AIMC Topic: Feedback

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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...

Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network.

Computational intelligence and neuroscience
In the detection of genome variation, the research on the internal correlation of reference genome is deepening; the detection of variation in genome sequence has become the focus of research, and it has also become an effective path to find new gene...

Extended Kalman filter for online soft tissue characterization based on Hunt-Crossley contact model.

Journal of the mechanical behavior of biomedical materials
Real-time soft tissue characterization is significant to robotic assisted minimally invasive surgery for achieving precise haptic control of robotic surgical tasks and providing realistic force feedback to the operator. This paper presents a nonlinea...

Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topi...