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Observer-based event-triggered control for zero-sum games of input constrained multi-player nonlinear systems.

Neural networks : the official journal of the International Neural Network Society
In this paper, an event-triggered control (ETC) method is investigated to solve zero-sum game (ZSG) problems of unknown multi-player continuous-time nonlinear systems with input constraints by using adaptive dynamic programming (ADP). To relax the re...

The Adaptive Dynamic Programming Toolbox.

Sensors (Basel, Switzerland)
The paper develops the adaptive dynamic programming toolbox (ADPT), which is a MATLAB-based software package and computationally solves optimal control problems for continuous-time control-affine systems. The ADPT produces approximate optimal feedbac...

Intermittent control for finite-time synchronization of fractional-order complex networks.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the finite-time synchronization problem for fractional-order complex dynamical networks (FCDNs) with intermittent control. Using the definition of Caputo's fractional derivative and the properties of Beta function, the Ca...

HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the force feedback from their proprioception. However, this ability is extremely challenging to reproduce...

Fast and Precise Control for the Vibration Amplitude of an Ultrasonic Transducer Based on Fuzzy PID Control.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
This work presents a novel constant frequency ultrasonicamplitude control (CFUAC) method based on fuzzy proportional-integral-derivative (FPID) and amplitude direct feedback. The frequency shift and amplitude nonlinearity of the piezoelectric transdu...

Novel methods to global Mittag-Leffler stability of delayed fractional-order quaternion-valued neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, a type of fractional-order quaternion-valued neural networks (FOQVNNs) with leakage and time-varying delays is established to simulate real-world situations, and the global Mittag-Leffler stability of the system is investigated by usin...

Dynamical and static multisynchronization analysis for coupled multistable memristive neural networks with hybrid control.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the dynamical multisynchronization (DMS) and static multisynchronization (SMS) problems for a class of delayed coupled multistable memristive neural networks (DCMMNNs) via a novel hybrid controller which includes delayed impul...

Human-in-the-Loop Low-Shot Learning.

IEEE transactions on neural networks and learning systems
We consider a human-in-the-loop scenario in the context of low-shot learning. Our approach was inspired by the fact that the viability of samples in novel categories cannot be sufficiently reflected by those limited observations. Some heterogeneous s...

Intrinsic Plasticity-Based Neuroadptive Control With Both Weights and Excitability Tuning.

IEEE transactions on neural networks and learning systems
This brief presents an intrinsic plasticity (IP)-driven neural-network-based tracking control approach for a class of nonlinear uncertain systems. Inspired by the neural plasticity mechanism of individual neuron in nervous systems, a learning rule re...

Dynamics Analysis and Design for a Bidirectional Super-Ring-Shaped Neural Network With n Neurons and Multiple Delays.

IEEE transactions on neural networks and learning systems
Recently, the dynamics of delayed neural networks has always incurred the widespread concern of scholars. However, they are mostly confined to some simplified neural networks, which are only made up of a small amount of neurons. The main cause is tha...