16 files changed, 2922 insertions, 0 deletions

diff --git a/examples/hybrid/ObstacleAvoidance.R b/examples/hybrid/ObstacleAvoidance.R
new file mode 100644
index 0000000..5a94543
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.R
@@ -0,0 +1,86 @@
+#Code automatically generated with fuzzylite 6.0.
+
+library(ggplot2);
+
+engine.name = "ObstacleAvoidance"
+engine.fll = "Engine: ObstacleAvoidance
+InputVariable: obstacle
+  enabled: true
+  range: 0.000 1.000
+  lock-range: false
+  term: left Ramp 1.000 0.000
+  term: right Ramp 0.000 1.000
+OutputVariable: mSteer
+  enabled: true
+  range: 0.000 1.000
+  lock-range: false
+  aggregation: Maximum
+  defuzzifier: Centroid 100
+  default: nan
+  lock-previous: false
+  term: left Ramp 1.000 0.000
+  term: right Ramp 0.000 1.000
+OutputVariable: tsSteer
+  enabled: true
+  range: 0.000 1.000
+  lock-range: false
+  aggregation: Maximum
+  defuzzifier: WeightedAverage Automatic
+  default: nan
+  lock-previous: false
+  term: left Constant 0.333
+  term: right Constant 0.666
+RuleBlock: mamdani
+  enabled: true
+  conjunction: none
+  disjunction: none
+  implication: AlgebraicProduct
+  activation: General
+  rule: if obstacle is left then mSteer is right
+  rule: if obstacle is right then mSteer is left
+RuleBlock: takagiSugeno
+  enabled: true
+  conjunction: none
+  disjunction: none
+  implication: none
+  activation: General
+  rule: if obstacle is left then tsSteer is right
+  rule: if obstacle is right then tsSteer is left"
+
+engine.fldFile = "ObstacleAvoidance.fld"
+if (require(data.table)) {
+    engine.df = data.table::fread(engine.fldFile, sep="auto", header="auto")
+} else {
+    engine.df = read.table(engine.fldFile, header=TRUE)
+}
+
+engine.plot.i1_o1 = ggplot(engine.df, aes(obstacle, mSteer)) + 
+    geom_line(aes(color=mSteer), size=3, lineend="round", linejoin="mitre") + 
+    scale_color_gradient(low="yellow", high="red") + 
+    ggtitle("obstacle vs mSteer")
+
+engine.plot.o1_i1 = ggplot(engine.df, aes(obstacle, mSteer)) + 
+    geom_line(aes(color=mSteer), size=3, lineend="round", linejoin="mitre") + 
+    scale_color_gradient(low="yellow", high="red") + 
+    coord_flip() + 
+    ggtitle("mSteer vs obstacle")
+
+engine.plot.i1_o2 = ggplot(engine.df, aes(obstacle, tsSteer)) + 
+    geom_line(aes(color=tsSteer), size=3, lineend="round", linejoin="mitre") + 
+    scale_color_gradient(low="yellow", high="red") + 
+    ggtitle("obstacle vs tsSteer")
+
+engine.plot.o2_i1 = ggplot(engine.df, aes(obstacle, tsSteer)) + 
+    geom_line(aes(color=tsSteer), size=3, lineend="round", linejoin="mitre") + 
+    scale_color_gradient(low="yellow", high="red") + 
+    coord_flip() + 
+    ggtitle("tsSteer vs obstacle")
+
+if (require(gridExtra)) {
+    engine.plots = arrangeGrob(engine.plot.i1_o1, engine.plot.o1_i1, engine.plot.i1_o2, engine.plot.o2_i1, ncol=2, top=engine.name)
+    ggsave(paste0(engine.name, ".pdf"), engine.plots)
+    if (require(grid)) {
+        grid.newpage()
+        grid.draw(engine.plots)
+    }
+}
diff --git a/examples/hybrid/ObstacleAvoidance.cpp b/examples/hybrid/ObstacleAvoidance.cpp
new file mode 100644
index 0000000..a5e42e1
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.cpp
@@ -0,0 +1,75 @@
+#include <fl/Headers.h>
+
+int main(int argc, char** argv){
+//Code automatically generated with fuzzylite 6.0.
