Autonomous Control Reconfiguration of Aerospace Vehicle Based on Control Effectiveness Estimation

Future aerospace vehicles （ASV） are designed to fly in both inner and extra atmospheric fields, which requires autonomous adaptability to the uncertainties emanated from abrupt faults and continuously time-varying environments. An autonomous control reconfiguration scheme is presented for ASV to deal with the uncertainties on the base of control effectiveness estimation. The on-line estimation methods for the time-varying control effectiveness of linear control system are investigated. Some sufficient conditions for the estimable system are given for different cases. There are proposed corresponding on-line estimation algorithms which are proved to be convergent and robust to noise using the least-square-based methods. On the ground of fuzzy logic and linear programming, the control allocation algorithms, which are able to implement the autonomous control reconfiguration through the redundant actuators, are put forward. Finally, an integrated system is developed to verify the scheme and algorithms by way of numerical simulation and analysis.

A Decentralized Autonomous Control on Highly Redundant Robot Manipulators

The control method of highly redundant robot manipulators is introduced. A decentralized autonomous control scheme is used to guide the movement of robot manipulators so that the work done by manipulators is minimized. The method of computing pseudoinverse which needs too many complicated calculation can be avoided. Then the calculation and control of robots are simplified. At the same time system robustness/fault tolerance is achieved.

Guest Editorial for Special Issue on Autonomous Control of Unmanned Aerial Vehicles

IN recent years,unmanned aerial vehicles(UAVs)have been widely employed in different applications,both military and civilian.Especially,a fast growing civil UAV market is predicted over the next decades.However,most currently developed UAVs depend on simple control strategy.They require exact modeling of the UAVs dynamics and are vulnerable to external disturbance.Therefore,there is great

Autonomous Control Strategy of a Swarm System Under Attack Based on Projected View and Light Transmittance

In the study of a visual projection field with swarm movements,an autonomous control strategy is presented in this paper for a swarm system under attack.To ensure a fast swarm dynamic response and stable spatial cohesion in a complex environment,a new hybrid swarm motion model is proposed by introducing global visual projection information to a traditional local interaction mechanism.In the face of attackers,individuals move towards the largest free space according to the projected view of the environment,rather than directly in the opposite direction of the attacker.Moreover,swarm individuals can certainly regroup without dispersion after the attacker leaves.On the other hand,the light transmittance of each individual is defined based on global visual projection information to represent its spatial freedom and relative position in the swarm.Then,an autonomous control strategy with adaptive parameters is proposed according to light transmittance to guide the movement of swarm individuals.The simulation results demonstrate in detail how individuals can avoid attackers safely and reconstruct ordered states of swarm motion.

Managing Variable Transmittance Windowpanes byModel-Based Autonomous Control

The use of digitally activated, variable transmittance materials and artificial intelligence methods to building control will enhance the performance of buildings, and programmable components will change the traditional modes of architectural design, manufacturing and construction. In the presented key study, the architectural form and functionality of windows are revisited with a view to integrate current advances in material science, control systems engineering and human-computer interaction. The features of a building facade, involving a matrix of programmable windows that enables precise control of daylight, view and privacy in the interior of a house are discussed. Managing the variable transmittance materials of the facade by an autonomous high-level control system allows the optimization of the house performance based on real time data and the schedule of the inhabitants. Using constraint violations as a measure of success, the autonomous control of the house outperforms any existing deterministic control models.

