Real-Time Workshop

An Open and Extensible Environment

The Simulink and Real-Time Workshop model-based software development environment is extensible in several ways.

Custom Code Support

S-functions are dynamically linked objects (.dll or .so) that bind with Simulink to extend the modeling environment. By developing S-functions, you can add custom block algorithms to Simulink. Such S-functions provide supporting logic for the model. S-functions are flexible, allowing you to implement complex algorithmic equations or basic low-level device drivers. Real-Time Workshop support for S-functions includes the ability to inline S-function code directly into the generated code. Inlining, supported by the Target Language Compiler, can significantly reduce memory usage and calling overhead.

Support for Supervisory Code

The generated code implements an algorithm that corresponds exactly to the algorithm defined in your model. With the embedded code format, you can call the generated model code as a procedure. This enables you to incorporate the generated code into larger systems that decide when to execute the generated code. Conceptually, you can think of the generated code as set of equations, wrapped in a function called by your supervisory code. This facilitates integration of model code into large existing systems, or into environments that consist of more than signal-flow processing (Simulink) and state machines (Stateflow).

Monitoring and Parameter Tuning APIs

External mode provides a communication channel for interfacing the generated code running on your target with Simulink. External mode lets you use Simulink as a debugging front end for an executing model. Typically, the external mode configuration works in conjunction with either the real-time code format or the real-time malloc code format.

Real-Time Workshop provides other mechanisms for making model signals and block parameters visible to your own monitoring and tuning interfaces. These mechanisms, suitable for use on all code formats, include:

• The Model Parameter Configuration dialog box, where you declare how to allocate memory for variables that are used in your model. For example, if a Gain block contains the variable k, you can declare k as an external variable, a pointer to an external variable, a global variable, or let Real-Time Workshop decide where and how to declare the variable.

• The Model Parameter Configuration feature enables you to specify block parameters as tunable or global. This gives your supervisory code complete access to any block parameter variables that you may need to alter while your model is executing. You can also use this feature to interface parameters to specific constant read-only memory locations.

• You can mark signals in your model as test points. Declaring a test point indicates that you may want to see the signal's value while the model is executing. After marking a signal as a test point, you specify how the memory for the signal is to be allocated. This gives your supervisory code complete read-only access to signals in your model, so that you can monitor the internal workings of your model.
• C and Target Language Compiler APIs provide another form of access to the signals and parameters in your model. The Target Language Compiler API is a means to access the internal signals and parameters during code generation. With this information, you can generate monitoring/tuning code that is optimized specifically for your model or target.

Interrupt Support

Interrupt blocks enable you to create models that handle synchronous and asynchronous events, including interrupt service routines (ISRs), hardware-generated interrupts, and asynchronous read and write operations. The blocks provided work with the Tornado target. You can use these blocks as templates when creating new interrupt blocks for your target environment. Interrupt blocks include

• Asynchronous Interrupt block
• Task Synchronization block
• Asynchronous Buffer block (read)
• Asynchronous Buffer block (write)
• Asynchronous Rate Transition block

Code Generation Optimizations