+
+using namespace fl;
+
+Engine* engine = new Engine;
+engine->setName("ObstacleAvoidance");
+engine->setDescription("");
+
+InputVariable* obstacle = new InputVariable;
+obstacle->setName("obstacle");
+obstacle->setDescription("");
+obstacle->setEnabled(true);
+obstacle->setRange(0.000, 1.000);
+obstacle->setLockValueInRange(false);
+obstacle->addTerm(new Ramp("left", 1.000, 0.000));
+obstacle->addTerm(new Ramp("right", 0.000, 1.000));
+engine->addInputVariable(obstacle);
+
+OutputVariable* mSteer = new OutputVariable;
+mSteer->setName("mSteer");
+mSteer->setDescription("");
+mSteer->setEnabled(true);
+mSteer->setRange(0.000, 1.000);
+mSteer->setLockValueInRange(false);
+mSteer->setAggregation(new Maximum);
+mSteer->setDefuzzifier(new Centroid(100));
+mSteer->setDefaultValue(fl::nan);
+mSteer->setLockPreviousValue(false);
+mSteer->addTerm(new Ramp("left", 1.000, 0.000));
+mSteer->addTerm(new Ramp("right", 0.000, 1.000));
+engine->addOutputVariable(mSteer);
+
+OutputVariable* tsSteer = new OutputVariable;
+tsSteer->setName("tsSteer");
+tsSteer->setDescription("");
+tsSteer->setEnabled(true);
+tsSteer->setRange(0.000, 1.000);
+tsSteer->setLockValueInRange(false);
+tsSteer->setAggregation(new Maximum);
+tsSteer->setDefuzzifier(new WeightedAverage("Automatic"));
+tsSteer->setDefaultValue(fl::nan);
+tsSteer->setLockPreviousValue(false);
+tsSteer->addTerm(new Constant("left", 0.333));
+tsSteer->addTerm(new Constant("right", 0.666));
+engine->addOutputVariable(tsSteer);
+
+RuleBlock* mamdani = new RuleBlock;
+mamdani->setName("mamdani");
+mamdani->setDescription("");
+mamdani->setEnabled(true);
+mamdani->setConjunction(fl::null);
+mamdani->setDisjunction(fl::null);
+mamdani->setImplication(new AlgebraicProduct);
+mamdani->setActivation(new General);
+mamdani->addRule(Rule::parse("if obstacle is left then mSteer is right", engine));
+mamdani->addRule(Rule::parse("if obstacle is right then mSteer is left", engine));
+engine->addRuleBlock(mamdani);
+
+RuleBlock* takagiSugeno = new RuleBlock;
+takagiSugeno->setName("takagiSugeno");
+takagiSugeno->setDescription("");
+takagiSugeno->setEnabled(true);
+takagiSugeno->setConjunction(fl::null);
+takagiSugeno->setDisjunction(fl::null);
+takagiSugeno->setImplication(fl::null);
+takagiSugeno->setActivation(new General);
+takagiSugeno->addRule(Rule::parse("if obstacle is left then tsSteer is right", engine));
+takagiSugeno->addRule(Rule::parse("if obstacle is right then tsSteer is left", engine));
+engine->addRuleBlock(takagiSugeno);
+
+
+}
diff --git a/examples/hybrid/ObstacleAvoidance.fcl b/examples/hybrid/ObstacleAvoidance.fcl
new file mode 100644
index 0000000..81a30a7
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.fcl
@@ -0,0 +1,49 @@
+//Code automatically generated with fuzzylite 6.0.
+
+FUNCTION_BLOCK ObstacleAvoidance
+
+VAR_INPUT
+  obstacle: REAL;
+END_VAR
+
+VAR_OUTPUT
+  mSteer: REAL;
+  tsSteer: REAL;
+END_VAR
+
+FUZZIFY obstacle
+  RANGE := (0.000 .. 1.000);
+  TERM left := Ramp 1.000 0.000;
+  TERM right := Ramp 0.000 1.000;
+END_FUZZIFY
+
+DEFUZZIFY mSteer
+  RANGE := (0.000 .. 1.000);
+  TERM left := Ramp 1.000 0.000;
+  TERM right := Ramp 0.000 1.000;
+  METHOD : COG;
+  ACCU : MAX;
+  DEFAULT := nan;
+END_DEFUZZIFY
+
+DEFUZZIFY tsSteer
+  RANGE := (0.000 .. 1.000);
+  TERM left := 0.333;
+  TERM right := 0.666;
+  METHOD : COGS;
+  ACCU : MAX;
+  DEFAULT := nan;
+END_DEFUZZIFY
+
+RULEBLOCK mamdani
+  ACT : PROD;
+  RULE 1 : if obstacle is left then mSteer is right
+  RULE 2 : if obstacle is right then mSteer is left
+END_RULEBLOCK
+
+RULEBLOCK takagiSugeno
+  RULE 1 : if obstacle is left then tsSteer is right
+  RULE 2 : if obstacle is right then tsSteer is left
+END_RULEBLOCK
+
+END_FUNCTION_BLOCK
diff --git a/examples/hybrid/ObstacleAvoidance.fis b/examples/hybrid/ObstacleAvoidance.fis
new file mode 100644
index 0000000..1bf0476
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.fis
@@ -0,0 +1,43 @@
+#Code automatically generated with fuzzylite 6.0.
+
+[System]
+Name='ObstacleAvoidance'
+Type='hybrid'
+Version=6.0
+NumInputs=1
+NumOutputs=2
+NumRules=4
+AndMethod='min'
+OrMethod='max'
+ImpMethod='prod'
+AggMethod='max'
+DefuzzMethod='centroid'
+
+[Input1]
+Name='obstacle'
+Range=[0.000 1.000]
+NumMFs=2
+MF1='left':'rampmf',[1.000 0.000]
+MF2='right':'rampmf',[0.000 1.000]
+
+[Output1]
+Name='mSteer'
+Range=[0.000 1.000]
+NumMFs=2
+MF1='left':'rampmf',[1.000 0.000]
+MF2='right':'rampmf',[0.000 1.000]
+
+[Output2]
+Name='tsSteer'
+Range=[0.000 1.000]
+NumMFs=2
+MF1='left':'constant',[0.333]
+MF2='right':'constant',[0.666]
+
+[Rules]
+# RuleBlock mamdani
+1.000 , 2.000 0.000 (1.000) : 1
+2.000 , 1.000 0.000 (1.000) : 1
+# RuleBlock takagiSugeno
+1.000 , 0.000 2.000 (1.000) : 1
+2.000 , 0.000 1.000 (1.000) : 1
diff --git a/examples/hybrid/ObstacleAvoidance.fld b/examples/hybrid/ObstacleAvoidance.fld
new file mode 100644
index 0000000..bd96696
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.fld
@@ -0,0 +1,1025 @@
+obstacle mSteer tsSteer
+0.000000000 0.666650000 0.666000000
+0.000977517 0.666650000 0.665674487
+0.001955034 0.666650000 0.665348974
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+0.990224829 0.333413807 0.336255132
+0.991202346 0.333400697 0.335929619
+0.992179863 0.333387611 0.335604106