Suggestions for flying qualities requirements of autonomous control unmanned combat aerial vehicles

There is a lack of quantitative flying qualities assessment requirements for unmanned combat aerial vehicles.The mission-oriented flying qualities evaluation approach can make up for the deficiencies of existing flying qualities specifications.Considering the control characteristics and mission requirements of autonomous control unmanned combat aerial vehicles,flying qualities assessment tasks are designed and performance standards are developed on the basis of manned aircraft flying qualities assessment tasks.Multiple sets of mathematical simulations are performed by varying the control law parameters to investigate the relationship between the control law parameter values,closed-loop aircraft system characteristics and flying qualities levels.The simulation results and closed-loop frequency domain analysis show that the existing flying qualities guidelines for manned aircraft are not fully applicable to the flying qualities assessment of autonomous control unmanned combat aerial vehicles.It is found that the combination of the bandwidth and the phase at the bandwidth frequency can define the flying qualities requirements of autonomous control unmanned aerial vehicles.The criterion boundaries of different levels are given,and the physical reasons for the formation of boundary are analysed.Our results can be applied to flying qualities assessment and design of flight control laws for autonomous control unmanned combat aerial vehicles.

Sliding Mode Control-Based Autonomous Control of a Tri-rotor Unmanned Aerial Vehicle

A nonlinear control technique for autonomous control of a tri-rotor unmanned aerial vehicle is presented in this paper.First,a comprehensive mathematical model is developed using the Newton–Euler approach for a tri-rotor,which is found to be highly nonlinear and coupled.Then,the equivalent input a±ne model is extracted by applying a suitable transformation.Finally,the sliding mode control for trajectory tracking is chosen which is immune to matched external disturbances,parametric uncertainties,and modeling errors.The proposed controller performance has been veri¯ed for appropriate inputs under wind disturbances using MATLAB,and the simulation results are presented.

A learning-based flexible autonomous motion control method for UAV in dynamic unknown environments

This paper presents a deep reinforcement learning(DRL)-based motion control method to provide unmanned aerial vehicles(UAVs)with additional flexibility while flying across dynamic unknown environments autonomously.This method is applicable in both military and civilian fields such as penetration and rescue.The autonomous motion control problem is addressed through motion planning,action interpretation,trajectory tracking,and vehicle movement within the DRL framework.Novel DRL algorithms are presented by combining two difference-amplifying approaches with traditional DRL methods and are used for solving the motion planning problem.An improved Lyapunov guidance vector field(LGVF)method is used to handle the trajectory-tracking problem and provide guidance control commands for the UAV.In contrast to conventional motion-control approaches,the proposed methods directly map the sensorbased detections and measurements into control signals for the inner loop of the UAV,i.e.,an end-to-end control.The training experiment results show that the novel DRL algorithms provide more than a 20%performance improvement over the state-ofthe-art DRL algorithms.The testing experiment results demonstrate that the controller based on the novel DRL and LGVF,which is only trained once in a static environment,enables the UAV to fly autonomously in various dynamic unknown environments.Thus,the proposed technique provides strong flexibility for the controller.

Autonomous Tracking Control for Four-Wheel Independent Steering Robot Based on Improved Pure Pursuit

Autonomous tracking control is one of the fundamental challenges in the field of robotic autonomous navigation,especially for future intelligent robots.In this paper,an improved pure pursuit control method is proposed for the path tracking control problem of a four-wheel independent steering robot.Based on the analysis of the four-wheel independent steering model,the kinematic model and the steering geometry model of the robot are established.Then the path tracking control is realized by considering the correlation between the look-ahead distance and the velocity,as well as the lateral error between the robot and the reference path.The experimental results demonstrate that the improved pure pursuit control method has the advantages of small steady-state error,fast response and strong robustness,which can effectively improve the accuracy of path tracking.

Robust H_∞ directional control for a sampled-data autonomous airship

A robust H∞ directional controller for a sampled-data autonomous airship with polytopic parameter uncertainties was proposed. By input delay approach, the linearized airship model was transformed into a continuous-time system with time-varying delay. Sufficient conditions were then established based on the constructed Lyapunov-Krasovskii functional, which guarantee that the system is mean-square exponentially stable with H∞ performance. The desired controller can be obtained by solving the obtained conditions. Simulation results show that guaranteed minimum H∞ performance γ=1.4037 and fast response of attitude for sampled-data autonomous airship are achieved in spite of the existence of parameter uncertainties.

