An Overview of Finite/Fixed-Time Control and Its Application in Engineering Systems

The finite/fixed-time stabilization and tracking control is currently a hot field in various systems since the faster convergence can be obtained. By contrast to the asymptotic stability,the finite-time stability possesses the better control performance and disturbance rejection property. Different from the finite-time stability, the fixed-time stability has a faster convergence speed and the upper bound of the settling time can be estimated. Moreover, the convergent time does not rely on the initial information.This work aims at presenting an overview of the finite/fixed-time stabilization and tracking control and its applications in engineering systems. Firstly, several fundamental definitions on the finite/fixed-time stability are recalled. Then, the research results on the finite/fixed-time stabilization and tracking control are reviewed in detail and categorized via diverse input signal structures and engineering applications. Finally, some challenging problems needed to be solved are presented.

Decentralized Optimal Control and Stabilization of Interconnected Systems With Asymmetric Information

The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time.The main challenge lies in three aspects:Firstly,the asymmetric information results in coupling between control and estimation and failure of the separation principle.Secondly,two extra unknown variables are generated by asymmetric information(different information filtration)when solving forward-backward stochastic difference equations.Thirdly,the existence of additive noise makes the study of mean-square boundedness an obstacle.The adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise.A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.

Prediction and Output Estimation of Pattern Moving in Non-Newtonian Mechanical Systems Based on Probability Density Evolution

A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.

Model Parameters Identification and Backstepping Control of Lower Limb Exoskeleton Based on Enhanced Whale Algorithm

Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to construct.Hence,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model parameters.Meanwhile,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical constraints.Then a backstepping controller based on the identified model is adopted to improve the human-robot wearable comfortable performance under cooperative motion.Finally,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons platform.The knee joint motion achieves a steady-state response after 0.5 s.Meanwhile,the position error of hip joint response is less than 0.03 rad after 0.9 s.In addition,the steady-state human-robot interaction torque of the two joints is constrained within 15 N·m.This research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model parameters.Furthermore,an enhanced mutation strategy is adopted to avoid whale evolution’s unsatisfactory local optimal value.

Design and verification of an improved experimental platform for stray current in urban rail transit

With the rapid development of urban rail transit,there have been an urgent problem of excessive stray current.Because the stray current distribution is random and difficult to verify in the field,we designed an improved stray current experimental platform by replacing the simulated aqueous solution with a real soil environment and by calculating the transition resistance by measuring the soil resistivity,which makes up for the defects in the previous references.Firstly,the mathematical models of rail-drainage net and rail-drainage netground were established,and the analytical expressions of current and voltage of rail,drainage net and other structures were derived.In addition,the simulation model was built,and the mathematical analysis results were compared with the simulation results.Secondly,the accuracy of the improved stray current experimental platform was verified by comparing the measured and simulation results.Finally,based on the experimental results,the influence factors of stray current were analyzed.The relevant conclusions provide experimental data and theoretical reference for the study of stray current in urban rail transit.

Enhanced UAV Pursuit-Evasion Using Boids Modelling:A Synergistic Integration of Bird Swarm Intelligence and DRL

TheUAV pursuit-evasion problem focuses on the efficient tracking and capture of evading targets using unmanned aerial vehicles(UAVs),which is pivotal in public safety applications,particularly in scenarios involving intrusion monitoring and interception.To address the challenges of data acquisition,real-world deployment,and the limited intelligence of existing algorithms in UAV pursuit-evasion tasks,we propose an innovative swarm intelligencebased UAV pursuit-evasion control framework,namely“Boids Model-based DRL Approach for Pursuit and Escape”(Boids-PE),which synergizes the strengths of swarm intelligence from bio-inspired algorithms and deep reinforcement learning(DRL).The Boids model,which simulates collective behavior through three fundamental rules,separation,alignment,and cohesion,is adopted in our work.By integrating Boids model with the Apollonian Circles algorithm,significant improvements are achieved in capturing UAVs against simple evasion strategies.To further enhance decision-making precision,we incorporate a DRL algorithm to facilitate more accurate strategic planning.We also leverage self-play training to continuously optimize the performance of pursuit UAVs.During experimental evaluation,we meticulously designed both one-on-one and multi-to-one pursuit-evasion scenarios,customizing the state space,action space,and reward function models for each scenario.Extensive simulations,supported by the PyBullet physics engine,validate the effectiveness of our proposed method.The overall results demonstrate that Boids-PE significantly enhance the efficiency and reliability of UAV pursuit-evasion tasks,providing a practical and robust solution for the real-world application of UAV pursuit-evasion missions.