+0.993157380 0.333374550 0.335278592
+0.994134897 0.333361515 0.334953079
+0.995112414 0.333350000 0.334627566
+0.996089932 0.333350000 0.334302053
+0.997067449 0.333350000 0.333976540
+0.998044966 0.333350000 0.333651026
+0.999022483 0.333350000 0.333325513
+1.000000000 0.333350000 0.333000000
diff --git a/examples/hybrid/ObstacleAvoidance.fll b/examples/hybrid/ObstacleAvoidance.fll
new file mode 100644
index 0000000..970221b
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.fll
@@ -0,0 +1,43 @@
+Engine: ObstacleAvoidance
+InputVariable: obstacle
+  enabled: true
+  range: 0.000 1.000
+  lock-range: false
+  term: left Ramp 1.000 0.000
+  term: right Ramp 0.000 1.000
+OutputVariable: mSteer
+  enabled: true
+  range: 0.000 1.000
+  lock-range: false
+  aggregation: Maximum
+  defuzzifier: Centroid 100
+  default: nan
+  lock-previous: false
+  term: left Ramp 1.000 0.000
+  term: right Ramp 0.000 1.000
+OutputVariable: tsSteer
+  enabled: true
+  range: 0.000 1.000
+  lock-range: false
+  aggregation: Maximum
+  defuzzifier: WeightedAverage Automatic
+  default: nan
+  lock-previous: false
+  term: left Constant 0.333
+  term: right Constant 0.666
+RuleBlock: mamdani
+  enabled: true
+  conjunction: none
+  disjunction: none
+  implication: AlgebraicProduct
+  activation: General
+  rule: if obstacle is left then mSteer is right
+  rule: if obstacle is right then mSteer is left
+RuleBlock: takagiSugeno
+  enabled: true
+  conjunction: none
+  disjunction: none
+  implication: none
+  activation: General
+  rule: if obstacle is left then tsSteer is right
+  rule: if obstacle is right then tsSteer is left
\ No newline at end of file
diff --git a/examples/hybrid/ObstacleAvoidance.java b/examples/hybrid/ObstacleAvoidance.java
new file mode 100644
index 0000000..8196670
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.java
@@ -0,0 +1,86 @@
+import com.fuzzylite.*;
+import com.fuzzylite.activation.*
+import com.fuzzylite.defuzzifier.*;
+import com.fuzzylite.factory.*;
+import com.fuzzylite.hedge.*;
+import com.fuzzylite.imex.*;
+import com.fuzzylite.norm.*;
+import com.fuzzylite.norm.s.*;
+import com.fuzzylite.norm.t.*;
+import com.fuzzylite.rule.*;
+import com.fuzzylite.term.*;
+import com.fuzzylite.variable.*;
+
+public class ObstacleAvoidance{
+public static void main(String[] args){
+//Code automatically generated with fuzzylite 6.0.
+
+Engine engine = new Engine();
+engine.setName("ObstacleAvoidance");
+engine.setDescription("");
+
+InputVariable obstacle = new InputVariable();
+obstacle.setName("obstacle");
+obstacle.setDescription("");
+obstacle.setEnabled(true);
+obstacle.setRange(0.000, 1.000);
+obstacle.setLockValueInRange(false);
+obstacle.addTerm(new Ramp("left", 1.000, 0.000));
+obstacle.addTerm(new Ramp("right", 0.000, 1.000));
+engine.addInputVariable(obstacle);
+
+OutputVariable mSteer = new OutputVariable();
+mSteer.setName("mSteer");
+mSteer.setDescription("");
+mSteer.setEnabled(true);
+mSteer.setRange(0.000, 1.000);
+mSteer.setLockValueInRange(false);
+mSteer.setAggregation(new Maximum());
+mSteer.setDefuzzifier(new Centroid(100));
+mSteer.setDefaultValue(Double.NaN);
+mSteer.setLockPreviousValue(false);
+mSteer.addTerm(new Ramp("left", 1.000, 0.000));
+mSteer.addTerm(new Ramp("right", 0.000, 1.000));
+engine.addOutputVariable(mSteer);
+
+OutputVariable tsSteer = new OutputVariable();
+tsSteer.setName("tsSteer");
+tsSteer.setDescription("");
+tsSteer.setEnabled(true);
+tsSteer.setRange(0.000, 1.000);
+tsSteer.setLockValueInRange(false);
+tsSteer.setAggregation(new Maximum());
+tsSteer.setDefuzzifier(new WeightedAverage("Automatic"));
+tsSteer.setDefaultValue(Double.NaN);
+tsSteer.setLockPreviousValue(false);
+tsSteer.addTerm(new Constant("left", 0.333));
+tsSteer.addTerm(new Constant("right", 0.666));
+engine.addOutputVariable(tsSteer);
+
+RuleBlock mamdani = new RuleBlock();
+mamdani.setName("mamdani");
+mamdani.setDescription("");
+mamdani.setEnabled(true);
+mamdani.setConjunction(null);
+mamdani.setDisjunction(null);
+mamdani.setImplication(new AlgebraicProduct());
+mamdani.setActivation(new General());
+mamdani.addRule(Rule.parse("if obstacle is left then mSteer is right", engine));
+mamdani.addRule(Rule.parse("if obstacle is right then mSteer is left", engine));
+engine.addRuleBlock(mamdani);
+
+RuleBlock takagiSugeno = new RuleBlock();
+takagiSugeno.setName("takagiSugeno");
+takagiSugeno.setDescription("");
+takagiSugeno.setEnabled(true);
+takagiSugeno.setConjunction(null);
+takagiSugeno.setDisjunction(null);
+takagiSugeno.setImplication(null);
+takagiSugeno.setActivation(new General());
+takagiSugeno.addRule(Rule.parse("if obstacle is left then tsSteer is right", engine));
+takagiSugeno.addRule(Rule.parse("if obstacle is right then tsSteer is left", engine));
+engine.addRuleBlock(takagiSugeno);
+
+
+}
+}
diff --git a/examples/hybrid/ObstacleAvoidance.pdf b/examples/hybrid/ObstacleAvoidance.pdf
new file mode 100644
index 0000000..ad74e68
--- /dev/null
+++ b/examples/hybrid/ObstacleAvoidance.pdf
diff --git a/examples/hybrid/tipper.R b/examples/hybrid/tipper.R
new file mode 100644
index 0000000..ba11351
--- /dev/null
+++ b/examples/hybrid/tipper.R
@@ -0,0 +1,109 @@
+#Code automatically generated with fuzzylite 6.0.
