Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , neural networks (NNs) are utilized in the backstepping approach to design a control input by approximating unknown dynamics of the strict-feedback nonlinear system with event-sampled inputs. The system state vector is assumed to be measurable. As part of the controller design, first, local input-to-state-like stability (ISS) for a continuously sampled controller that has been injected with bounded measurement errors is demonstrated and, subsequently, an event-execution control law is derived such that the measurement errors are guaranteed to remain bounded. Lyapunov theory is used to demonstrate that the tracking errors and the NN ight estimation errors for each NN are locally uniformly ultimately bounded (UUB) in the presence bounded disturbances, NN reconstruction errors, as ll as errors introduced by event-sampling. Simulation results are provided to illustrate the effectiveness of the proposed controller.
['Nathan Szanto', 'Vignesh Narayanan', 'S. Jagannathan']
I am writing a research paper on a idea Event-sampled direct adaptive NN state-feedback control of uncertain strict-feedback system
[{"from": "human", "value": "I am writing a research paper on a idea Event-sampled direct adaptive NN state-feedback control of uncertain strict-feedback system"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , neural networks (NNs) are utilized in the backstepping approach to design a control input by approximating unknown dynamics of the strict-feedback nonlinear system with event-sampled inputs. The system state vector is assumed to be measurable. As part of the controller design, first, local input-to-state-like stability (ISS) for a continuously sampled controller that has been injected with bounded measurement errors is demonstrated and, subsequently, an event-execution control law is derived such that the measurement errors are guaranteed to remain bounded. Lyapunov theory is used to demonstrate that the tracking errors and the NN ight estimation errors for each NN are locally uniformly ultimately bounded (UUB) in the presence bounded disturbances, NN reconstruction errors, as ll as errors introduced by event-sampling. Simulation results are provided to illustrate the effectiveness of the proposed controller."}]