Research on Detection of Food additives Based on Terahertz Spectroscopy and Analytic Hierarchy Process

Terahertz time-domain spectroscopy is a kind of far-infrared spectroscopy technology,and its spectrum reflects the internal properties of substances with rich physical and chemical information,so the use of terahertz waves can be used to qualitatively identify food additives containing nitrogen elements.Analytic hierarchy process(AHP)was originally used to solve evaluation-type problems,and this paper introduces it into the field of terahertz spectral qualitative analysis,proposes a terahertz time-domain spectral qualitative identification method combined with analytic hierarchy process,and verifies the feasibility of the method by taking four common food additives(xylitol,L-alanine,sorbic acid,and benzoic acid)and two illegal additives(melamine,and Sudan Red No.I)as the objects of study.Firstly,the collected terahertz time-domain spectral data were pre-processed and transformed into a data set consisting of peaks,peak positions,peak numbers and overall trends;then,the data were divided into comparison and test sets,and a qualitative additive identification model incorporating analytic hierarchy process was constructed and parameter optimisation was performed.The results showed that the qualitative identification accuracies of additives based on single factors,i.e.,overall trend,peak value,peak position,and peak number,were 80.23%,70.93%,67.44%,and 40.70%,respectively,whereas the identification accuracy of the analytic hierarchy process qualitative identification method based on multi-factors could be improved to 92.44%.In addition,the fuzzy characterisation of the absorption spectrum data was binarised in the data pre-processing stage and used as the base data for the overall trend,and the recognition accuracy was improved to 94.19%by combining the fuzzy characterisation method of such data with the hierarchical analysis qualitative recognition model.The results show that it is feasible to use terahertz technology to identify different varieties of additives,and this paper constructs a hierarchical analytical qualitative model with better effect,which provides a new means for food additives detection,and the method is simple in steps,with a small demand for samples,which is suitable for the rapid detection of small samples.

Electromagnetic-thermal Coupled Analyses and Joint Optimisation of Electrically-excited Flux-switching Linear Machines

Electrically-excited flux-switching machines are advantageous in simple and reliable structure,good speed control performance,low cost,etc.,so they have arouse wide concerns from new energy field.However,they have much lower torque density/thrust density compared with the same type PM machines.To overcome this challenge,electromagnetic-thermal coupled analysis is carried out with respect to water-cooled electrically-excited flux-switching linear machines(EEFSLM).The simulation results indicate that the conventional fixed copper loss method(FCLM)is no longer suitable for high thrust density design,since it is unable to consider the strong coupling between the electromagnetic and thermal performance.Hence,a multi-step electromagnetic-thermal joint optimisation method is proposed,which first ensures the consistency between the electromagnetic and thermal modelling and then considers the effect of different field/armature coil sizes.By using the proposed joint optimisation method,it is found that the combination of relatively large size of field coil and relatively low field copper loss is favourable for achieving high thrust force for the current EEFSLM design.Moreover,the thrust force is raised by 13-15%compared with using the FCLM.The electromagnetic and thermal performance of the EEFSLM is validated by the prototype test.

A survey of brain-inspired artificial intelligence and its engineering

Exploring the human brain is perhaps the most challenging and fascinating scientific issue in the 21st century.It will facilitate the development of various aspects of the society,including economics,education,health care,national defense and daily life.The artificial intelligence techniques are becoming useful as an alternate method of classical techniques or as a component of an integrated system.They are used to solve complicated problems in various fields and becoming increasingly popular nowadays.Especially,the investigation of human brain will promote the artificial intelligence techniques,utilizing the accumulating knowledge of neuroscience,brain-machine interface techniques,algorithms of spiking neural networks and neuromorphic supercomputers.Consequently,we provide a comprehensive survey of the research and motivations for brain-inspired artificial intelligence and its engineering over its history.The goals of this work are to provide a brief review of the research associated with brain-inspired artificial intelligence and its related engineering techniques,and to motivate further work by elucidating challenges in the field where new researches are required.

Obstacle Avoidance of Flapping⁃Wing Air Vehicles Based on Optical Flow and Fuzzy Control

The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Farneback algorithm is used to calculate the optical flow field of the first-view video frames taken by the on-board image transmission camera.Based on the optical flow information,a fuzzy obstacle avoidance controller is then designed to generate the FWAV steering commands.Experimental results show that the proposed obstacle avoidance method can accurately identify obstacles and achieve obstacle avoidance for FWAVs.