+
+library(ggplot2);
+
+engine.name = "tipper"
+engine.description = "(service and food) -> (tip)"
+engine.fll = "Engine: tipper
+description: (service and food) -> (tip)
+InputVariable: service
+  description: quality of service
+  enabled: true
+  range: 0.000 10.000
+  lock-range: true
+  term: poor Trapezoid 0.000 0.000 2.500 5.000
+  term: good Triangle 2.500 5.000 7.500
+  term: excellent Trapezoid 5.000 7.500 10.000 10.000
+InputVariable: food
+  description: quality of food
+  enabled: true
+  range: 0.000 10.000
+  lock-range: true
+  term: rancid Trapezoid 0.000 0.000 2.500 7.500
+  term: delicious Trapezoid 2.500 7.500 10.000 10.000
+OutputVariable: mTip
+  description: tip based on Mamdani inference
+  enabled: true
+  range: 0.000 30.000
+  lock-range: false
+  aggregation: Maximum
+  defuzzifier: Centroid 100
+  default: nan
+  lock-previous: false
+  term: cheap Triangle 0.000 5.000 10.000
+  term: average Triangle 10.000 15.000 20.000
+  term: generous Triangle 20.000 25.000 30.000
+OutputVariable: tsTip
+  description: tip based on Takagi-Sugeno inference
+  enabled: true
+  range: 0.000 30.000
+  lock-range: false
+  aggregation: none
+  defuzzifier: WeightedAverage TakagiSugeno
+  default: nan
+  lock-previous: false
+  term: cheap Constant 5.000
+  term: average Constant 15.000
+  term: generous Constant 25.000
+RuleBlock: mamdani
+  description: Mamdani inference
+  enabled: true
+  conjunction: AlgebraicProduct
+  disjunction: AlgebraicSum
+  implication: Minimum
+  activation: General
+  rule: if service is poor or food is rancid then mTip is cheap
+  rule: if service is good then mTip is average
+  rule: if service is excellent or food is delicious then mTip is generous with 0.5
+  rule: if service is excellent and food is delicious then mTip is generous with 1.0
+RuleBlock: takagiSugeno
+  description: Takagi-Sugeno inference
+  enabled: true
+  conjunction: AlgebraicProduct
+  disjunction: AlgebraicSum
+  implication: none
+  activation: General
+  rule: if service is poor or food is rancid then tsTip is cheap
+  rule: if service is good then tsTip is average
+  rule: if service is excellent or food is delicious then tsTip is generous with 0.5
+  rule: if service is excellent and food is delicious then tsTip is generous with 1.0"
+
+engine.fldFile = "tipper.fld"
+if (require(data.table)) {
+    engine.df = data.table::fread(engine.fldFile, sep="auto", header="auto")
+} else {
+    engine.df = read.table(engine.fldFile, header=TRUE)
+}
+
+engine.plot.i1i2_o1 = ggplot(engine.df, aes(service, food)) + 
+    geom_tile(aes(fill=mTip)) + 
+    scale_fill_gradient(low="yellow", high="red") + 
+    stat_contour(aes(x=service, y=food, z=mTip), color="black") + 
+    ggtitle("(service, food) = mTip")
+
+engine.plot.i2i1_o1 = ggplot(engine.df, aes(food, service)) + 
+    geom_tile(aes(fill=mTip)) + 
+    scale_fill_gradient(low="yellow", high="red") + 
+    stat_contour(aes(x=food, y=service, z=mTip), color="black") + 
+    ggtitle("(food, service) = mTip")
+
+engine.plot.i1i2_o2 = ggplot(engine.df, aes(service, food)) + 
+    geom_tile(aes(fill=tsTip)) + 
+    scale_fill_gradient(low="yellow", high="red") + 
+    stat_contour(aes(x=service, y=food, z=tsTip), color="black") + 
+    ggtitle("(service, food) = tsTip")
+
+engine.plot.i2i1_o2 = ggplot(engine.df, aes(food, service)) + 
+    geom_tile(aes(fill=tsTip)) + 
+    scale_fill_gradient(low="yellow", high="red") + 
+    stat_contour(aes(x=food, y=service, z=tsTip), color="black") + 
+    ggtitle("(food, service) = tsTip")
+
+if (require(gridExtra)) {
+    engine.plots = arrangeGrob(engine.plot.i1i2_o1, engine.plot.i2i1_o1, engine.plot.i1i2_o2, engine.plot.i2i1_o2, ncol=2, top=engine.name)
+    ggsave(paste0(engine.name, ".pdf"), engine.plots)
+    if (require(grid)) {
+        grid.newpage()
+        grid.draw(engine.plots)
+    }
+}
diff --git a/examples/hybrid/tipper.cpp b/examples/hybrid/tipper.cpp
new file mode 100644
index 0000000..57bcc78
--- /dev/null
+++ b/examples/hybrid/tipper.cpp
@@ -0,0 +1,92 @@
+#include <fl/Headers.h>
+
+int main(int argc, char** argv){
+//Code automatically generated with fuzzylite 6.0.
