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Modelli LPV e LTV

R2026a

Modelli lineari a parametri variabili e modelli lineari a tempo variabile

Creare, manipolare, analizzare e simulare modelli lineari a parametri variabili (LPV) e modelli lineari a tempo variabile (LTV). Questi modelli possono approssimare sistemi non lineari e consentono di applicare in modo efficiente le tecniche di progettazione lineare a modelli non lineari.

Con le funzionalità disponibili, è possibile:

Creare modelli LPV o LTV da espressioni matematiche.
Creare modelli LPV o LTV che interpolino i risultati della linearizzazione su una griglia di condizioni operative.
Simulare la risposta temporale.
Specificare le connessioni basate sul segnale tra modelli variabili e modelli LTI.
Campionare la dinamica su una griglia di parametri per ottenere le approssimazioni LTI locali.
Discretizzare e ricampionare i modelli LPV o LTV.

Funzioni

espandi tutto

Oggetti del modello

`lpvss`	Linear parameter-varying state-space model (Da R2023a)
`ltvss`	Linear time-varying state-space model (Da R2023a)
`getTestValue`	Access test values for validating data function (Da R2023a)
`setTestValue`	Modify test values for validating data function (Da R2023a)
`findop`	Compute operating condition from specifications (Da R2023b)
`fixInput`	Fix value of some inputs and delete them (Da R2024a)

Campionamento e interpolazione

`psample`	Sample linear parameter-varying or time-varying dynamics (Da R2024a)
`ssInterpolant`	Build gridded LTV or LPV model from state-space data (Da R2023a)

Simulazione della risposta temporale

`step`	Risposta al gradino di un sistema dinamico
`impulse`	Grafico della risposta all'impulso di un sistema dinamico; dati di risposta all'impulso
`lsim`	Compute time response simulation data of dynamic system to arbitrary inputs
`initial`	System response to initial states of state-space model
`RespConfig`	(Not recommended) Options for step or impulse responses (Da R2023a)

Interconnessione del modello

`feedback`	Connessione di feedback di più modelli
`connect`	Block diagram interconnections of dynamic systems
`series`	Collegamento in serie di due modelli
`parallel`	Parallel connection of two models
`lft`	Generalized feedback interconnection of two models (Redheffer star product)

Trasformazione del modello

`c2d`	Convertire il modello da tempo continuo a tempo discreto
`d2c`	Convert model from discrete to continuous time
`d2d`	Resample discrete-time model
`xperm`	Reorder states in state-space models
`sminreal`	Eliminates structurally disconnected states, delays, and blocks

Blocchi

espandi tutto

Simulazione LPV

	LPV System	Simulare sistemi lineari a parametri variabili (LPV)
	LTV System	Simulate linear time-varying (LTV) systems (Da R2024a)

Sistemi variabili a tempo continuo

	Varying Delay	Varying delay with support for fixed delay and zero delay (direct feedthrough) (Da R2024a)
	Varying Lowpass Filter	Butterworth filter with varying coefficients
	Varying Notch Filter	Notch filter with varying coefficients
	PID Controller	Continuous-time or discrete-time PID controller
	PID Controller (2DOF)	Continuous-time or discrete-time two-degree-of-freedom PID controller
	Varying Transfer Function	Transfer function with varying coefficients
	Varying State Space	State-space model with varying matrix values
	Varying Observer Form	Observer-form state-space model with varying matrix values

Sistemi variabili a tempo discreto

	Discrete Varying Delay	Discrete varying delay with support for fixed delay and zero delay (direct feedthrough) (Da R2024a)
	Discrete Varying Lowpass	Discrete Butterworth filter with varying coefficients
	Discrete Varying Notch	Discrete-time notch filter with varying coefficients
	Discrete PID Controller (2DOF)	Discrete-time or continuous-time two-degree-of-freedom PID controller
	Discrete PID Controller	Discrete-time or continuous-time PID controller
	Discrete Varying Transfer Function	Discrete-time transfer function with varying coefficients
	Discrete Varying State Space	Discrete-time state-space model with varying matrix values
	Discrete Varying Observer Form	Discrete-time observer-form state-space model with varying matrix values

Argomenti

Nozioni di base dei modelli LTV e LPV

LTV and LPV Modeling
Fundamentals of linear time-varying and parameter-varying models.
Using LTV and LPV Models in MATLAB and Simulink
Create, analyze, and simulate linear parameter-varying and linear time-varying state-space models.

Utilizzo dei modelli analitici LTV e LPV

LPV Model of Bouncing Ball
Construct an LPV representation of a system that exhibits multi-mode dynamics.
LPV Model of Engine Throttle
Model engine throttle behavior as a linear parameter-varying system.
Analysis of Gain-Scheduled PI Controller
Analyze gain-scheduled PI control of an LPV system.
LPV Model of Magnetic Levitation System
Create analytic LPV model from linearized equations of magnetic levitation system.
Gain-Scheduled LQG Controller
Demonstrate instability in gain-scheduled control when parameters vary too quickly.

Utilizzo dei modelli LTV e LPV a griglia

LPV Approximation of Boost Converter Model
Obtain linear parameter-varying approximation of a nonlinear Simscape™ Electrical™ model.
Design and Validate Gain-Scheduled Controller for Nonlinear Aircraft Pitch Dynamics
Approximate nonlinear behavior of airframe pitch axis dynamics using linear parameter-varying model.
LPV Model of Magnetic Levitation Model from Batch Linearization Results
Create a gridded LPV model from batch linearization results of a magnetic levitation model.
Reduced Order Modeling of a Nonlinear Dynamical System as an Identified Linear Parameter Varying Model (System Identification Toolbox)
Identify a linear parameter varying reduced order model of a cascade of nonlinear mass-spring-damper systems.