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Model Based Development: From system engineering with Simulink to software specification with SCADE then to implementat

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### Model Based Development:From system engineering with Simulink to software specification with SCADEthen to implementation

### From Simulink to SCADE

Thierry LE SERGENT

FERIA

May 4th, 2004

Agenda

- Model based development
- Simulink vs. SCADE
- Principles of Simulink Gateway

Esterel Technologies, 2004

Context

- System design with Simulink
- Goal: develop software for the Controller

Plant to be controlled

Controller: Software to be implemented

HW interface

HW interface

Electronic system to be implemented

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Software development

- Traditional method
- Modelisation in Simulink for simulation
- Hand coding of the software controller
- Inconveniences
- Coherence between Model and Code
- Round trip is difficult

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Model based development

- First solution
- Code generation from the Simulink model
- Advantages: model based a single reference: the Simulink model coherence, fast round trip, etc.
- Inconvenience: Simulink model not a formal description (see next slides)
- New solution
- Assisted translation
- From Simulink model
- To formal description language SCADE
- Then code generation from SCADE
- Advantages:
- Model based (fast round trip if translation automatized)
- Formal software specification No ambiguities, Formal verification, etc.

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Workflow

System Engineering

Software Specification

Software Implementation

SCADE Specification

Simulink model

SCADE Simulink Gateway

SCADE Implementer

SCADE implementation

Engineering to specification

Specification to implementation

C code

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Different Tools for Different Purposes

- SCADE and Simulink are both model based development tools, but they are targeted for different purposes
- Simulink: Simulation environment
- Primarily an environment for prototyping. Excellent at quickly representing graphically numerical equations/control laws, and simulating them
- Extremely flexible. Requires no programming constraint
- But not designed to generate safe code
- SCADE: SW Design environment for critical control systems
- SCADE has been designed from the beginning to meet the strongest embedded software requirements, in particular for safety critical systems in avionics
- SCADE offers a fully integrated design environment from specification to safe embedded production code certifiable to strict industry standards (DO178B)

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SCADE

C code generation

&

embedding

- Modelling of environment (system) + controller
- Simulation of the whole system

- Validation of the controller model
- Code generation

- The translation must:
- Explicit some implicit behavior
- Filter unsafe constructs
- Compute types and clocks

Pb1: Simulink initial values

- Initial values
- Implicitly determined from the content of the sub-system
- can lead to misunderstandings
- On this model, only the Unit Delay has an initial value = 3Gain block has no initial value Simulink sets the output to 0

3 * 2 = 0 !!

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Pb1: SCADE initial values

- It is mandatory to explicitly set initial output values of an enabled sub-system
- Independent of the content of the sub-system
- No automatic change out of control of the designer, sono unexpected calculated values

Initial value of the first output

Initial value of the second output

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Pb 2: Unsafe Operators

- Simulink
- Some operators are not usable for the development of critical embedded software because they can result in non deterministic or misleading behavior
- Simulink blocks:
- Merge: indeterminist block, except in special cases
- Goto/From, Data Store : equivalent to global variables, make the design hard to understand and not robust for enhancements
- While loops: could lead to infinite loops
- SCADE
- SCADE has been designed from the beginning with safety objectives: only safe and deterministic operators exist
- The SCADE language, based on Lustre academic languagemakes it impossible to create a non deterministic design

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Unsafe Operators: Merge

- The Merge block combines its inputs into a single output line whose value at any time is equal to the most recently computed output of its driving blocks
- On this example, both sub-systems are running in parallel and it is not possible to determine which output the Merge block will give, the square or the sinus

- The Merge block is determinist when all its inputs are strictly exclusives, for example when generated by an action block of the If/Then/Else or Switch/Case blocks

Supported by Simulink Gateway

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Pb 3: Modularity

- Simulink
- “Virtually” modular: only visual grouping
- Subsystem behaviour depends on this usage within the system
- No clear subsystem interface definition
- A subsystem re-used in another project can behave differently, it must be re-validated
- SCADE
- Truly modular: a SCADE design is composed of independent node designed separately
- A node always behaves in the same way, independently of where it is used
- A SCADE node has a strong interface definition
- A node can be directly re-used in another project without any additional work