+
+using namespace fl;
+
+Engine* engine = new Engine;
+engine->setName("tipper");
+engine->setDescription("(service and food) -> (tip)");
+
+InputVariable* service = new InputVariable;
+service->setName("service");
+service->setDescription("quality of service");
+service->setEnabled(true);
+service->setRange(0.000, 10.000);
+service->setLockValueInRange(true);
+service->addTerm(new Trapezoid("poor", 0.000, 0.000, 2.500, 5.000));
+service->addTerm(new Triangle("good", 2.500, 5.000, 7.500));
+service->addTerm(new Trapezoid("excellent", 5.000, 7.500, 10.000, 10.000));
+engine->addInputVariable(service);
+
+InputVariable* food = new InputVariable;
+food->setName("food");
+food->setDescription("quality of food");
+food->setEnabled(true);
+food->setRange(0.000, 10.000);
+food->setLockValueInRange(true);
+food->addTerm(new Trapezoid("rancid", 0.000, 0.000, 2.500, 7.500));
+food->addTerm(new Trapezoid("delicious", 2.500, 7.500, 10.000, 10.000));
+engine->addInputVariable(food);
+
+OutputVariable* mTip = new OutputVariable;
+mTip->setName("mTip");
+mTip->setDescription("tip based on Mamdani inference");
+mTip->setEnabled(true);
+mTip->setRange(0.000, 30.000);
+mTip->setLockValueInRange(false);
+mTip->setAggregation(new Maximum);
+mTip->setDefuzzifier(new Centroid(100));
+mTip->setDefaultValue(fl::nan);
+mTip->setLockPreviousValue(false);
+mTip->addTerm(new Triangle("cheap", 0.000, 5.000, 10.000));
+mTip->addTerm(new Triangle("average", 10.000, 15.000, 20.000));
+mTip->addTerm(new Triangle("generous", 20.000, 25.000, 30.000));
+engine->addOutputVariable(mTip);
+
+OutputVariable* tsTip = new OutputVariable;
+tsTip->setName("tsTip");
+tsTip->setDescription("tip based on Takagi-Sugeno inference");
+tsTip->setEnabled(true);
+tsTip->setRange(0.000, 30.000);
+tsTip->setLockValueInRange(false);
+tsTip->setAggregation(fl::null);
+tsTip->setDefuzzifier(new WeightedAverage("TakagiSugeno"));
+tsTip->setDefaultValue(fl::nan);
+tsTip->setLockPreviousValue(false);
+tsTip->addTerm(new Constant("cheap", 5.000));
+tsTip->addTerm(new Constant("average", 15.000));
+tsTip->addTerm(new Constant("generous", 25.000));
+engine->addOutputVariable(tsTip);
+
+RuleBlock* mamdani = new RuleBlock;
+mamdani->setName("mamdani");
+mamdani->setDescription("Mamdani inference");
+mamdani->setEnabled(true);
+mamdani->setConjunction(new AlgebraicProduct);
+mamdani->setDisjunction(new AlgebraicSum);
+mamdani->setImplication(new Minimum);
+mamdani->setActivation(new General);
+mamdani->addRule(Rule::parse("if service is poor or food is rancid then mTip is cheap", engine));
+mamdani->addRule(Rule::parse("if service is good then mTip is average", engine));
+mamdani->addRule(Rule::parse("if service is excellent or food is delicious then mTip is generous with 0.5", engine));
+mamdani->addRule(Rule::parse("if service is excellent and food is delicious then mTip is generous with 1.0", engine));
+engine->addRuleBlock(mamdani);
+
+RuleBlock* takagiSugeno = new RuleBlock;
+takagiSugeno->setName("takagiSugeno");
+takagiSugeno->setDescription("Takagi-Sugeno inference");
+takagiSugeno->setEnabled(true);
+takagiSugeno->setConjunction(new AlgebraicProduct);
+takagiSugeno->setDisjunction(new AlgebraicSum);
+takagiSugeno->setImplication(fl::null);
+takagiSugeno->setActivation(new General);
+takagiSugeno->addRule(Rule::parse("if service is poor or food is rancid then tsTip is cheap", engine));
+takagiSugeno->addRule(Rule::parse("if service is good then tsTip is average", engine));
+takagiSugeno->addRule(Rule::parse("if service is excellent or food is delicious then tsTip is generous with 0.5", engine));
+takagiSugeno->addRule(Rule::parse("if service is excellent and food is delicious then tsTip is generous with 1.0", engine));
+engine->addRuleBlock(takagiSugeno);
+
+
+}
diff --git a/examples/hybrid/tipper.fcl b/examples/hybrid/tipper.fcl
new file mode 100644
index 0000000..299dbb8
--- /dev/null
+++ b/examples/hybrid/tipper.fcl
@@ -0,0 +1,66 @@
+//Code automatically generated with fuzzylite 6.0.
