Abstract:This paper proposes a multiple-vehicle longitude control method with considering unknown control input of the leading vehicle.First,the linearized vehicle dynamics is obtained by adopting a technique of the exact feedback linearization.Then,based on the state information of neighboring vehicles,a distributed control law is designed for each following vehicle with the bidirectional-leader communication strategy.Taking the upper bound input of the leading vehicle into account,an effective control method is proposed to guarantee the inner stability of the multiple-vehicle systems with the maximum rate of convergence.Finally,the simulation results show the effectiveness and superiority of the proposed controller design algorithm.

Abstract:For high-order multi-agent systems with nonlinear dynamics,consensus algorithms and adaptive laws based on observer mechanism are proposed in the paper.Additionally,history information of agent's states are added in consensus algorithms.Furthermore,parameter gains are decided by adaptive control laws.By applying the Lyapunov function,stability theory,graph theory and linear matrix inequalities techniques,sufficient consensus conditions for multi-agent systems are obtained.Finally,results of numerical examples are used to verify the effectiveness of the proposed algorithms.

Abstract:This paper is concerned with the consensus problem of multi-agent systems with event-triggered scheme and deception attacks.In order to alleviate the wireless communication network load,an event-triggered scheme is introduced to reduce the amount of redundant data.Due to wireless communication networks between agents are vulnerable to cyber attacks,this paper considers the influence of deception attacks.By taking the effects of deception attacks into account,the mathematical model of multi-agent systems with event-triggered scheme and deception attacks is established.Based on the constructed model,through the utilization of Lyapunov stability theory,multi-agent approach and linear matrix inequalities,the sufficient conditions are acquired which can guarantee consensus of the system and the designed algorithm of the controller is obtained,respectively.Finally,the feasibility of the proposed method is verified by a simulated example.

Abstract:We performed research on a quadrotor with tiltable-rotors,which has full controllability over the position and orientation,and established its dynamics system.To handle the system's strong nonlinearity problem,a nonlinear separation strategy was utilized to decompose the nonlinear system into a linear dynamic subsystem and a nonlinear static system by constructing intermediate control.Subsequently,linear quadratic regulator with small calculation and easy hardware implementation was designed only for linear dynamic subsystem while real control including tilting angle and motor speed was mapped from intermediate control by calculating the input nonlinear static subsystem.Simulation results illustrate that LQR flight controller based on nonlinear separation strategy not only performs well under a stable control,but also in independently tracking control of position and orientation.

Abstract:In this paper,the global synchronization problem of general linear complex networks is analyzed by combining the event-triggered control strategy with the aperiodically intermittent pinning control scheme.By designing an event-triggered condition and the rules for selecting the controlled nodes,the pinning node set can be updated under certain conditions,which not only greatly improves the efficiency of networks synchronization,but also avoids the deficiencies caused by random selection of controlled node set in existing research.Furthermore,a simple Lyapunov function is constructed,and the stability theory and differential inequality are applied,some sufficient conditions for the asymptotically exponential synchronization of the networks are obtained through rigorous mathematical analysis.At the same time,the infinitely fast switching of the pinning node set is also avoided.

Abstract:In this paper,the fixed-time mixed outer synchronization between two complex dynamical networks are studied.By using suitable controllers,we achieve the fixed-time mixed outer synchronization between two complex networks based on the fixed-time stability theory.Finally,the numerical simulations are performed to illustrate the effectiveness and feasibility of our proposed control approach.

Abstract:By utilizing discontinuous protocols,this paper considers the finite-time and fixed-time consensus of multi-agent systems.Based on differential inclusion,set-value map and Lyapunov stability method,finite-time and fixed-time consensus criteriaof multi-agent systems are given under a unified framework.Simulation experiments are given to verify the effectiveness of the protocols.

Abstract:In a real world scenario,several complex systems are represented by a group of interdependent network systems,and not by a single network.This paper focuses on the synchronization control of corresponding nodes in two-layer heterogeneous networks with stochastic perturbations and mixed delays.Based on the LaSalle-type invariance principle and the Lyapunov stability theory,the paper derives sufficient conditions for global asymptotic synchronization by applying the pinning control,which only controls a small fraction of the nodes.To reduce the gain of feedback control,the synchronization conditions of two-layer heterogeneous networks is further weakened by adopting the adaptive control scheme.Finally,the effectiveness of the theoretical results is verified by numerical simulations.

