Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A recursive least squares based on Multi-model is proposed for non-uniformly sampled-data nonlinear (NUSDN) systems. The corresponding state space model of an NUSDN system is derived using lifting technique. Taking advantage of the Fuzzy c-Mean Clustering algorithm, NUSDN is divided into several local models. The basic idea is that the NUSDN system is vied as a model switching system under a given rule. Once the local models are identified, the global model is determined. A pH neutralization process validate the performance of the proposed algorithm.
['Ranran Liu', 'Tianhong Pan', 'Zhengming Li']
I am writing a research paper on a idea Multi-model recursive identification for nonlinear systems with non-uniformly sampling
[{"from": "human", "value": "I am writing a research paper on a idea Multi-model recursive identification for nonlinear systems with non-uniformly sampling"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A recursive least squares based on Multi-model is proposed for non-uniformly sampled-data nonlinear (NUSDN) systems. The corresponding state space model of an NUSDN system is derived using lifting technique. Taking advantage of the Fuzzy c-Mean Clustering algorithm, NUSDN is divided into several local models. The basic idea is that the NUSDN system is vied as a model switching system under a given rule. Once the local models are identified, the global model is determined. A pH neutralization process validate the performance of the proposed algorithm."}]