AIMC Topic: Feedback

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Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies.

The Journal of experimental biology
Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biolo...

Contact feedback helps snake robots propel against uneven terrain using vertical bending.

Bioinspiration & biomimetics
Snakes can bend their elongate bodies in various forms to traverse various environments. We understand well how snakes use lateral body bending to push against asperities on flat ground for propulsion, and snake robots can do so effectively. However,...

Multidirectional Associative Memory Neural Network Circuit Based on Memristor.

IEEE transactions on biomedical circuits and systems
Multidirectional associative memory neural network(MAMNN) is a direct extension of bidirectional associative memory neural network, which can handle multiple associations. In this work, a circuit of MAMNN based on memristor is proposed, which simulat...

A modular strategy for distributed, embodied control of electronics-free soft robots.

Science advances
Robots typically interact with their environments via feedback loops consisting of electronic sensors, microcontrollers, and actuators, which can be bulky and complex. Researchers have sought new strategies for achieving autonomous sensing and contro...

Data-Driven H Optimal Output Feedback Control for Linear Discrete-Time Systems Based on Off-Policy Q-Learning.

IEEE transactions on neural networks and learning systems
This article develops two novel output feedback (OPFB) Q -learning algorithms, on-policy Q -learning and off-policy Q -learning, to solve H static OPFB control problem of linear discrete-time (DT) systems. The primary contribution of the proposed alg...

Local Stability and Convergence Analysis of Neural Network Controllers With Error Integral Inputs.

IEEE transactions on neural networks and learning systems
This article investigates the local stability and local convergence of a class of neural network (NN) controllers with error integrals as inputs for reference tracking. It is formally proved that if the input of the NN controller consists exclusively...

Safe control of logical control networks with random impulses.

Neural networks : the official journal of the International Neural Network Society
Under the framework of a hybrid-index model, this paper investigates safe control problems of state-dependent random impulsive logical control networks (RILCNs) on both finite and infinite horizons, respectively. By using the ΞΎ-domain method and the ...

Robust Stabilization of Linear Time-Delay Systems under Denial-of-Service Attacks.

Sensors (Basel, Switzerland)
This research examines new methods for stabilizing linear time-delay systems that are subject to denial-of-service (DoS) attacks. The study takes into account the different effects that a DoS attack can have on the system, specifically delay-independ...

Nonfragile Output Feedback Tracking Control for Markov Jump Fuzzy Systems Based on Integral Reinforcement Learning Scheme.

IEEE transactions on cybernetics
In this article, a novel integral reinforcement learning (RL)-based nonfragile output feedback tracking control algorithm is proposed for uncertain Markov jump nonlinear systems presented by the Takagi-Sugeno fuzzy model. The problem of nonfragile co...

Comparing end-effector position and joint angle feedback for online robotic limb tracking.

PloS one
Somatosensation greatly increases the ability to control our natural body. This suggests that supplementing vision with haptic sensory feedback would also be helpful when a user aims at controlling a robotic arm proficiently. However, whether the pos...