## Basics

A YopSystem is a symbolic representation of a model. It handles semi-expicit differential algebraic equations (DAEs) of differential index 1, on the form:

dx = f(t, x, z, u, w, p)  % Differential equation
0 == g(t, x, z, u, w, p)  % Algebraic equation


where t represents the independent variable (typically time), x the state variable, z the algebraic variable, u the control input, w external inputs (exogenous variable), and p model parameters.

To declare a YopSystem, the following syntax is used:

mySystem = YopSystem(...
'states', numberOfStates, ...
'algebraics', numberOfAlgebraics, ...
'controls', numberOfControlInputs, ...
'externals', numberOfExternalInputs, ...
'parameters', numberOfParameters, ...
'model', @myModelFunction ...
)


Note The function call is independent of the input ordering. The output looks like (variable dimensions vary depending on the input):

>> mySystem

mySystem =

YopSystem with properties:



The properties t, x, z, u, w, p, ode, ae, y contains the symbolic variables and expressions representing the model. The same information is contained in the other entries, these are used internally, but can of course be used by the user, if that is preferred.

The entry model assumes a function handle on the following form:

function [dx, alg, signals] = myModelFunction(t, x, z, u, w, p)


dx is the evaluation of dx = f(t, x, z, u, w, p), and alg the evaluation of g(t, x, z, u, w, p) , both of these must be column vectors. signals represent any signal specified by the user. Opposite to dx and alg, this can be of arbitrary type, in the case of many signals, a struct is a good choice.

## The independent variable

The independent variable in Yop is treated in a special way using the class YopIndependentVariable. This way all YopSystems share the same independent variable. This is of practical value to the user when plotting or obtaining numerical results from a simulation or optimal control problem, since it means that the independent variable of any YopSystem can be used.

## When your system do not require all of the inputs or outputs

If your system happen to not need one or several of the inputs, then that entry can be omitted. For instance if your system only takes states and controls as input, the declaration looks as follows:

mySystem = YopSystem(...
'states', numberOfStates, ...
'controls', numberOfControlInputs, ...
'model', @myModelFunction ...
);


This means that correspoding outputs should also be removed (i.e. alg, as the system lacks an algebraic variable):

function [dx, ~] = myModelFunction(t, x, u)


where ~ can be replaced by a signals if desired.

## When the model file do not match the input-output pattern

If your model file do not match the specified input-output pattern, there are two alternative ways of specifying the system dynamics. The simplest way is to use an anonymous function:

mySystem = YopSystem(...
'states', numberOfStates, ...
'algebraics', numberOfAlgebraics, ...
'controls', numberOfControlInputs, ...
'externals', numberOfExternalInputs, ...
'parameters', numberOfParameters, ...
);


The other way of doing it is to omit the model entry. Then you use the symbolic variables to obtain expressions, either by using the variables to compute the output expressions, or using them to make a call to a model file:

mySystem = YopSystem(...
'states', numberOfStates, ...
'algebraics', numberOfAlgebraics, ...
'controls', numberOfControlInputs, ...
'externals', numberOfExternalInputs, ...
'parameters', numberOfParameters ...
);

% Order arbitrary, but default used for convenience
[dx, alg, signals] = myModelFunction(mySystem.t, mySystem.x, mySystem.z, ...
mySystem.u, mySystem.w, mySystem.p);

% Set model expressions
mySystem.set('ode', dx);
mySystem.set('alg', alg);

% Not necessary, but can be convenient
mySystem.set('y', signals);


## Connecting systems

One of the main reasons for supporting semi-explicit DAEs of differential index 1, is the possibility of connecting ordinary differential equations (ODEs). If the optimal control problem we are interested in solving is non-linear and non-convex, it may be necessary to provide a good initial guess. One way of doing that is by simulation. As the system may be unstable, or for any other reason need a controller in order to be make a simulation, it can be convenient to simply connect two ODEs via an algebraic equation. In Yop systems are connected in the following way:

mySystem = YopSystem('states', nx_sys, 'controls', nu, 'model' @myModelFunction);
myController = YopSystem('states', nx_ctrl, 'externals', nx_sys, 'model', @myController);

% Connecting the system state (could be any signal)
% to the controller external input
c1 = YopConnection(mySystem.x, myController.w);

% Connecting the control signal from the myController
% (stored in the signals output as a struct) to the
% control input of the system
c2 = YopConnection(mySystem.u, myController.y.controlSignal);


When used in a simulation or optimal control problem, the connections, in this case c1 and c2, need to be specified. Note it is possible to define expressions not contained in the model files when connecting the system. For instance if the controller should track a reference value, this can be formulated as the connection:

c1 = YopConnection(referenceValue - mySystem.x, myController.w);


Or if we want an unconnected signal, let’s say the third control input, to remain fixed, we can write:

c =  YopConnection(mySystem.u(3), 0);


## Important limitations

Yop uses CasADi for symbolic representation of model objects. This means the expressions making up a YopSystem can only contain expressions the can be formulated in CasADi’s symbolic framework. For instance the if-statesments like:

function dx = mySystem(t, x)

% ...

if x > 10
% ...
% Some code
% ...
end

% ...

end


In this case it is possible to replace the if-statement with the CasADi function if_else(expression, trueCase, falseCase). Most operations are available in CasADi, but for a complete list, visit the CasADi website.