«non linear systems»
۵۱٬۶۸۹ نتیجهChange-Of-Bases Abstractions for Non-Linear Systems
We present abstraction techniques that transform a given non-linear dynamical system into a linear system or an algebraic system described by polynomials of bounded degree, such that, invariant properties of the resulting abstraction can be used to infer invariants for the origin
On the stability of T-S fuzzy control for non-linear systems
The main feature of a Takagi-Sugeno (T-S) fuzzy model is to express the local dynamics of each fuzzy implication (rule) by a linear system model. The overall fuzzy model of the system is achieved by fuzzy “blending” of the linear system models. Parallel or feedback connections of
Adaptive fuzzy pole placement for stabilization of non-linear systems
A new approach is proposed for the pole placement of non-linear systems using the state feedback and fuzzy system. We use a new online fuzzy training method in order to identify and obtain a fuzzy model for an unknown non-linear system using only the system input and output. Then
Uncertain LTI-models for Linear Control Design of Non-Linear Systems, Report no. LiTH-ISY-R-2808
Much attention in robust identi cation and control has been focused on linear low order models approximating high order linear systems. We consider the more realistic situation with a linear model approximating a non-linear system. We describe how a linear time invariant (LTI) mo
Tech Report: Robust Model Predictive Control for Non-Linear Systems with Input and State Constraints Via Feedback Linearization
Robust predictive control of non-linear systems under state estimation errors and input and state constraints is a challenging problem, and solutions to it have generally involved solving computationally hard non-linear optimizations. Feedback linearization has reduced the comput
Predictive Control Design Based on Neural Model of a Non-linear System
This paper provides two approaches for design of Generalized Predictive Control (GPC) algorithm for a non-linear dynamic system. In the classical approach of the GPC strategy the recursive method of least square is considered for calculating of the linearized model parameters fro
Extended model set, global data and threshold model identification of severely non-linear systems
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Robust adaptive control of uncertain non-linear systems with non-linear parameterisation
Abstract: Many physical systems such as welding processes are typically non-linear and uncertain. To control such systems effectively the control scheme requires to be robust with respect to varying operating conditions. On the basis of robust control Lyapunov function method and
Adaptive Smith Predictive Control of Non-Linear Systems Using Neurofuzzy Hammerstein Models
This paper proposes an Adaptive Smith Predictor Controller (ASPC) based on Neuro-Fuzzy Hammerstein Models (NFHM) with on-line non-linear model parameters identification. The NFHM approach uses a zeroorder Takagi-Sugeno fuzzy model to approximate the non-linear static function tha
Linear and Non-linear System Identification Using Separable Least-Squares
We demonstrate how the separable least-squares technique of Golub and Pereyra can be exploited in the identiication of both linear and non-linear systems based on the prediction error formulation. The model classes to be considered here are the output error model and innovations