffeq.org/stable/types/discrete_types.html)
-for discrete-time solving of ODEs (don't be discouraged, this is almost as simple as
-forward Euler above).
+1. Make `control` perform forward Euler, i.e., `x[t+1] = x[t] + f(x[t],u[t])*h` for a general system model ``x' = f(x,u); y = g(x,u)`` and sample time ``h``.
+2. Integrate the system model using some fancy method like Runge-Kutta. See [DifferentialEquations.jl](http://docs.juliadiffeq.org/stable/types/discrete_types.html) for discrete-time solving of ODEs (don't be discouraged, this is almost as simple as forward Euler above).
 
 # Exported functions and types
 ```@autodocs