Broad Learning System (BLS) that aims to offer an alternative way of learning in deep structure is proposed this paper. Deep and suffer from a time-consuming training process because large number connecting parameters filters layers. Moreover, it encounters complete retraining if the not sufficient model system. The BLS established form flat network, where original inputs are transferred placed as "mapped features" feature nodes expanded wide sense "enhancement nodes." incremental algorithms...

Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Consequently, an effective algorithm inspired by the contrast mechanism human vision system derived kernel model presented this paper. At first stage, local map input image obtained using proposed measure which measures dissimilarity between current location its neighborhoods. In way, signal enhancement background clutter suppression are...

Because of the complexity consensus control nonlinear multiagent systems in state time-delay, most previous works focused only on linear with input time-delay. An adaptive neural network (NN) method for a class time-delay is proposed this paper. The approximation property radial basis function networks (RBFNNs) used to neutralize uncertain dynamics agents. appropriate Lyapunov-Krasovskii functional, which obtained from derivative an Lyapunov function, compensate uncertainties unknown time...

Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, which each follower agent modeled in semi-strict-feedback form. By constructing the neural network-based state observer follower, proposed method solves unmeasurable problem systems. The algorithm can guarantee that all signals system are semi-globally uniformly ultimately bounded and outputs synchronously track reference...

Smart grid is a promising power delivery infrastructure integrated with communication and information technologies. Its bi-directional electricity flow enable both utilities customers to monitor, predict, manage energy usage. It also advances environmental sustainability through the integration of vast distributed resources. Deploying such green electric system has enormous far-reaching economic social benefits. Nevertheless, increased interconnection introduce cyber-vulnerabilities into...

This paper studies an adaptive tracking control for a class of nonlinear stochastic systems with unknown functions. The considered are in the nonaffine pure-feedback form, and it is first to this disturbances. fuzzy-neural networks used approximate Based on backstepping design technique, controllers adaptation laws obtained. Compared most existing systems, proposed algorithm has fewer adjustable parameters thus, can reduce online computation load. By using Lyapunov analysis, proven that all...

In order to stabilize a class of uncertain nonlinear strict-feedback systems with full-state constraints, an adaptive neural network control method is investigated in this paper. The state constraints are frequently emerged the real-life plants and how avoid violation important task. By introducing barrier Lyapunov function (BLF) every step backstepping procedure, novel design well developed ensure that not violated. At same time, one remarkable feature minimal learning parameters employed...

After a very fast and efficient discriminative broad learning system (BLS) that takes advantage of flatted structure incremental has been developed, here, mathematical proof the universal approximation property BLS is provided. In addition, framework several variants with their modeling given. The variations include cascade, recurrent, broad-deep combination structures. From experimental results, its outperform exist algorithms on regression performance over function approximation, time...

This brief studies an adaptive neural output feedback tracking control of uncertain nonlinear multi-input-multi-output (MIMO) systems in the discrete-time form. The considered MIMO are composed n subsystems with couplings inputs and states among subsystems. In order to solve noncausal problem decouple couplings, it needs transform into a predictor higher networks utilized approximate desired controllers. By using Lyapunov analysis, is proven that all signals closed-loop system semi-globally...

A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by merging the Takagi-Sugeno (TS) into BLS. The BLS replaces feature nodes of with a group TS subsystems, and input data are processed each them. Instead aggregating outputs rules produced every subsystem one value immediately, all them sent to enhancement layer for further nonlinear transformation preserve characteristic inputs. defuzzification combined together obtain output. k -means method employed determine...

Chaotic maps are widely used in different applications. Motivated by the cascade structure electronic circuits, this paper introduces a general chaotic framework called system (CCS). Using two 1-D as seed maps, CCS is able to generate huge number of new maps. Examples and evaluations show CCS's robustness. Compared with corresponding newly generated more unpredictable have better performance, parameters, complex properties. To investigate applications CCS, we introduce pseudo-random...

Compared with the existing neural network (NN) or fuzzy logic system (FLS) based adaptive consensus methods, proposed approach can greatly alleviate computation burden because it needs only to update a few parameters online. In multiagent agreement control, uncertainties derive from unknown nonlinear dynamics are counteracted by employing NNs; state delays compensated designing Lyapunov-Krasovskii functional. Finally, on Lyapunov stability theory, is demonstrated that scheme steer...

This paper addresses the problem of adaptive tracking control for a class strict-feedback nonlinear state constrained systems with input delay. To alleviate major challenges caused by appearances full constraints and delay, an appropriate barrier Lyapunov function opportune backstepping design are used to avoid constraint violation, Pade approximation intermediate variable employed eliminate effect Neural networks estimate unknown functions in procedure. It is proven that closed-loop signals...

A novel nonlinear sliding mode control approach dealing with the formation of under-actuated ships is presented in this paper. To avoid singularity problem, state space system partitioned into two regions, one region bounded for terminal and its complement singular that. And a linear auxiliary controller designed trajectories starting from region. With application finite-time stability theory, distributed individual ship to achieve given pattern within finite time. Finally, simulation...

This paper solves the stochastically finite-time control problem for uncertain stochastic nonlinear systems in nontriangular form. The considered controlled plants are different from previous results of systems, which multiple-input and multiple-output (MIMO) with unknown functions consisting all states, disturbance, immeasurable states. Fuzzy logic a state filter used to model estimate respectively. Based on theory Itȏ differential equation, novel stability theorem is first raised. By...

In this paper, the problems of stability and tracking control for a class large-scale nonlinear systems with unmodeled dynamics are addressed by designing decentralized adaptive fuzzy output feedback approach. Because dynamic surface technique is introduced, designed controllers can avoid issue "explosion complexity," which comes from traditional backstepping design procedure that deals dynamics. addition, reduced-order observer to estimate those immeasurable states. Based on Lyapunov...

In this paper, a fuzzy adaptive approach for stochastic strict-feedback nonlinear systems with quantized input signal is developed. Compared the existing research on problem, works focus stabilization, while paper considers tracking which recovers stabilization as special case. addition, uncertain nonlinearity and unknown disturbances are simultaneously considered in feedback control systems. By putting forward new decomposition of input, relationship between established, result, major...

In recent years, emotion recognition has become a research focus in the area of artificial intelligence. Due to its irregular structure, EEG data can be analyzed by applying graphical based algorithms or models much more efficiently. this work, Graph Convolutional Broad Network (GCB-net) was designed for exploring deeper-level information graph-structured data. It used graph convolutional layer extract features input and stacks multiple regular layers relatively abstract features. The final...

In this paper, the consensus tracking control problem of second-order multiagent systems with unknown nonlinear dynamics, immeasurable states, and disturbances is investigated. The dynamics in do not satisfy matched condition. fuzzy logic system introduced to approximate adaptive high-gain observer designed estimate unmeasured states. Based on backstepping approach Lyapunov theory, a new distributed controller proposed for each agent only using information itself its neighbors. Then achieved...