Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

813
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
813
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

129
A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
129
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

391
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
391
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.0K
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
1.0K
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

1.0K
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
1.0K
Linearization and Approximation01:26

Linearization and Approximation

143
Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...
143

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Flexible and Regenerative Aptameric Graphene-Nafion Biosensor for Cytokine Storm Biomarker Monitoring in Undiluted Biofluids toward Wearable Applications.

Advanced functional materials·2026
Same author

Aptameric Metal-Organic Framework Nanobiosensor.

ACS applied nano materials·2026
Same author

Electroacupuncture Protects Against Post-MI Heart Failure Through Autonomic Regulation and α7nAChR Activation.

Cardiology research and practice·2026
Same author

Optimisation and validation of capture mNGS for predicting antimicrobial resistance.

EBioMedicine·2026
Same author

Author Correction: RIP-PEN-seq identifies a class of kink-turn RNAs as splicing regulators.

Nature biotechnology·2026
Same author

Cobalt-Catalyzed Asymmetric Cyclopropanation of Heteroaryl Alkenes with Homogeneous Zinc Carbenoids.

Journal of the American Chemical Society·2026

Related Experiment Video

Updated: Mar 16, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.2K

Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis.

Qinglai Wei1, Derong Liu2, Qiao Lin1

  • 1The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

IEEE Transactions on Neural Networks and Learning Systems
|August 17, 2016
PubMed
Summary
This summary is machine-generated.

A new local value iteration adaptive dynamic programming (ADP) algorithm efficiently solves optimal control problems for nonlinear systems. This method ensures admissible control laws by introducing novel termination criteria for improved performance.

More Related Videos

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K

Related Experiment Videos

Last Updated: Mar 16, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.2K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K

Area of Science:

  • Control Theory
  • Nonlinear Systems
  • Adaptive Dynamic Programming

Background:

  • Optimal control problems for discrete-time nonlinear systems are challenging.
  • Existing adaptive dynamic programming (ADP) methods often require computation over the entire state space.

Purpose of the Study:

  • To develop a novel local value iteration adaptive dynamic programming (ADP) algorithm.
  • To analyze admissibility properties and establish termination criteria for discrete-time local value iteration ADP algorithms.
  • To solve infinite horizon optimal control problems for discrete-time nonlinear systems.

Main Methods:

  • A local value iteration ADP algorithm is proposed, updating value functions and control laws on a subset of the state space.
  • Admissibility properties of iterative control laws are analyzed for the first time in this context.
  • New termination criteria are established to ensure admissible approximate optimal control laws.

Main Results:

  • The developed algorithm effectively solves infinite horizon optimal control problems for discrete-time nonlinear systems.
  • Admissibility properties of the local value iteration ADP algorithm are rigorously analyzed.
  • Novel termination criteria guarantee an admissible approximate optimal control law upon algorithm termination.

Conclusions:

  • The local value iteration ADP algorithm offers an efficient approach to optimal control for discrete-time nonlinear systems.
  • The established admissibility properties and termination criteria ensure reliable and effective control law generation.
  • Simulation results validate the performance and applicability of the proposed algorithm.