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Pb 4: SW Simulation

- Simulink
- The model is interpreted as a Mathematical set of equations, an Ordinary Differential Equations (ODE), solved at each simulation step by the solver
- Simulation results are highly dependant of the solver (integration algorithm) resulting in different behaviors for different solvers
- Discrete time does not exist, it is interpreted as piece wise constant continuous time: this is different from SW behavior
- SCADE
- Everything in SCADE is based on a cyclic logical time, counted as discrete instants which enables exactly the same behavior as a SW application
- This is an execution of the generated code (Software In the Loop simulation)
- No difference between simulation and generated code

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Simulink to SCADE translation

- Filtering unsafe constructs
- Unsafe blocks translated into undefined imported nodes
- Interpretation of the Simulink model
- Discrete time, fixed-step solver
- Translation of the Controller of the Simulink model a SCADE model with same interface
- Structure kept: Subsystem Node
- Graphical look kept: Simulink net view SCADE net view
- Names kept: variables, operators, …
- Mapping: Simulink predefined operator SCADE node
- Configurable mapping to SCADE librarie node(generated node for a few specific cases)
- Mapping dependant from datatype computed

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Simulink model example

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Simulink model format

- Simulink .mdl files:
- Basically 3 kind of objects:
- System {…}
- -> Hierarchy
- Block {…}
- List of: “AttributeName” = “value”
- First attribute: “BlockType”
- Line {…}

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.mdl example

System {

Name "sys NOT"

Location [107, 120, 513, 367]

…

Block {

BlockType Constant

Name "Constant"

Position [25, 40, 130, 80]

Value "2.5 * AA"

}

…

Block {

BlockType Logic

Name "Logical\nOperator"

Position [185, 34, 280, 86]

Operator "NOT"

…

}

…

Line {

SrcBlock "Logical\nOperator"

SrcPort 1

DstBlock "Out1"

DstPort 1

}

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Type inference

- Simulink
- No data type specified, i.e. all data flows are of type « double »
- Flat vectors possible almost everywhere (vectorized blocks)
- Scade: all flows must be typed;
- Basic types: bool (noted b), int (i), real (r)
- Tuples
- For precise software specification, SCADE types must be computed
- For formal verification, an « int » is very different from a « real »
- Note: In Simulink, it is possible to specify very precise datatype such as int8, uint16, etc. for code generation
- This coding step should be handled after the software specification phase
- This step is handled by the new SCADE implementer tool

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Principles

- Always compute the smallest types (bool < int < real)
- Start from the value of the static expressions (also for Matlab variables)
- “Propagate” the types on the flow
- Show the result on a decompiled, annotated Simulink model

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Configuration file

- For each Simulink block
- How propagate the types ?
- Translation to which SCADE node ?
- Depend of
- The BlockType, and attributes of the block (ex: “operator”=“NOT”, or…)
- The types inferred for the input
- First example from Main Configuration File:

( "BlockType" = "Logic", "Operator" = "NOT" ) {

Interface( 1, 1)

Type( b -> b) {"SC_ECK_NOT"} // SCADE predefined NOT operator

Type( i -> b) { "LibSimulink", "SMLK_NotI"}

Type( r -> b) { "LibSimulink", "SMLK_NotR"}

}

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Resulting SCADE model

- Note: Parameterization with Matlab variable AA kept
- Each Matlab variable translated into a SCADE constant

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Set of mapping rules

- When the types input does not match CF rules
- Choice of the « nearest » rule with larger types
- Introduction of explicit cast: always from a smaller type to a bigger one
- Example:

- SCADE model

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Set of mapping rules

( "BlockType" = "Switch")

{

Interface( 3( "Threshold"), 1)

Type( b, r, b ( r) -> b) { "LibSimulink", "SMLK_Switch"}

Type( i, r, i ( r) -> i) { "LibSimulink", "SMLK_Switch"}

Type( r, r, r ( r) -> r) { "LibSimulink", "SMLK_Switch"}

}

- The « nearest rule » must be unique !
- Non coherent example:
- Problem if (i, i) inferred for the inputs. The 2 rules are “equally near”
- A set of rule is « coherent » if the min of any 2 rules is in the set
- Min computed with b < i < r input per input
- Error message: add rule « type…. » or remove one of rules « type… », « type… », …