+
+FUNCTION_BLOCK tipper
+
+VAR_INPUT
+  service: REAL;
+  food: REAL;
+END_VAR
+
+VAR_OUTPUT
+  mTip: REAL;
+  tsTip: REAL;
+END_VAR
+
+FUZZIFY service
+  RANGE := (0.000 .. 10.000);
+  TERM poor := Trapezoid 0.000 0.000 2.500 5.000;
+  TERM good := Triangle 2.500 5.000 7.500;
+  TERM excellent := Trapezoid 5.000 7.500 10.000 10.000;
+END_FUZZIFY
+
+FUZZIFY food
+  RANGE := (0.000 .. 10.000);
+  TERM rancid := Trapezoid 0.000 0.000 2.500 7.500;
+  TERM delicious := Trapezoid 2.500 7.500 10.000 10.000;
+END_FUZZIFY
+
+DEFUZZIFY mTip
+  RANGE := (0.000 .. 30.000);
+  TERM cheap := Triangle 0.000 5.000 10.000;
+  TERM average := Triangle 10.000 15.000 20.000;
+  TERM generous := Triangle 20.000 25.000 30.000;
+  METHOD : COG;
+  ACCU : MAX;
+  DEFAULT := nan;
+END_DEFUZZIFY
+
+DEFUZZIFY tsTip
+  RANGE := (0.000 .. 30.000);
+  TERM cheap := 5.000;
+  TERM average := 15.000;
+  TERM generous := 25.000;
+  METHOD : COGS;
+  DEFAULT := nan;
+END_DEFUZZIFY
+
+RULEBLOCK mamdani
+  AND : PROD;
+  OR : ASUM;
+  ACT : MIN;
+  RULE 1 : if service is poor or food is rancid then mTip is cheap
+  RULE 2 : if service is good then mTip is average
+  RULE 3 : if service is excellent or food is delicious then mTip is generous with 0.5
+  RULE 4 : if service is excellent and food is delicious then mTip is generous with 1.0
+END_RULEBLOCK
+
+RULEBLOCK takagiSugeno
+  AND : PROD;
+  OR : ASUM;
+  RULE 1 : if service is poor or food is rancid then tsTip is cheap
+  RULE 2 : if service is good then tsTip is average
+  RULE 3 : if service is excellent or food is delicious then tsTip is generous with 0.5
+  RULE 4 : if service is excellent and food is delicious then tsTip is generous with 1.0
+END_RULEBLOCK
+
+END_FUNCTION_BLOCK
diff --git a/examples/hybrid/tipper.fis b/examples/hybrid/tipper.fis
new file mode 100644
index 0000000..abd850a
--- /dev/null
+++ b/examples/hybrid/tipper.fis
@@ -0,0 +1,57 @@
+#Code automatically generated with fuzzylite 6.0.
+
+[System]
+Name='tipper'
+Type='hybrid'
+Version=6.0
+NumInputs=2
+NumOutputs=2
+NumRules=8
+AndMethod='prod'
+OrMethod='probor'
+ImpMethod='min'
+AggMethod='max'
+DefuzzMethod='centroid'
+
+[Input1]
+Name='service'
+Range=[0.000 10.000]
+NumMFs=3
+MF1='poor':'trapmf',[0.000 0.000 2.500 5.000]
+MF2='good':'trimf',[2.500 5.000 7.500]
+MF3='excellent':'trapmf',[5.000 7.500 10.000 10.000]
+
+[Input2]
+Name='food'
+Range=[0.000 10.000]
+NumMFs=2
+MF1='rancid':'trapmf',[0.000 0.000 2.500 7.500]
+MF2='delicious':'trapmf',[2.500 7.500 10.000 10.000]
+
+[Output1]
+Name='mTip'
+Range=[0.000 30.000]
+NumMFs=3
+MF1='cheap':'trimf',[0.000 5.000 10.000]
+MF2='average':'trimf',[10.000 15.000 20.000]
+MF3='generous':'trimf',[20.000 25.000 30.000]
+
+[Output2]
+Name='tsTip'
+Range=[0.000 30.000]
+NumMFs=3
+MF1='cheap':'constant',[5.000]
+MF2='average':'constant',[15.000]
+MF3='generous':'constant',[25.000]
+
+[Rules]
+# RuleBlock mamdani
+1.000 1.000 , 1.000 0.000 (1.000) : 2
+2.000 0.000 , 2.000 0.000 (1.000) : 1
+3.000 2.000 , 3.000 0.000 (0.500) : 2
+3.000 2.000 , 3.000 0.000 (1.000) : 1
+# RuleBlock takagiSugeno
+1.000 1.000 , 0.000 1.000 (1.000) : 2
+2.000 0.000 , 0.000 2.000 (1.000) : 1
+3.000 2.000 , 0.000 3.000 (0.500) : 2
+3.000 2.000 , 0.000 3.000 (1.000) : 1
diff --git a/examples/hybrid/tipper.fld b/examples/hybrid/tipper.fld
new file mode 100644
index 0000000..7a8e29d
--- /dev/null
+++ b/examples/hybrid/tipper.fld
@@ -0,0 +1,1025 @@
+service food mTip tsTip
+0.000000000 0.000000000 4.998950210 5.000000000
+0.000000000 0.322580645 4.998950210 5.000000000
+0.000000000 0.645161290 4.998950210 5.000000000
+0.000000000 0.967741935 4.998950210 5.000000000
+0.000000000 1.290322581 4.998950210 5.000000000
+0.000000000 1.612903226 4.998950210 5.000000000
+0.000000000 1.935483871 4.998950210 5.000000000
+0.000000000 2.258064516 4.998950210 5.000000000
+0.000000000 2.580645161 5.314026132 5.160000000
+0.000000000 2.903225806 6.467756859 5.775193798
+0.000000000 3.225806452 7.452789474 6.353383459
+0.000000000 3.548387097 8.316896407 6.897810219
+0.000000000 3.870967742 9.067963620 7.411347518
+0.000000000 4.193548387 9.734585733 7.896551724
+0.000000000 4.516129032 10.322182298 8.355704698
+0.000000000 4.838709677 10.846060307 8.790849673
+0.000000000 5.161290323 11.316227524 9.203821656
+0.000000000 5.483870968 11.733949841 9.596273292
+0.000000000 5.806451613 12.115369655 9.969696970
+0.000000000 6.129032258 12.452152483 10.325443787
+0.000000000 6.451612903 12.762450565 10.664739884
+0.000000000 6.774193548 13.037607639 10.988700565
+0.000000000 7.096774194 13.291172539 11.298342541
+0.000000000 7.419354839 13.516499633 11.594594595
+0.000000000 7.741935484 13.570706205 11.666666667
+0.000000000 8.064516129 13.570706205 11.666666667
+0.000000000 8.387096774 13.570706205 11.666666667
+0.000000000 8.709677419 13.570706205 11.666666667
+0.000000000 9.032258065 13.570706205 11.666666667
+0.000000000 9.354838710 13.570706205 11.666666667
+0.000000000 9.677419355 13.570706205 11.666666667
+0.000000000 10.000000000 13.570706205 11.666666667
+0.322580645 0.000000000 4.998950210 5.000000000
+0.322580645 0.322580645 4.998950210 5.000000000
