Model-Based Control and Equipment Design

Advantages:

The MBC design approach has a number of major advantages over other approaches such as the design of traditional PID controllers:

• Performance Maximization: The MBC design approach can be used directly for designing and implementing complex Multi-Input Multi-Output (MIMO), possibly nonlinear, controllers that extract the maximum performance from your system.
• Provides Key Physical Insights: In MBC design, the model provides physical insight into the open-loop and closed-loop behavior of the system.
• Robustness: The controller can be tested in simulation over a wide range of system operating conditions by simply varying one or more inputs and model parameters.
• Reduced time-to-market: Because a physical model can be developed prior to (or in parallel with) prototype hardware development, a controller can be developed in parallel with the system, and can be ready for testing even before the hardware is ready.
• Cost-efficiency: Much of the control design can be done without access to equipment which is expensive and time-consuming.

From the viewpoint of equipment design, the model-based approach provides the following advantages:

• System simulation tool: 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 our customers use the model to tune controller set-points for optimal process yield. The model may also be incorporated into a simulation tool for training purposes.
• Troubleshooting tool: The model-based approach provides a tool for fault diagnostics. It may be useful for equipment health monitoring.
• Finally, the MBC approach offers a path for continued improvement of the system.

See a description of our Modeling, Simulation and Analysis activities for further information in the use of physics-based models for equipment design and maintenance.

Design Process:

As shown in the flow chart in 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 open-loop experiments if it an existing system. For next-generation equipment, initial control design is performed with a best-estimate model. 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 control system design.

Figure 1: MBC Design Process

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 an iterative design approach is employed. The reason is that the actual system is far more complex than a physical model can capture accurately, 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, as shown in the flow diagram in Figure 1.

Controller Implementation:

SC Solutions 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. 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 the ability to update the controller without the need for recompiling code, reducing your QA cycle time. 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.