Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Automated physical resource management of large-scale Internet Technology (IT) systems requires dynamic configuration of both application-level and system-level parameters. The existence of large number of tunable parameters makes it difficult to design a feedback controller that adjusts these parameters effectively in order to achieve application-level performance targets. ,  introduce a new approach for simplified control architecture of large-scale IT systems based on dimension reduction techniques. It combines online selection of critical control knobs through LASSO-a porful   $L_1$    -constrained fitting method/Compressive Sensing (CS)-a   $L_1$    -optimization method, and adaptive control of the identified knobs. The latter relies on the online estimation of the input-output model with the selected control knobs using the recursive least square (RLS) method and a self-tuning linear quadratic (LQ) optimal controller for output regulation. The results of both a numerical simulation in Matlab and a realistic case are presented to demonstrate the effectiveness of our approach.
['Jianguo Yao', 'Xue Liu', 'Xiaoyun Zhu', 'Haibing Guan']
I am writing a research paper on a idea Control of Large-Scale Systems through Dimension Reduction
[{"from": "human", "value": "I am writing a research paper on a idea Control of Large-Scale Systems through Dimension Reduction"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Automated physical resource management of large-scale Internet Technology (IT) systems requires dynamic configuration of both application-level and system-level parameters. The existence of large number of tunable parameters makes it difficult to design a feedback controller that adjusts these parameters effectively in order to achieve application-level performance targets. ,  introduce a new approach for simplified control architecture of large-scale IT systems based on dimension reduction techniques. It combines online selection of critical control knobs through LASSO-a porful   $L_1$    -constrained fitting method/Compressive Sensing (CS)-a   $L_1$    -optimization method, and adaptive control of the identified knobs. The latter relies on the online estimation of the input-output model with the selected control knobs using the recursive least square (RLS) method and a self-tuning linear quadratic (LQ) optimal controller for output regulation. The results of both a numerical simulation in Matlab and a realistic case are presented to demonstrate the effectiveness of our approach."}]