Plant & Controls

Model-Based Control

The Challenge

Control systems developed according to traditional design methods come with a number of drawbacks. For example, they are inherently ill-suited to deal with complex, multi-variable systems, require a significant amount of experimental calibration effort, do not naturally adapt to changes in the plant characterstics, lack a reusable, methodical design process, and many more. With the emergence of more and more powerful CAD tools, companies are increasingly adopting model-based controller design methods because these methods promise to ease many of these shortcomings.

The Promise

The idea behind a model-based control design approach is to identify and leverage important plant characteristics and synthesize the controller with those plant characteristics in mind. Unlike a controller designed according to classical control design principles, a model-based controller can anticipate the plant response to a particular control command. It is, therefore, inherently better suited to meet a given set of control performance objectives. In fact, control performance objectives guide a truly model-based control synthesis process from the onset, either in the form of analytical controller design constraints or in the form of controller optimization criteria. In a sense, the controller is tuned upfront by way of selecting appropriate design parameters. Overall, model-based control is a promising approach to expedite the control design process and to alleviate the typical calibration burdon associated with traditional controller development.

The Obstacle

Of course, there is no "free" lunch. Classical control design is still attractive, mainly because of the simplicity of the resulting controllers. One does not have to be a control specialist in order to understand the inner workings of a PID controller. Moreover, in order to tune the controller parameters one does not have to understand the plant dynamics any more than from a behavioral standpoint. Conversely, model-based design techniques require a fundamental physical understanding of relevant plant charactersitics and, more importantly, an aptitude to put these characteristics into an analytical context (e.g., an aptitude to derive plant model equations and an aptitude to understand the mathematical framework behind the controller synthesis method).

It is this fact that has impeded the deployment of "truly" model-based control synthesis methods in the past, and, to a certain extent, still does today. In fact, many of the model-based efforts currently underway reflect a compromise where classical control design principles are paired with a model-based development approach. The benefit here lies in utilizing a virtual design framework to pre-calibrate the controller parameters. While this approach has certainly proven viable it still does not exploit all the benefits of a truly model-based design strategy.

The Remedy

We at SimuQuest have assembled a team with profound expertise in both plant model development and model-based controller synthesis techniques. In addition, we know how to leverage state of the art tools towards the realization of a fully intergrated, model-based development solution for any particular need. Among our customers we are known for our commitment, our dedication, and on our focus on the task at hand. We will go the extra mile in order to find the best solution for you. Leverage our expertise and our resources for your projects without getting your current committments off track.