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Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics.

IEEE transactions on cybernetics
In this article, we investigate the self-learning robust control synthesis and tracking design of general uncertain dynamical systems. Based on the adaptive critic learning, the robust stabilization method is developed with the help of conducting pro...

An Approximate Neuro-Optimal Solution of Discounted Guaranteed Cost Control Design.

IEEE transactions on cybernetics
The adaptive optimal feedback stabilization is investigated in this article for discounted guaranteed cost control of uncertain nonlinear dynamical systems. Via theoretical analysis, the guaranteed cost control problem involving a discounted utility ...

Distributed Control of Time-Varying Signed Networks: Theories and Applications.

IEEE transactions on cybernetics
Signed networks admitting antagonistic interactions among agents may polarize, cluster, or fluctuate in the presence of time-varying communication topologies. Whether and how signed networks can be stabilized regardless of their sign patterns is one ...

Sampled-Data Stabilization for Boolean Control Networks With Infinite Stochastic Sampling.

IEEE transactions on cybernetics
Sampled-data state feedback control with stochastic sampling periods for Boolean control networks (BCNs) is investigated in this article. First, based on the algebraic form of BCNs, stochastic sampled-data state feedback control is applied to stabili...

Neural Matrix Factorization Recommendation for User Preference Prediction Based on Explicit and Implicit Feedback.

Computational intelligence and neuroscience
Explicit feedback and implicit feedback are two important types of heterogeneous data for constructing a recommendation system. The combination of the two can effectively improve the performance of the recommendation system. However, most of the curr...

Parametric Neural Network-Based Model Free Adaptive Tracking Control Method and Its Application to AFS/DYC System.

Computational intelligence and neuroscience
This paper deals with adaptive nonlinear identification and trajectory tracking problem for model free nonlinear systems via parametric neural network (PNN). Firstly, a more effective PNN identifier is developed to obtain the unknown system dynamics,...

Exponential synchronization for variable-order fractional discontinuous complex dynamical networks with short memory via impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper considers the exponential synchronization issue for variable-order fractional complex dynamical networks (FCDNs) with short memory and derivative couplings via the impulsive control scheme, where dynamical nodes are modeled to be discontin...

Shape Sensing of Hyper-Redundant Robots Using an AHRS IMU Sensor Network.

Sensors (Basel, Switzerland)
The paper proposes a novel approach for shape sensing of hyper-redundant robots based on an AHRS IMU sensor network embedded into the structure of the robot. The proposed approach uses the data from the sensor network to directly calculate the kinema...

Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) Systems.

Sensors (Basel, Switzerland)
The current wireless communication infrastructure has to face exponential development in mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems and their variants (i.e., Multi-User MIMO and Massive MIMO) are the...

Observer-based adaptive neural tracking control for a class of nonlinear systems with prescribed performance and input dead-zone constraints.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the problem of output feedback neural network (NN) learning tracking control for nonlinear strict feedback systems subject to prescribed performance and input dead-zone constraints. First, an NN is utilized to approximate the ...