Optimal control and energy storage for DC electric train systems using evolutionary algorithms

Electrified railways are becoming a popular transport medium and these consume a large amount of electrical energy.Environmental concerns demand reduction in energy use and peak power demand of railway systems.Furthermore,high transmission losses in DC railway systems make local storage of energy an increasingly attractive option.An optimisation framework based on genetic algorithms is developed to optimise a DC electric rail network in terms of a comprehensive set of decision variables including storage size,charge/discharge power limits,timetable and train driving style/trajectory to maximise benefits of energy storage in reducing railway peak power and energy consumption.Experimental results for the considered real-world networks show a reduction of energy consumption in the range 15%–30%depending on the train driving style,and reduced power peaks.

Application of Fuzzy Logic for Autonomous Bay Parking of Automobiles

In this paper, we investigate the control problem of autonomous bay parking system. We choose a referenced parking lot and define a suitable parking spot based on some measurements at various places. A kinetic model is set up for the convenience of analysis and simulation. The pose of the car during the parking procedure can be determined by the initial pose, the backward speed, and the steering angle of the wheel. Then, both a fuzzy speed controller and a fuzzy steering controller are designed for the bay parking. Finally, simulation results show the effectiveness of our designed controllers.

Acute Effect of Kapalbhati Yoga on Cardiac Autonomic Control Using Heart Rate Variability Analysis in Healthy Male Individuals

Kapalbhati is well known for improving cardiovascular health.But there are some reports of heart attacks while practising kapalbhati.We hypothesize that ill-effect of kapalbhati could be because of autonomic dysfunction to heart.In the present study,we aim to understand the acute effect of kapalbhati yoga on heart rate dynamics using heart rate variability(HRV)analysis.Resting heart rate(HR)varies widely in different individuals and during various physiological stresses,particularly,exercise it can go up to three-fold.These changes in heart rate are known as heart rate variability(HRV).Variability in heart rate reflects the control of autonomic system on the heart and which can be determined during brief periods of electrocardiographic(ECG)monitoring.HRV measures the effect of any physical exercise on the heart rate using time-and frequency-domain methods.Frequency-domain method involves power spectral analyses of the beat-to-beat intervals(R-R intervals)variability data.When total power vs.frequency,fast fourier transform analysis of R-R intervals data is done,it shows three well-defined peaks/rhythms in every individual,which contain different physiological information.Thus,the total spectral power of R-R intervals data can be divided into three components or bands viz.,the very low frequency(VLF)band,the low-frequency(LF)band and the high frequency(HF)band.VLF represent very long time-period physiological phenomenon like thermoregulation,circadian rhythms etc.and thus are not seen in short-term recordings like in this work.LF band power represents long period physiological rhythms in the frequency range of 0.05-0.15 Hz and LF band power increases as a consequence of sympathetic activation.HF band represent physiological rhythms in the frequency range of 0.15-0.5 Hz and they are synchronous with the respiration rate,and arise due to the intrathoracic pressure changes and mechanical vibrations caused by the breathing activity.In this work,twenty healthy male volunteers were trained in kapalbhati yoga and their ECG waveforms(2 min.)were obtained while doing kapalbhati(breathing at 1 Hz frequency for 2 min.)and were compared with the baseline(just 2 min.before the start)and post-kapalbhati(immediately 2 min.after completing the practice)HRV data.Our results showed a significant decrease in the time-domain measures i.e.,NN50,pNN50 and the mean heart rate interval during-kapalbhati when compared statistically to the respective before practice or“pre”-kapalbhati(p<0.05,student’s paired t-test)values.Frequency-domain indices showed that during-kapalbhati there is a significant increase(~48%)in the LF band power which suggests sympathetic activation and a significant increase(~88%)in the low frequency to the high frequency power ratio(LF/HF ratio)which indicates sympathetic system predominance.A significant decrease(~63%)in the HF component was also noted during-kapalbhati as compared to the“pre-kapalbhati”values which shows decrease in parasympathetic tone.Thus,these results suggest that during-kapalbhati there is drastic increase of sympathetic tone whereas parasympathetic activity is reduced.We propose these changes in autonomic system control on heart are responsible for the myocardial ischemic attacks induced during kapalbhati in some individuals.

