AIMC Topic: Feedback

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Synchronization of Memristor-Based Coupling Recurrent Neural Networks With Time-Varying Delays and Impulses.

IEEE transactions on neural networks and learning systems
Synchronization of an array of linearly coupled memristor-based recurrent neural networks with impulses and time-varying delays is investigated in this brief. Based on the Lyapunov function method, an extended Halanay differential inequality and a ne...

MEMS sensors for assessing flow-related control of an underwater biomimetic robotic stingray.

Bioinspiration & biomimetics
A major difference between manmade underwater robotic vehicles (URVs) and undersea animals is the dense arrays of sensors on the body of the latter which enable them to execute extreme control of their limbs and demonstrate super-maneuverability. The...

Undamped Oscillations Generated by Hopf Bifurcations in Fractional-Order Recurrent Neural Networks With Caputo Derivative.

IEEE transactions on neural networks and learning systems
In this paper, a fractional-order recurrent neural network is proposed and several topics related to the dynamics of such a network are investigated, such as the stability, Hopf bifurcations, and undamped oscillations. The stability domain of the tri...

Finite-time synchronization for memristor-based neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
Memristive network exhibits state-dependent switching behaviors due to the physical properties of memristor, which is an ideal tool to mimic the functionalities of the human brain. In this paper, finite-time synchronization is considered for a class ...

Periodic synchronization control of discontinuous delayed networks by using extended Filippov-framework.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the periodic synchronization problem for a general class of delayed neural networks (DNNs) with discontinuous neuron activation. One of the purposes is to analyze the problem of periodic orbits. To do so, we introduce new...

Adaptive Neural Output Feedback Control of Output-Constrained Nonlinear Systems With Unknown Output Nonlinearity.

IEEE transactions on neural networks and learning systems
This paper addresses the problem of adaptive neural output-feedback control for a class of special nonlinear systems with the hysteretic output mechanism and the unmeasured states. A modified Bouc-Wen model is first employed to capture the output hys...

Mechatronic design and locomotion control of a robotic thunniform swimmer for fast cruising.

Bioinspiration & biomimetics
This paper presents mechatronic design and locomotion control of a biomimetic robotic fish that swims using thunniform kinematics for fast cruising. Propulsion of the robotic fish is realized with a parallel four-bar propulsive mechanism that deliver...

Finite-Horizon Near-Optimal Output Feedback Neural Network Control of Quantized Nonlinear Discrete-Time Systems With Input Constraint.

IEEE transactions on neural networks and learning systems
The output feedback-based near-optimal regulation of uncertain and quantized nonlinear discrete-time systems in affine form with control constraint over finite horizon is addressed in this paper. First, the effect of input constraint is handled using...

Peaking-Free Output-Feedback Adaptive Neural Control Under a Nonseparation Principle.

IEEE transactions on neural networks and learning systems
High-gain observers have been extensively applied to construct output-feedback adaptive neural control (ANC) for a class of feedback linearizable uncertain nonlinear systems under a nonlinear separation principle. Yet due to static-gain and linear pr...

Adaptive Robust Output Feedback Control for a Marine Dynamic Positioning System Based on a High-Gain Observer.

IEEE transactions on neural networks and learning systems
This paper develops an adaptive robust output feedback control scheme for dynamically positioned ships with unavailable velocities and unknown dynamic parameters in an unknown time-variant disturbance environment. The controller is designed by incorp...