Abstract:To solve the uncertainty problems in traffic assignment,this paper established a method of quantifying the uncertainty in traffic assignment model based on Wardrop user equilibrium principle and Beckman traffic assignment model.The model uses the upper and lower limits of OD estimation results under different confidence levels as inputs,and subsequently uses the Frank-Wolf algorithm to solve the model to obtain link traffic flow intervals under different confidence levels to quantify uncertainty in traffic assignment.A case study utilizing a regional road network in Nanjing is performed,and the results were evaluated using the width flow ratio R and the kickoff percentage (KP) as the performance measures.The evaluation results show that the proposed method can effectively compute the confidence intervals of the road link flow,thereby quantifying the uncertainty in traffic assignment.

Abstract:In this paper,we mainly discuss the quasi-synchronization problem of a class of fractional-order memristor-based neural networks with multiple transmission delays and leakage delay under parameter mismatches.Firstly,the delay linear feedback controller is given,then according to the theory of fractional-order differential inclusion,set-valued maps,fractional-order differential inequality theory and so on,the conditions for the master-slave systems to reach the quasi-synchronization and the corresponding error bounds are obtained.Finally,some corresponding numerical simulations are given to demonstrate the effectiveness of the obtained results.

Abstract:This paper mainly investigates finite-time synchronization control of chaotic systems with multi-switching mode.For multiple real chaotic systems with different orders,its multi-switching synchronization behavior is investigated and finite-time combination multi-switching synchronization is defined,and a class of finite-time control schemes is designed,which can realize fast synchronization,when sufficient conditions for finite-time stability of error systems are provided.Finally,simulation results show that the proposed control scheme has fast convergence and reasonable validity.

Abstract:This paper focuses on the study of H_∞ state estimation of static neural networks having leakage delay.With the skills to construct Lyapunov-Krasovskii functionals,a state estimator is designed for the estimation of H_∞ performance,and the results are derived without applying differentiability on time-varying delays.Finally,a numerical example is provided to demonstrate the effectiveness and advantages of the obtained results.

Abstract:Ring structures are widely used in neural networks,and previous research with respect to neural dynamic bifurcation were confined to models with single-ring structure.Notably,neural networks are composed of thousands of neurons coupled together,and these structures are so complex that they cannot be accurately described through only a single-ring structure,and therefore is more practical for investigating neural network models with multiple ring topology.In this paper,an asymmetric model with double-ring neural structure is proposed,and the stability and Hopf bifurcation of the model are investigated.Numerical simulations are subsequently actualized to corroborate the theoretical results.

Abstract:Sensitivity to noises and outliers and inferior robustness are the primary problems associated with extreme learning machine(ELM).Based on the 1-norm loss function,a truncated 1-norm loss function is proposed to suppress the effects of noises and outliers.A robust ELM model with truncated 1-norm loss function is established.The corresponding optimization problem is solved by iterative re-weighted algorithm.Four simulated data sets and nine real-world data sets are used to verify the validity of the proposed model.The numerical results show that the generalization performance of robust ELM in noisy environment is superior to that of the compared methods and has superior robustness,especially in the case of a substantial proportion of outliers.

Abstract:With the large-scale wind power connected into the power systems,the intermittency and randomness of wind power have a great impact on the stability of the power systems.Therefore,the accurate prediction of wind power has become one of the most important ways to solve this problem.In this paper,considering the timing memory characteristics of long short-term memory (LSTM) network,by combining wavelet decomposition and LSTM network,an ultra-short-term probability prediction model for wind power based on wavelet-LSTM network is proposed.Firstly,wavelet decomposition is used to smooth the sequence of the original time sequence.Then the LSTM network prediction model for the sequence samples is developed.By using the maximum likelihood estimate method,the Gaussian distribution function of prediction error can be estimated.Thus the probability prediction of wind power in the future 4 hours could be realized.Finally,based on the wind farm data in Northeast China,simulation results show that wavelet decomposition with deep learning method can improve the accuracy of prediction.The interval reliability of probability prediction is also improved.

