What are the best ways to ensure portability of programming language control systems?

Portability in a Control System can be achieved by using simple method. Its creating templates. This is same as defining class in a High Level programming. Templates for each process objects in a plant can ensure portability, and can be saved as a Library for future use cases. Templates can also help in easily updating the whole of Control system without going to each of the process areas and can ease the testing as well.

Portability in industrial control programming is unique, often requiring the same brand of equipment. Unlike general programming, specific software and versions are needed for devices like HMIs, PLCs, and RTUs. For instance, upgrading from a Siemens S7-300 to an S7-1500 is straightforward if software versions match, allowing easy program transfer. However, switching between different brands complicates things significantly. In such cases, manually replicating the program structure from the old to the new system is usually the best approach.

Many PLC IDEs use different implementations of IEC 61131-3, making code portability relatively difficult. C/C++ code might also rely on libraries that are specific to certain IDEs. You might want to consider using Model-Based Design. Your "ultimate source of truth" for your intellectual property and design would be the models that you have designed. You can generate code from models for most PLC IDEs. For example, you can generate ST or C/C++ code from MATLAB Simulink for Beckhoff, Siemens, B&R, and many other PLCs.

MATLAB and Simulink have quite a few libraries that can simplify your development, ranging from toolboxes and libraries related to control design and going all the way to Predictive Maintenance and AI. You can generate code from MATLAB and Simulink to program and integrate on a large number of PLCs and other industrial controllers.

In the context of control systems, there are several standards that are commonly followed to ensure reliability, safety, and interoperability. Some of the key standards include: 1. IEC 61131-3 2. ISA-95 3. IEC 61508 4. ISO 27001 5. ISO 900 6. IEEE 1588 (Precision Time Protocol) These standards help in establishing best practices, ensuring safety, and promoting interoperability in control system development. The specific standards applicable can depend on the industry, region, and type of control system being developed.

Particularly for Control systems, you're likely working on some sort of critical system. In aviation, adherence to DO-178 (or similar for non-FAA work) is paramount. It may be tough to modernize your processes to Agile (or some other non-waterfall iterative process)and follow DO-178, but maintaining your design documents (HLR & LLR) alongside your code will help ensure that you're meeting your requirements when it's time to create your traceability. Ideally, it also means somebody else in the company can come after you and have a general idea of what to expect before they ever lay eyes on the code, as long as they can trust that you followed your standards and procedures.

After validating a control algorithm in desktop simulation, you might run into surprises caused by how it performs on the hardware that it is eventually supposed to run on. One way of dealing with this risk is to test the algorithms on the actual (final) hardware through Hardware-in-the-Loop (HIL). HIL implies having a model of the plant running on some real-time PC, and connecting that to the controller either with physical I/Os or through a communication bus (like OPC UA over ethernet) to validate the application. If you use Model-Based Design, you would be able to run the same tests in desktop simulation (at an earlier step) and generate code from the plant and control models. Software to automatically manage tests is also available.

Since a lot of control system implementations are on discrete time systems, it is important to specify the sampling and periodic update time intervals. Once these periods are specified, porting to a new architecture / platform becomes an easy task as long as the timing is guaranteed.

If there is one thing that I've learned, it's that early simulation can drastically improve control software quality. First-hand accounts from the industry show that the systematic use of models and simulation can: - drastically reduce software testing time, - decrease development time, - shorten time to FAT, - and facilitate updates and design iterations.