Analysis of Efficient 32 Bit Adder Using Tree Grafting Technique

Adder with high efficiency and accuracy is the major requirement for electronic circuit design.Here the optical logic gate based adder circuit is designed for better performance analysis of optical input signals varied with the wavelength.Efficiency of the adder can be improved by increasing the speed of operation,reducing the complexity and power consumption.To maintain the high efficiency with accuracy,a new combination of adder has been proposed and tested in this work.A new adder by combining the logics of Brent Kung,Sklansky and Kogge Stone adders by Tree Grafting Technique(BSKTGT)has been tested along with individual Brent Kung,Sklansky,Kogge Stone,Knowles,Han Carlson and Ladner Fischer adders.All the existing and proposed adders have been designed and tested for efficiency with the help of Cadence platform with 45 nm technology.Efficiency in terms of Size reduction,Power reduction,Power Delay Product(PDP)and accuracy in adding 8 bit,16 bit and 32 bit values had been tested for all the adders and found that the 32 bit BSKTGT adder performed well in all aspects and have produced better efficiency with the power consumption of 52.512426μW with 3.16%of power saving over Brent Kung adder,utilised an area of 631.191 with 8.55%reduction over Kogge Stone Adder,has the cell count of 132 which is 10.61%reduction over Brent Kung Adder and PDP value of 122.6695 J,which is 0.46%less than that of the Han Carlson Adder.

Advanced Industrial Engineering in Next Generation of Manufacturing Systems

The article deals with possible approaches to the development trends in the industrial engineering in manufacturing organizations. The authors emphasize the need for integration of advanced industrial engineering in the next generation of manufacturing systems, which responds to new trends of production, innovation and advanced technology. This integration represents a sustainable development, so that humanization of work are increased, more effective use of natural and energy resources are achieved and production costs are reduced. Trends in the products manufacturing must meet both industrial engineering as well as production management. The development trends in the industrial engineering in manufacturing organizations must use methods and tools of advanced industrial engineering to achieve competitiveness. The second part of this article deals with specification of these approaches in next generation of production systems.

A homogenization-planning-tracking method to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems

Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking(HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance,multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase.The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.

Neuroanatomical Circuitry between Kidney and Rostral Elements of Brain： a Virally Mediated Transsynaptic Tracing Study in Mice

The identity of higher-order neurons and circuits playing an associative role to control renal function is not well understood. We identified specific neural populations of rostral elements of brain regions that project multisynaptically to the kidneys in 3–6 days after injecting a retrograde tracer pseudorabies virus（PRV）-614 into kidney of 13 adult male C57BL/6J strain mice. PRV-614 infected neurons were detected in a number of mesencephalic（e.g. central amygdala nucleus）, telencephalic regions and motor cortex. These divisions included the preoptic area（POA）, dorsomedial hypothalamus（DMH）, lateral hypothalamus, arcuate nucleus（Arc）, suprachiasmatic nucleus（SCN）, periventricular hypothalamus（Pe H）, and rostral and caudal subdivision of the paraventricular nucleus of the hypothalamus（PVN）. PRV-614/Tyrosine hydroxylase（TH） double-labeled cells were found within DMH, Arc, SCN, Pe H, PVN, the anterodorsal and medial POA. A subset of neurons in PVN that participated in regulating sympathetic outflow to kidney was catecholaminergic or serotonergic. PRV-614 infected neurons within the PVN also contained arginine vasopressin or oxytocin. These data demonstrate the rostral elements of brain innervate the kidney by the neuroanatomical circuitry.