+0.322580645 0.645161290 4.998950210 5.000000000
+0.322580645 0.967741935 4.998950210 5.000000000
+0.322580645 1.290322581 4.998950210 5.000000000
+0.322580645 1.612903226 4.998950210 5.000000000
+0.322580645 1.935483871 4.998950210 5.000000000
+0.322580645 2.258064516 4.998950210 5.000000000
+0.322580645 2.580645161 5.314026132 5.160000000
+0.322580645 2.903225806 6.467756859 5.775193798
+0.322580645 3.225806452 7.452789474 6.353383459
+0.322580645 3.548387097 8.316896407 6.897810219
+0.322580645 3.870967742 9.067963620 7.411347518
+0.322580645 4.193548387 9.734585733 7.896551724
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+10.000000000 0.645161290 13.570706205 11.666666667
+10.000000000 0.967741935 13.570706205 11.666666667
+10.000000000 1.290322581 13.570706205 11.666666667
+10.000000000 1.612903226 13.570706205 11.666666667
+10.000000000 1.935483871 13.570706205 11.666666667
+10.000000000 2.258064516 13.570706205 11.666666667
+10.000000000 2.580645161 13.572517919 11.881720430
+10.000000000 2.903225806 13.603707815 12.741935484
+10.000000000 3.225806452 13.676532623 13.602150538
+10.000000000 3.548387097 13.793124575 14.462365591
+10.000000000 3.870967742 13.957010447 15.322580645
+10.000000000 4.193548387 14.173387937 16.182795699
+10.000000000 4.516129032 14.449561083 17.043010753
+10.000000000 4.838709677 14.795606896 17.903225806
+10.000000000 5.161290323 15.430252399 18.763440860
+10.000000000 5.483870968 16.305345082 19.623655914
+10.000000000 5.806451613 17.225621817 20.483870968
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+10.000000000 7.419354839 24.380408194 24.784946237
+10.000000000 7.741935484 25.001049790 25.000000000
+10.000000000 8.064516129 25.001049790 25.000000000
+10.000000000 8.387096774 25.001049790 25.000000000
+10.000000000 8.709677419 25.001049790 25.000000000
+10.000000000 9.032258065 25.001049790 25.000000000
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+10.000000000 9.677419355 25.001049790 25.000000000
+10.000000000 10.000000000 25.001049790 25.000000000
diff --git a/examples/hybrid/tipper.fll b/examples/hybrid/tipper.fll
new file mode 100644
index 0000000..cb8803f
--- /dev/null
+++ b/examples/hybrid/tipper.fll
@@ -0,0 +1,63 @@
+Engine: tipper
+description: (service and food) -> (tip)
+InputVariable: service
+  description: quality of service
+  enabled: true
+  range: 0.000 10.000
+  lock-range: true
+  term: poor Trapezoid 0.000 0.000 2.500 5.000
+  term: good Triangle 2.500 5.000 7.500
+  term: excellent Trapezoid 5.000 7.500 10.000 10.000
+InputVariable: food
+  description: quality of food
+  enabled: true
+  range: 0.000 10.000
+  lock-range: true
+  term: rancid Trapezoid 0.000 0.000 2.500 7.500
+  term: delicious Trapezoid 2.500 7.500 10.000 10.000
+OutputVariable: mTip
+  description: tip based on Mamdani inference
+  enabled: true
+  range: 0.000 30.000
+  lock-range: false
+  aggregation: Maximum
+  defuzzifier: Centroid 100
+  default: nan
+  lock-previous: false
+  term: cheap Triangle 0.000 5.000 10.000
+  term: average Triangle 10.000 15.000 20.000
+  term: generous Triangle 20.000 25.000 30.000
+OutputVariable: tsTip
+  description: tip based on Takagi-Sugeno inference
+  enabled: true
+  range: 0.000 30.000
+  lock-range: false
+  aggregation: none
+  defuzzifier: WeightedAverage TakagiSugeno
+  default: nan
+  lock-previous: false
+  term: cheap Constant 5.000
+  term: average Constant 15.000
+  term: generous Constant 25.000
+RuleBlock: mamdani
+  description: Mamdani inference
+  enabled: true
+  conjunction: AlgebraicProduct
+  disjunction: AlgebraicSum
+  implication: Minimum
+  activation: General
+  rule: if service is poor or food is rancid then mTip is cheap
+  rule: if service is good then mTip is average
+  rule: if service is excellent or food is delicious then mTip is generous with 0.5
+  rule: if service is excellent and food is delicious then mTip is generous with 1.0
+RuleBlock: takagiSugeno
+  description: Takagi-Sugeno inference
+  enabled: true
+  conjunction: AlgebraicProduct
+  disjunction: AlgebraicSum
+  implication: none
+  activation: General
+  rule: if service is poor or food is rancid then tsTip is cheap
+  rule: if service is good then tsTip is average
+  rule: if service is excellent or food is delicious then tsTip is generous with 0.5
+  rule: if service is excellent and food is delicious then tsTip is generous with 1.0
\ No newline at end of file
diff --git a/examples/hybrid/tipper.java b/examples/hybrid/tipper.java
new file mode 100644
index 0000000..e0578ca
--- /dev/null
+++ b/examples/hybrid/tipper.java
@@ -0,0 +1,103 @@
+import com.fuzzylite.*;
+import com.fuzzylite.activation.*
+import com.fuzzylite.defuzzifier.*;
+import com.fuzzylite.factory.*;
+import com.fuzzylite.hedge.*;
+import com.fuzzylite.imex.*;
+import com.fuzzylite.norm.*;
+import com.fuzzylite.norm.s.*;
+import com.fuzzylite.norm.t.*;
+import com.fuzzylite.rule.*;
+import com.fuzzylite.term.*;
+import com.fuzzylite.variable.*;
+
+public class tipper{
+public static void main(String[] args){
+//Code automatically generated with fuzzylite 6.0.
