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The increasingly complex environments in which systems need to execute has lead to the need for tools and techniques to systematically design dynamically adaptable systems. A new framework for the design of these adaptive systems is proposed here. The framework, named SMART (State Model Adaptive Run Time), is based on the mathematics of control theory and system identification techniques. This foundation allows the system to accurately predict constraint violations in the environment, such as a memory overflow, and avert them by selecting components that better utilize a particular resource. The result is a more robust system. An example of the application of SMART is presented to show the need and applicability of the framework. Experimental results demonstrate the framework has an 86% accuracy in predicting and averting memory constraint violations. These results indicate the SMART Framework is feasible and has the potential to be a useful design solution for dynamic adaptable systems. Improvements to the framework are proposed as future work.