Overall Life Cycle Comprehensive Assessment of Pneumatic and Electric Actuator

Pneumatic actuators and electric actuators have almost been applied to all manufacturing industries. The two kinds of actuators can replace each other in most fields, such as the point to point transmission occasion and some rotating occasions. However, there are very few research results about the advantages and disadvantages of two kinds of actuators under the same working conditions so far. In this paper, a novel comprehensive assessment method, named as overall life cycle comprehensive assessment （OLCCA）, is proposed for comparison and assessment of pneumatic and electric actuators. OLCCA contains mechanical properties evaluation （MPE）, life cycle cost analysis based on users （LCCABOU） and life cycle environmental impact analysis （LCEIA） algorithm in order to solve three difficult problems： mechanical properties assessment, cost analysis and environmental impact assessment about actuators. The mechanical properties evaluation of actuators is a multi-objective optimization problem. The fuzzy data quantification and information entropy methods are combined to establish MPE algorithm of actuators. Two kinds of pneumatic actuators and electric actuators with similar bearing capacity and similar work stroke were taken for example to verify the correctness of MPE algorithm. The case study of MPE algorithm for actuators verified its correctness. LCCABOU for actuators is also set up. Considering cost complex structure of pneumatic actuators, public device cost even method （PDCEM） is firstly presented to solve cost division of public devices such as compressors, aftercooler, receivers, etc. LCCABOU method is also effective and verified by the three groups of pneumatic actuators and electric actuators. Finally, LCEIA model of actuators is established for the environmental impact assessment of actuators. LCEIA data collection method and model establishment procedure for actuators are also put forward. With Simapro 7, LCEIA comparison results of six actuators can be obtained： Fossil fuels are the major environmental factor of pneumatic and electric actuators; Environmental impact of electric actuator is large than one of pneumatic actuator under the similar mechanical properties and working conditions of pneumatic and electric actuators. The results are correct and correspond with the actual mechanical properties of actuators. This paper proposes a comprehensive evaluation method of the actuators, which can solve the critical problem that similar electromechanical products are very difficult to be compared with each other from the angle of performance, cost and environment impact.

Methods to Evaluate and Measure Power of Pneumatic System and Their Applications

Pneumatic system has been widely used throughout industry, and it consumes more than billions kW h of electricity one year all over the world. So as to improve the efficiency of pneumatic system, its power evaluation as well as measurement methods should be proposed, and their applicability should be validated. In this paper, firstly, power evaluation and measurement methods of pneumatic system were introduced for the first time. Secondly, based on the proposed methods, power distributions in pneumatic system was analyzed. Thirdly, through the analysis on pneumatic efficiencies of typical compressors and pneumatic components, the applicability of the proposed methods were validated. It can be concluded that, first of all, the proposed methods to evaluation and measurement the power of pneumatic system were efficient. Furthermore, the pneumatic power efficiencies of pneumatic system in the air production and cleaning procedure are respectively about 35%–75% and 85%–90%. Moreover, the pneumatic power efficiencies of pneumatic system in the transmission and consumption procedures are about 70%–85% and 10%–35%. And the total pneumatic power efficiency of pneumatic system is about 2%–20%, which varies largely with the system configuration. This paper provides a method to analyze and measure the power of pneumatic system, lay a foundation for the optimization and energy-saving design of pneumatic system.

Stability and Stabilization of Networked Control Systems with Bounded Packet Dropout

在这份报纸，与围住的包退学学生一起的联网的控制系统(NCS ) 的一个类的稳定性和稳定问题被调查。一条反复的途径被建议作为 Markovian 与围住的包退学学生一起为 NCS 建模跳线性系统(MJLS ) 。MJLS 的转变可能性由于网络的复杂性是部分未知的。在考虑下面的系统是更一般的，它完全用盖住系统知道并且完全未知的转变可能性作为二个空间案例。而且， sensor-to-controller 和 controller-to-actuator 包退学学生同时被考虑。为内在的系统的随机的稳定性和稳定的足够的条件经由线性矩阵不平等(LMI ) 被导出明确的表达。最后，二个解说性的例子被给表明建议结果的有效性。

Visual Object Tracking and Servoing Control of a Nano-Scale Quadrotor:System,Algorithms,and Experiments

There are two main trends in the development of unmanned aerial vehicle(UAV)technologies:miniaturization and intellectualization,in which realizing object tracking capabilities for a nano-scale UAV is one of the most challenging problems.In this paper,we present a visual object tracking and servoing control system utilizing a tailor-made 38 g nano-scale quadrotor.A lightweight visual module is integrated to enable object tracking capabilities,and a micro positioning deck is mounted to provide accurate pose estimation.In order to be robust against object appearance variations,a novel object tracking algorithm,denoted by RMCTer,is proposed,which integrates a powerful short-term tracking module and an efficient long-term processing module.In particular,the long-term processing module can provide additional object information and modify the short-term tracking model in a timely manner.Furthermore,a positionbased visual servoing control method is proposed for the quadrotor,where an adaptive tracking controller is designed by leveraging backstepping and adaptive techniques.Stable and accurate object tracking is achieved even under disturbances.Experimental results are presented to demonstrate the high accuracy and stability of the whole tracking system.

