Control Design & Implementation Methodology

Many applications greatly benefit from or even completely rely on a well-tuned controller. At SC Solutions we have a long track record of tackling control problems and supplying our customers with solutions ranging from ready-to-install controller hardware to controller software modules. And in the process we help you to gain insight into your system, often leading to significant improvements in its design or operation.

Model-based Control

Model-Based Feedback Control Design is the cornerstone of SC Solutions' control design technology. This proven technology consists of several steps, see Figure 1. The first step is the development of a physics-based computer model of a system to be controlled. The model (generally nonlinear) is then validated using actual data from the system. The order and complexity of the model depends on the application, but are typically large at the validation stage. A reduced-order model is then constructed for use in the feedback control system design.

Figure 1. Schematic of SC Solutions’ iterative model-based control design procedure.

The next step involves the design of a (feedback) controller based on the model. The closed-loop control system is first evaluated via computer simulations. Once the performance meets (or exceeds) specification, the feedback controller is used to control the actual system. This constitutes the third step, in which data closed-loop data is collected on the actual system.

Typically, the controller does not meet the desired performance specifications right away, and some kind of design iteration is necessary. The reason for this is the fact that the actual system is far more complex than a physical model can typically capture, i.e., there is some inherent system/model uncertainty. Other sources of uncertainty include sensor noise and/or actuator dynamics or quantization.

Subsequent steps in the design procedure therefore include comparing the data to the model and adjusting uncertain model parameters until the simulated model matches the system data. The last step is the re-design of the controller based on the adjusted model. This iterative procedure is repeated until the closed-loop data on the actual system meets or exceeds the desired performance specifications, see Figure 1.

Advantages

This model-based control design approach has a number of major advantages over other approaches:

• Performance. The model can be used directly for designing and implementing complex multi-input multi-output, possibly nonlinear, controllers that extract the maximum performance from your system.
• Insight. The model provides physical insight into the open-loop and closed-loop behavior of the system; it can be used to generate data that may not be easily measured.

Other advantages of this approach are:

• Robustness. The controller can be validated for a wide range of system conditions by simply varying one or more model parameters.
• Soft copy. The resulting physical model of the system represents a ‘soft copy’ of the system hardware, and can therefore be used for “what-if” tests. For example, some of customers use the model to tune controller set-points for optimal process yield. It can also be used as the basis of a simulator tool for training purposes.
• Reduced time-to-market. Because a physical model can be developed prior or in parallel with the actual hardware, a controller can be developed in parallel with the system as well, and be ready for testing even before the hardware is ready.
• Cost efficient. Related to this, much of the control design can be done without (oftentimes expensive) access to equipment.
• Analysis tool. Lastly, the model-based approach provides a tool for troubleshooting, and is a path for continued improvement of the system.

Controller Implementation

SC has developed a complete solution for embedded control development including different embedded controller platforms in conjunction with our real-time implementation software SC-x™, SC-xTune™, SC-xSim™. Our model-based feedback control design technology provides a systematic process for modeling, simulation, data acquisition, and controller design. We use industry standards such as C/C++/C# to implement our controller code as well as graphical user interfaces, see Figure 2 for an example user interface. The embedded control approach can be tailored toward the control of arbitrary systems to implement the required feedback controller algorithms. We deliver controllers in a number of formats, including:

• Ready-to-install hardware box;
• Ready-to-install software application for your system of choice;
• Compiled module for the system of your choice;
• ANSI C code with zero dependencies on system libraries.

We provide a clear and easy to use software interface to our controllers, including a facility to update the controller without the need for recompiling code, reducing your QA cycle time.

Figure 2. SC-xSim, one of SC Solutions’ graphical simulation interfaces.

Typically, the embedded controller will make use of available system sensor information, and will calculate the signals that drive the available system actuators. Given the flexibility of both the embedded controller hardware and software, it is possible to easily combine real-time control, and data acquisition, as well as readily accommodate changes in the process configuration.

SC Solutions uses a proprietary Model-Based Feedback Control Development Process which provides for a systematic and seamless process for modeling, simulation, controller design and development. This approach enables us to extract maximum performance from complex multi-input, multi-output processes which have a high degree of interaction between various process inputs and outputs. Traditional single-input, single-output design approaches limit the level of performance that can be achieved in systems with strong coupling.