A Design Method for Multi-Input Single-Output Nonlinear Adaptive Digital Filters Using Neural Networks
نویسندگان
چکیده
منابع مشابه
Model Reference Adaptive Control for Multi-Input Multi-Output Nonlinear Systems Using Neural Networks
This paper presents a method of MRAC(model reference adaptive control) for multi-input multi-output(MIMO) nonlinear systems using NNs(neural networks). The control input is given by the sum of the output of a model reference adaptive controller and the output of the NN(neural network). The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the us...
متن کاملAdaptive Output Feedback Stabilization Using Mt-filters for Nonlinear Systems with Input and Output Time-delay
This paper investigates the problem of adaptive output feedback stabilization using MT-filters and the backstepping design method for a class of nonlinear systems with unknown input and output time-delay. It is shown that all the signals in the closed-loop system are globally uniformly bounded, and the output can be regulated to zero.
متن کاملStable multi-input multi-output adaptive fuzzy/neural control
In this letter, stable direct and indirect adaptive controllers are presented that use Takagi–Sugeno (T–S) fuzzy systems, conventional fuzzy systems, or a class of neural networks to provide asymptotic tracking of a reference signal vector for a class of continuous time multi-input multi-output (MIMO) square nonlinear plants with poorly understood dynamics. The direct adaptive scheme allows for...
متن کاملAdaptive output feedback control of nonlinear systems using neural networks
A direct adaptive output feedback control design procedure is developed for highly uncertain nonlinear systems, that do not rely on state estimation. The approach is also applicable to systems of unknown, but bounded dimension. In particular, we consider single-input/single-output nonlinear systems, whose output has known, but otherwise arbitrary relative degree. This includes systems with both...
متن کاملAdaptive Neural Network Method for Consensus Tracking of High-Order Mimo Nonlinear Multi-Agent Systems
This paper is concerned with the consensus tracking problem of high order MIMO nonlinear multi-agent systems. The agents must follow a leader node in presence of unknown dynamics and uncertain external disturbances. The communication network topology of agents is assumed to be a fixed undirected graph. A distributed adaptive control method is proposed to solve the consensus problem utilizing re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEJ Transactions on Electronics, Information and Systems
سال: 2000
ISSN: 0385-4221,1348-8155
DOI: 10.1541/ieejeiss1987.120.7_986