State-dependent Parameter Nonlinear Systems: Identification, Estimation and Control
نویسندگان
چکیده
A control system design procedure is proposed for a widely applicable class of discrete-time, non-linear systems in which the system nonlinearities are incorporated into a linear model structure in the form of State-Dependent Parameter (SDP) functions. The identification and estimation of both non-parametric and parametric SDP models is discussed briefly. The SDP NMSS model structure is defined, and the SDP ProportionalIntegral-Plus (PIP) control algorithm is derived using an optimal LQ technique. The practical utility of the design methodology is illustrated by numerical example. Copyright © 2002 IFAC
منابع مشابه
An innovation representation for nonlinear systems with application to parameter and state estimation
An innovation model is derived for a nonlinear stochastic system described by a state variable representation. The problem of state and system parameter estimation is solved through identification of the innovation model. A recursive prediction error (RPE) algorithm is derived for the joint system parameter and state estimation through minimization of the innovation variance (MIV). The algorith...
متن کاملRotated Unscented Kalman Filter for Two State Nonlinear Systems
In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...
متن کاملNon-linear Fractional-Order Chaotic Systems Identification with Approximated Fractional-Order Derivative based on a Hybrid Particle Swarm Optimization-Genetic Algorithm Method
Although many mathematicians have searched on the fractional calculus since many years ago, but its application in engineering, especially in modeling and control, does not have many antecedents. Since there are much freedom in choosing the order of differentiator and integrator in fractional calculus, it is possible to model the physical systems accurately. This paper deals with time-domain id...
متن کاملTime-Invariant State Feedback Control Laws for a Special Form of Underactuated Nonlinear Systems Using Linear State Bisection
Linear state bisection is introduced as a new method to find time-invariant state feedback control laws for a special form of underactuated nonlinear systems. The specialty of the systems considered is that every unactuated state should be coupled with at least two directly actuated states. The basic idea is based on bisecting actuated states and using linear combinations with adjustable parame...
متن کاملNonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them. TheHammerstein-Wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002