Initialization Script: Orange Juice Canning

Inits the combined discrete-continuous example "Orange Juice Canning" from "Introduction to Simulation using SIMAN", page 451.

Preparation
Create the Model
After Incarnation
Define Some Values for ODE-Plot
Finally

Basic models are taken from the "Orange Juice Canning" example, folder DEVSPATH/01-modelbase/orange_juice_canning.

Call: init_orange_juice_canning

File: DEVSPATH/02-examples/hybrid/orange_juice_canning/init_orange_juice_canning.m

Model Structure

Preparation

global SIMUSTOP % to stop simulation by condition
SIMUSTOP = 0;

global HYBRID
HYBRID = 1; % it's a hybrid model

elapsed = 0;

Create the Model

Atomic models' classes: am_truck_generator, am_fifo_queue, am_dock_undock_server, am_truck, am_tank, am_canner, am_truck_transducer

% Components for coupled model root_model
% Since hybrid DEVs is still in experimental phase, hybrid models need to be flattenend, so that there is no
% hierarchy.
%
% Take care to choose different seeds for random number generators!


% Generator for trucks, exponential 44 min. mean.
% This is a discrete atomic.
random_seed = 4; % system parameter
inistates = struct('sigma',0,'rand_state',[],'number_generated',0,'generation_times',[]);% generate first truck at right beginning
t_gen =  am_truck_generator('t_gen',inistates,elapsed,random_seed);

% Queue for trucks, FIFO.
% This is a discrete atomic.
inistates = struct('sigma',inf,'queue_length',0,'queue_stats',[0,0],'requested',1);
queue = am_fifo_queue('queue',inistates,elapsed);

% Server for docking process for trucks.
% This is a discrete atomic.
% System parameter service_time
% uniformely distributed 1-2 min.
service_time = [1,2];
random_seed = 2; % system parameters
inistates = struct('sigma',inf,'rand_state',[]);
dock = am_dock_undock_server('dock',inistates,elapsed,service_time,random_seed);

% Server for undocking process for trucks.
% This is a discrete atomic.
service_time = [1,2];
random_seed = 3; % system parameters
inistates = struct('sigma',inf,'rand_state',[]);
undock = am_dock_undock_server('undock',inistates,elapsed,service_time,random_seed);

% Truck unload.
% This is a hybrid atomic.
% Event, if truck is empty.
TruckLevel = 0;
TruckRate = 0;
c_inistates = [TruckLevel; TruckRate];% continuous initial values
inistates = struct('sigma',inf,'active',1,'arrival',0);% 'active' == 1 at init means: "not stopped by signal from tank"
truck = am_truck('truck',inistates,c_inistates,elapsed);


% Tank.
% This is a hybrid atomic.
% Events, if filled with 6000 gallons,
%         if sunk to 5500 gallons,
%         if empty.
TankLevel = 0;
TankRate = 0;
c_inistates = [TankLevel; TankRate;];% continuous initial values
inistates = struct('sigma',inf,'filling_suspended',0,'event_type','');
tank = am_tank('tank',inistates,c_inistates,elapsed);

% Canning.
% This is a hybrid atomic.
% Event, if 48 gallons filled.
CannerLevel = 0;
CannerRate = 0;
c_inistates = [CannerLevel; CannerRate];% continuous initial values
inistates = struct('sigma',inf,'up_time',0, 'start_time',0);% canner up time and start time for statistics
canner = am_canner('canner',inistates,c_inistates,elapsed);

% Transducer to collect data.
% This is a discrete atomic.
inistates = struct('sigma',inf,'num_trucks',0,'num_pallets',0);
transducer = am_truck_transducer('transducer',inistates,elapsed);

% Hybrid coupled model root_model
y_root = {};
x_root = {};
root_model = hybridcoupled('root_model',x_root,y_root);
addcomponents(root_model,{t_gen,queue,dock,undock,truck,tank,canner,transducer});
Zid_model = {'t_gen','p1','queue','in1';...         % trucks from generator to queue, message: 1
             'queue','out1','dock','p1';...         % trucks from queue to dock-process, message: 1
             'dock','out1','truck','in1';...         % trucks from docking-process to truck unload, message: 1
             'truck','out1','undock','p1';...         % trucks (empty) from unload to undocking-process, message: 1
             'truck','out2','canner','in1';...         % signal, that new truck arrived to canner, message: 1
             'undock','out1','transducer','p1';...  % trucks from undocking-process to transducer, message: 1
             'undock','out2','queue','in2';...      % signal from undocking-process to queue, ask for next truck, message: 'send_next'
             'tank','out1','truck','in2';...           % signal from tank to truck unload to suspend/restart unloading, message: 0/1 (stop/start)
             'tank','out2','canner','in2';...          % signal from tank to canner to stop canning, because tank empty, message: 0
             'canner','out1','transducer','p2'};      % pallet à 48 gallons to transducer, message: 1
set_Zid(root_model, Zid_model);

CZid_model = {'truck',2,'tank',1;...                % second continuous variable (TruckRate) of truck acts as first input for tank
              'canner',2,'tank',2};                 % second continuous variable (CannerRate) of canner acts as second input for tank
                                                    % end continuous couplings
set_CZid(root_model, CZid_model);

After Incarnation

Display and check the outermost coupled. If you like to, set the observe flag to 1, so that all discrete state variables in s are tracked automatically.

showall(root_model);
% set_observe(root_model, 1);
Check(root_model);

Because we did not connect the second port of 'dock'- server, the Check() function results in:

No problem here - it is just a warning and we did it on purpose. ;-)

Define Some Values for ODE-Plot

Continuous variables can be plotted during simulation, if desired. If you want this, define here:

global ODEPLOT
ODEPLOT = 1;

% If ODEPLOT is set, following structure needs to be definend:
plot_params = struct('OutputSel_vec',[1 3 5],...        % decide, which continuous variables are to be plotted. HERE: TruckLevel, TankLevel, CannerLevel
                     'name_strg','Hybrid Example',...   % name of the figure
                     'xlim_interv',[0 1440],...         % xlim of axes
                     'ylim_interv',[-500 6000],...      % ylim of axes
                     'xlabel_strg','time [min]',...     % label for x-axes
                     'ylabel_strg','level [gallons]',...% label for y-axes
                     'title_strg','Orange Juice Canning',...% title for plot
                     'num_legend', 3,...                    % number of variables, for which a legend is supported
                     'legend1','truck level','legend2','tank level','legend3','canner level');% legend texts

ODEPLOT = 1 results in:

Finally

Done! Now the root_coordinator can be called to simulate the model.

without plotting during simulation (ODEPLOT == 0): [root_model,tout,yout,teout,yeout,ieout]=r_c_hybrid(root_model,tstart,tend)

with plotting during simulation (ODEPLOT == 1): [root_model,tout,yout,teout,yeout,ieout]=r_c_hybrid(root_model,tstart,tend,plot_params)

To simulate scenario from SIMAN book use tstart = 0, tend = 1440. This also fits with the plot_params. ;-)

After simulation you can get some statistics and plot the results via analyse_orange_juice_canning(root_model,tstart,tend,tout,yout)

Commands to initialize, simulate, analyze the example:

>> init_orange_juice_canning;

>> [root_model,tout,yout,teout,yeout,ieout] = r_c_hybrid(root_model,0,1440,plot_params);

>> analyse_orange_juice_canning(root_model,0,1440,tout,yout);