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Applying any of these will result in highly sub-optimal system realizations in the presence of nonlinearities. The more recently introduced System Scenarios methodology can only handle limited form of dynamics and nonlinearities. Existing predictive optimization approaches are far from optimal as they do not fully exploit the predictability of the system at hand. To bridge this gap, the authors propose the combined strategy of dynamic bounding and proactive system conditioning for the predicted likely future. This paper describes systematic principles to design low-overhead controllers for cost-effective hard constraint management. When applied to fine-grain performance scaling mode assignment problem in a video decoder design, proposed concepts resulted in more than 2x energy gains compared to state-of-the-art techniques.<\/p>","DOI":"10.4018\/jaras.2011010102","type":"journal-article","created":{"date-parts":[[2011,2,15]],"date-time":"2011-02-15T20:42:50Z","timestamp":1297802570000},"page":"18-45","source":"Crossref","is-referenced-by-count":6,"title":["Systematic Design Principles for Cost-Effective Hard Constraint Management in Dynamic Nonlinear Systems"],"prefix":"10.4018","volume":"2","author":[{"given":"Satyakiran","family":"Munaga","sequence":"first","affiliation":[{"name":"IMEC and K. U. Leuven\/ESAT, Belgium"}]},{"given":"Francky","family":"Catthoor","sequence":"additional","affiliation":[{"name":"IMEC and K. U. Leuven\/ESAT, Belgium"}]}],"member":"2432","reference":[{"key":"jaras.2011010102-0","unstructured":"Adve, S., et al. (2002). 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