A Survey of Human-centered Intelligent Robots:Issues and Challenges

Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.

Vibration Control of a High-Rise Building Structure:Theory and Experiment

In this study,an innovative solution is developed for vibration suppression of the high-rise building.The infinite dimensional system model has been presented for describing high-rise building structures which have a large inertial load with the help of the Hamilton’s principle.On the basis of this system model and with the use of the Lyapunov’s direct method,a boundary controller is proposed and the closed-loop system is uniformly bounded in the time domain.Finally,by using the Smart Structure laboratory platform which is produced by Quancer,we conduct a set of experiments and find that the designed method is resultful.

Saturated Adaptive Output-Constrained Control of Cooperative Spacecraft Rendezvous and Docking

This paper investigates the robust relative pose control for spacecraft rendezvous and docking with constrained relative pose and saturated control inputs.A barrier Lyapunov function is used to ensure the constraints of states,so that the computational singularity of the inverse matrix in control command can be avoided,while a linear auxiliary system is introduced to handle with the adverse effect of actuator saturation.The tuning rules for designing parameters in control command and auxiliary system are derived based on the stability analysis of the closed-loop system.It is proved that all closed-loop signals always keep bounded,the prescribed constraints of relative pose tracking errors are never violated,and the pose tracking errors ultimately converge to small neighborhoods of zero.Simulation experiments validate the performance of the proposed robust saturated control strategy.

Modeling research of train tracing based on UML sequence diagram and UPPAAL

The zone control subsystem is a real-time control system,which requests the correctness of the control process.Train tracing scene is an important function of the zone controller(ZC)in the communication based train control(CBTC)system.In the process of deep development and design,to ensure the safety of the system,the system needs to be modeled,simulated and verified to discover the system design flaws.Unified modeling language(UML)is combined with timed automata,and timed automata network models of train-filter and train tracing demarcation-point are established.At the same time,the verification tool of UPPAAL is applied to simulate the system,and verify the requirements of performance and function of system.The results show that the function of train tracing demaraction-point meets the requirements of system safety and limited activity.Therefore,the method is feasible and can be applied to the modeling and verification of other scenes of train control system.

The influence of temperature on flow-induced forces on quartz-crystal-microbalance sensors in a Chinese liquor identification electronic-nose: three-dimensional computational fluid dynamics simulation and analysis

An electronic-nose is developed based on eight quartz-crystal-microbalance (QCM) gas sensors in a sensor box, and is used to detect Chinese liquors at room temperature. Each sensor is a highly-accurate and highly-sensitive oscillator that has experienced airflow disturbances under the condition of varying room temperatures due to unstable flow-induced forces on the sensors surfaces. The three-dimensional (3D) nature of the airflow inside the sensor box and the interactions of the airflow on the sensors surfaces at different temperatures are studied by computational fluid dynamics (CFD) tools. Higher simulation accuracy is achieved by optimizing meshes, meshing the computational domain using a fine unstructural tetrahedron mesh. An optimum temperature, 30 ℃, is obtained by analyzing the distributions of velocity streamlines and the static pressure, as well as the flow-induced forces over time, all of which may be used to improve the identification accuracy of the electronic-nose for achieving stable and repeatable signals by removing the influence of temperature.

Validation of Flight Control Law Based on LFT and Structured Singular Value

The main goal of flight clearance is to use the structured singular value （ μ ） analysis of the flight control system when some parameters in the system vary in a certain range. As the p-analysis can only be done on a linear fractional transformation （LFT） model, the first step of flight clearance is to generate the LFT model of the flight control system. In this paper, based on the introduction of basic theory of LFT and μ-analysis, an X-fighter is chosen as an example to utilize the proposed methods. In order to realize the flight clearance process automatically, a novel soRware package based on MATLAB programming language is developed. The results of simulation experiments validate the feasibility and effectiveness of the novel methods proposed in this paper.