Direct evidence of VEGF-mediated neuroregulation and afferent explanation of blood pressure dysregulation during angiogenic therapy

Objective:Oncocardiology is increasingly hot research field/topic in the clinical management of cancer with anti-angiogenic therapy of vascular endothelial growth factor(VEGF)that may cause cardiovascular toxicity,such as hypertension via vascular dysfunction and attenuation of eNOS/NO signaling in the baroreflex afferent pathway.The aim of the current study was to evaluate the potential roles of VEGF/VEGF receptors(VEGFRs)expressed in the baroreflex afferent pathway in autonomic control of blood pressure(BP)regulation.Methods:The distribution and expression of VEGF/VEGFRs were detected in the nodose ganglia(NG)and nucleus of tractus solitary(NTS)using immunostaining and molecular approaches.The direct role of VEGF was tested by NG microinjection under physiological and hypertensive conditions.Results:Immunostaining data showed that either VEGF or VEGFR2/VEGFR3 was clearly detected in the NG and NTS of adult male rats.Microinjection of VEGF directly into the NG reduced the mean blood pressure(MBP)dose-dependently,which was less dramatic in renovascular hypertension(RVH)rats,suggesting the VEGF-mediated depressor response by direct activation of the 1st-order baroreceptor neurons in the NG under both normal and disease conditions.Notably,this reduced depressor response in RVH rats was directly caused by the downregulation of VEGFR2,which compensated the up regulation of VEGF/VEGFR3 in the NG during the development of hypertension.Conclusion:It demonstrated for the first time that the BP-lowering property of VEGF/VEGFRs signaling via the activation of baroreflex afferent function may be a common target/pathway leading to BP dysregulation in anti-angiogenic therapy.

Digital twin-enabled smart facility management: A bibliometric review

In recent years,the architecture,engineering,construction,and facility management(FM)industries have been applying various emerging digital technologies to facilitate the design,construction,and management of infrastructure facilities.Digital twin(DT)has emerged as a solution for enabling real-time data acquisition,transfer,analysis,and utilization for improved decision-making toward smart FM.Substantial research on DT for FM has been undertaken in the past decade.This paper presents a bibliometric analysis of the literature on DT for FM.A total of 248 research articles are obtained from the Scopus and Web of Science databases.VOSviewer is then utilized to conduct bibliometric analysis and visualize keyword co-occurrence,citation,and co-authorship networks;furthermore,the research topics,authors,sources,and countries contributing to the use of DT for FM are identified.The findings show that the current research of DT in FM focuses on building information modeling-based FM,artificial intelligence(AI)-based predictive maintenance,real-time cyber–physical system data integration,and facility lifecycle asset management.Several areas,such as AI-based real-time asset prognostics and health management,virtual-based intelligent infrastructure monitoring,deep learning-aided continuous improvement of the FM systems,semantically rich data interoperability throughout the facility lifecycle,and autonomous control feedback,need to be further studied.This review contributes to the body of knowledge on digital transformation and smart FM by identifying the landscape,state-of-the-art research trends,and future needs with regard to DT in FM.

From tunnel boring machine to tunnel boring robot: perspectives on intelligent shield machine and its smart operation

Advances in intelligent shield machines reflect an evolving trend from traditional tunnel boring machines(TBMs)to tunnel boring robots(TBRs).This shift aims to address the challenges encountered by the conventional shield machine industry arising from construction environment and manual operations.This study presents a systematic review of intelligent shield machine technology,with a particular emphasis on its smart operation.Firstly,the definition,meaning,contents,and development modes of intelligent shield machines are proposed.The development status of the intelligent shield machine and its smart operation are then presented.After analyzing the operation process of the shield machine,an autonomous operation framework considering both stand-alone and fleet levels is proposed.Challenges and recommendations are given for achieving autonomous operation.This study offers insights into the essence and developmental framework of intelligent shield machines to propel the advancement of this technology.