+
+Engine engine = new Engine();
+engine.setName("tipper");
+engine.setDescription("(service and food) -> (tip)");
+
+InputVariable service = new InputVariable();
+service.setName("service");
+service.setDescription("quality of service");
+service.setEnabled(true);
+service.setRange(0.000, 10.000);
+service.setLockValueInRange(true);
+service.addTerm(new Trapezoid("poor", 0.000, 0.000, 2.500, 5.000));
+service.addTerm(new Triangle("good", 2.500, 5.000, 7.500));
+service.addTerm(new Trapezoid("excellent", 5.000, 7.500, 10.000, 10.000));
+engine.addInputVariable(service);
+
+InputVariable food = new InputVariable();
+food.setName("food");
+food.setDescription("quality of food");
+food.setEnabled(true);
+food.setRange(0.000, 10.000);
+food.setLockValueInRange(true);
+food.addTerm(new Trapezoid("rancid", 0.000, 0.000, 2.500, 7.500));
+food.addTerm(new Trapezoid("delicious", 2.500, 7.500, 10.000, 10.000));
+engine.addInputVariable(food);
+
+OutputVariable mTip = new OutputVariable();
+mTip.setName("mTip");
+mTip.setDescription("tip based on Mamdani inference");
+mTip.setEnabled(true);
+mTip.setRange(0.000, 30.000);
+mTip.setLockValueInRange(false);
+mTip.setAggregation(new Maximum());
+mTip.setDefuzzifier(new Centroid(100));
+mTip.setDefaultValue(Double.NaN);
+mTip.setLockPreviousValue(false);
+mTip.addTerm(new Triangle("cheap", 0.000, 5.000, 10.000));
+mTip.addTerm(new Triangle("average", 10.000, 15.000, 20.000));
+mTip.addTerm(new Triangle("generous", 20.000, 25.000, 30.000));
+engine.addOutputVariable(mTip);
+
+OutputVariable tsTip = new OutputVariable();
+tsTip.setName("tsTip");
+tsTip.setDescription("tip based on Takagi-Sugeno inference");
+tsTip.setEnabled(true);
+tsTip.setRange(0.000, 30.000);
+tsTip.setLockValueInRange(false);
+tsTip.setAggregation(null);
+tsTip.setDefuzzifier(new WeightedAverage("TakagiSugeno"));
+tsTip.setDefaultValue(Double.NaN);
+tsTip.setLockPreviousValue(false);
+tsTip.addTerm(new Constant("cheap", 5.000));
+tsTip.addTerm(new Constant("average", 15.000));
+tsTip.addTerm(new Constant("generous", 25.000));
+engine.addOutputVariable(tsTip);
+
+RuleBlock mamdani = new RuleBlock();
+mamdani.setName("mamdani");
+mamdani.setDescription("Mamdani inference");
+mamdani.setEnabled(true);
+mamdani.setConjunction(new AlgebraicProduct());
+mamdani.setDisjunction(new AlgebraicSum());
+mamdani.setImplication(new Minimum());
+mamdani.setActivation(new General());
+mamdani.addRule(Rule.parse("if service is poor or food is rancid then mTip is cheap", engine));
+mamdani.addRule(Rule.parse("if service is good then mTip is average", engine));
+mamdani.addRule(Rule.parse("if service is excellent or food is delicious then mTip is generous with 0.5", engine));
+mamdani.addRule(Rule.parse("if service is excellent and food is delicious then mTip is generous with 1.0", engine));
+engine.addRuleBlock(mamdani);
+
+RuleBlock takagiSugeno = new RuleBlock();
+takagiSugeno.setName("takagiSugeno");
+takagiSugeno.setDescription("Takagi-Sugeno inference");
+takagiSugeno.setEnabled(true);
+takagiSugeno.setConjunction(new AlgebraicProduct());
+takagiSugeno.setDisjunction(new AlgebraicSum());
+takagiSugeno.setImplication(null);
+takagiSugeno.setActivation(new General());
+takagiSugeno.addRule(Rule.parse("if service is poor or food is rancid then tsTip is cheap", engine));
+takagiSugeno.addRule(Rule.parse("if service is good then tsTip is average", engine));
+takagiSugeno.addRule(Rule.parse("if service is excellent or food is delicious then tsTip is generous with 0.5", engine));
+takagiSugeno.addRule(Rule.parse("if service is excellent and food is delicious then tsTip is generous with 1.0", engine));
+engine.addRuleBlock(takagiSugeno);
+
+
+}
+}
diff --git a/examples/hybrid/tipper.pdf b/examples/hybrid/tipper.pdf
new file mode 100644
index 0000000..482e9cc
--- /dev/null
+++ b/examples/hybrid/tipper.pdf