Abstract:In this paper,a design scheme for the generation of multi-wing chaotic attractors by adjusting the threshold of a class of state-dependent switched systems is proposed.First,two Lorenz-like subsystems are constructed,and based on these two subsystems,threshold-dependent switching law is designed,and a state-dependent switched system is constructed.Finally,by adjusting the threshold of the switched system,the number and distribution of saddle-focus equilibrium points of the switched system can be changed.Therefore,the constructed switched system can generate chaotic attractors with 4-6-8 wings.In addition,the analog circuit of the switched system is designed by analyzing the state equations of the switched system.The simulation results of the analog circuit are consistent with those of numerical simulation.The experimental results show that the proposed design scheme provides a method of generating multi-wing chaotic attractors without increasing the dimension of the system or designing complex nonlinear functions.

Abstract:The rapid development of intelligent transportation system (ITS) applications demands high quality traffic data.However,presence of abnormal data in the raw data acquired through traffic data collection techniques is inevitable,thereby reducing the validity of traffic data and degrading the performance of ITS applications.In this paper,concerning the traffic data collected using radio frequency identification (RFID)-based traffic data collection technique,a series of evaluation measures are proposed.Based on the characteristics of these measures and comprehensively considering the applicability conditions,advantages and disadvantages of each weight vector,an IOWA operator-based comprehensive evaluation method is proposed.Based on an application of the method to real world RFID data,the proposed method is demonstrated to be effective in evaluating the RFID-based traffic data.

Abstract:Accurate determination of the severity of secondary equipment defects in power grid can provide an important basis for the operation and maintenance of equipment.Therefore,in this paper,to address problems such as large quantity of defective data features,and the great difficulty of using error-prone human judgment as an evaluation parameter,a defect classification method based on XGBoost (eXtreme Gradient Boosting) is proposed to improve the accuracy of defect classification of secondary equipment.First,a series of pre-processing work,such as removing outliers and coding,is performed on the secondary equipment historical defect data,and the characteristics highly correlated with equipment defects are extracted to establish the feature index set.Subsequently,the XGBoost model is trained and optimized using historical defect data.Finally,the trained classification model is used to realize the accurate classification of secondary equipment defects.Based on the secondary equipment defective data of a power plant,simulation results are presented to illustrate the effectiveness of the proposed algorithm and are compared with those of traditional classifiers (decision tree,logistic regression,etc.).Simulation results show that XGBoost can accurately determine the defect degree of secondary equipment,to assist the maintenance and management of equipment.

Abstract:This paper proposes a new automatic system for the application of artificial intelligence and other technologiesto field rescues.When peopleare trapped inthe vast wilderness and maritime environments,apart from relying on their own abilities and equipment,an effective external and timely rescue iscritical in improving their chances of survival.An automatic field rescue system recognizes the alarm produced byautomatic and manual alarm devices,which triggers the operation of the entire system.The automatic rescue device can determine the positionvia a positioning module,and performs a rescue by moving an actuator to the vicinity of a portable device.This device can also issue a beacon.The target-guided signalis detected by the automatic rescue system using a sensor.It can determine the coordinates of the rescue(using phase detection technology),plan the path,achieve more accurate positioning,and perform the rescue.The artificial rescue system can be controlled at critical moments.This device can significantly reduce the time taken for a field rescue,and greatly improve the overall efficiency of the process.Based on physical production and testing,the operability and practicability of the system are established.

Abstract:With the aging of the population and the pursuit of an improved quality of life among the disabled,the user requirements for wheelchair function have become diversified and intelligent.To improve the ability of wheelchair users to care for themselves and be independent,this paper proposes an intelligent wheelchair control system.The system is controlled by an STM32 single-chip microcomputer.It adopts modular and systematic design.The power module,rocker module,obstacle avoidance module,and drive module form an organic whole.The modules work together and coordinate with each other to form a safe and reliable wheelchair control system.The transmission and reception of data between modules are realized by a communication module.The wheelchair is designed to operate under both manual and automatic control,which the wheelchair user can exploit to live independently without care from others.The operation of the wheelchair is safe and reliable.