Type( i, r -> i) { "Lib1", "N1"}

Type( r, i -> r) { "Lib2", "N2"}

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Vectorization

- When the input types are vectors
- Vectorization of the mapping rule
- Automatic introduction of SCADE textual capsule that apply the operator as many time as necessary, and build the vectors to output

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Vectorization capsule

node S2S_Vect_3_DeadBandUnSymm(

Input1 : [bool , int , real] ;

hidden Input2 : real ;

hidden Input3 : real)

returns (

Output1 : [real , real , real]) ;

var

….

let equa S2S_Vect_3_DeadBandUnSymm[ , ]

_L0 = Input1[1] ;

_L1 = Input1[2] ;

_L2 = Input1[3] ;

_L3 = BoolToReal(_L0) ;

Out_1_1 = DeadBandUnSymmetrical(_L3 , Input2 , Input3) ;

_L4 = real (_L1) ;

Out_2_1 = DeadBandUnSymmetrical(_L4 , Input2 , Input3) ;

Out_3_1 = DeadBandUnSymmetrical(_L2 , Input2 , Input3) ;

Output1 = [Out_1_1 , Out_2_1 , Out_3_1] ;

tel ;

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Type inference algorithm

- Fix-point algorithm to propagate throughout the model - the arities (size of the vectors),- the types,thanks to the « main » and « user defined » Configuration Filesspecifying mapping rules.
- Problems: the loops in the data flow
- Message « ATI failed »
- Workaround: the Configuration Files:it is possible to « force the types » thanks to rules in CF
- Example:
- Vérimag is working on another strategy
- Constraints resolution algoritm (« propagation » in both direction of the data flow)

“Controller”/ "UnitDelay"{

interface(1,1)

ArityType(r -> r)

}

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Clock inference (1/3)

- Simulink
- Discrete operators: execution based on “sample time”
- Value representing an actual delay
- "-1" to represent inheritance of the sample time from the input flow
- Enable subsystems
- Excuted while condition signal > 0
- Triggered subsystems
- Executed on rising/falling edge of condition signal
- SCADE
- clocks derived from a basic clock
- Condact operator on node
- Executed if condition signal = TRUE

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Clock inference (2/3)

- Simulink Gateway
- computes the rate of the SCADE basic clock:
- GCD of the sample time values.Example: ST1=1.75, ST2=(2.25, 0.5) Basic Clock=0.25
- generates all required derived clocks
- SCADE node SMLK_ClockGen(period,offset) (period,offset) = (9,2) for the block with ST2
- Encapsulates the SCADE node corresponding to Simulink discrete block with condact activated by the correct generated clock

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Clock inference (3/3)

- Enable and trigger handling
- Encapsulate the SCADE node with condact activated by signal computed from the condition
- E.g.: GeneralTrigger = RisingEdge(condition);
- Caution: the generation of the derived clock (by SMLK_ClockGen) must be done OUTSIDE Enabled or Triggered subsystems;The « global time » runs always at the same speed
- Derived clocks generated in a textual capsule at the root node of the model
- Propagation of the clocks to the discrete blocks through additional parameters to the nodes

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From SCADE to Simulink: Simulink Wrapper

Back box Simulation

Simulink

Gateway

Original Simulink model

“Hybrid model”

SCADE CG

C files

MEX

Simulink

Wrapper

S-function DLL

Generated SCADE model

Wrapper code (C)

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Simulink Wrapper

- The SCADE model is integrated into Simulink as an “S-Function”
- The S-Function is automatically generated :
- C code generated by the SCADE Code Generator
- Capsule code generated by the Wrapper
- Simulation under Simulink:
- The SCADE node is a black box
- Next release: also white box co-simulation with SCADE simulator
- The embeddable code interacts with Simulink environment
- May be used Independently or coupled with Simulink translator

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Simulink Gateway project summary

- Started: February 2000
- under European project SafeAir (SNECMA, Airbus, Vérimag, …)
- Pursued under European project RISE (Audi, TTTech, Vérimag)
- Matured tool used on industrial projects
- Example: New Rafale engine developed by Hispano Suiza
- Several thousands of Simulink blocks
- Code generated by SCADE KCG for certification this year

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