Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always ...Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.展开更多
Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a netwo...Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.展开更多
In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(...In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.展开更多
2025 has,so far,been a year of surprises.The United States under its reelected president,Donald Trump,has not only ramped up the U.S.trade war with China that he began in his first term,but has also unleashed a verbal...2025 has,so far,been a year of surprises.The United States under its reelected president,Donald Trump,has not only ramped up the U.S.trade war with China that he began in his first term,but has also unleashed a verbal assault and a barrage of tariffs against its neighbors,Canada and Mexico.It appears the age of globalization and rules-based free trade is over,at least as far as the giant U.S.economy is concerned.展开更多
Trajectory planning under uncertain dynamics is critical for safety-critical systems like Unmanned Aerial Vehicles(UAVs),where uncertainties in aerodynamic force and control surface failure can lead to mission failure...Trajectory planning under uncertain dynamics is critical for safety-critical systems like Unmanned Aerial Vehicles(UAVs),where uncertainties in aerodynamic force and control surface failure can lead to mission failure.This paper proposes a Multi-stage Robust Optimization(MRO)framework to address nonlinear trajectory planning with bounded but unknown parameters.By integrating first-order sensitivity analysis and sequential optimization,the proposed method ensures robustness against worst-case parameter deviations while maintaining high terminal accuracy.Unlike existing approaches,this paper explicitly quantifies uncertainty propagation through sensitivity bounds and divides long-term planning into sub-stages to reduce cumulative errors.Simulations on a UAV model with uncertainties in aerodynamic coefficients,wind fields and coefficients of control inputs demonstrate that MRO achieves high terminal state accuracy and strong robustness.展开更多
This paper proposes an extension of the Modified-Plant ADRC(MP-ADRC)strategy to broaden its application to minimum phase dynamical systems.The main features of the MP-ADRC method are the inclusion of a constant gain i...This paper proposes an extension of the Modified-Plant ADRC(MP-ADRC)strategy to broaden its application to minimum phase dynamical systems.The main features of the MP-ADRC method are the inclusion of a constant gain in series with the plant output error and a linear filter in parallel with the overall error system.These structural changes do not influence the input/output dynamics of the original plant,but are intentionally introduced to modify the dynamics to be estimated by the extended state observer(ESO)and,thus,promote an increase in the robustness of the method.Some advantages can also be attributed to the proposed methodology,such as(i)the design procedures of both the controller and the ESO only require knowledge of the sign(±)of the plant input channel coefficient(or control gain);(ii)the plant control input is generated directly by a single ESO state variable.Despite the advantages and the characteristics of MP-ADRC mentioned earlier,closed-loop stability cannot be guaranteed when it is applied to dynamical systems that have finite zeros.To overcome this difficulty,this work introduces an extension in the MP-ADRC method.It basically consists of rewriting the minimum phase plant dynamics according to its relative order,and then follows with the design of the ESO by conveniently increasing the number of ESO state variables.The simulation results are also presented to illustrate the application of the proposed method.展开更多
Aiming at the sensitivity of linear active disturbance rejection control(LADRC)to measurement noise,an improved anti-saturation cascaded LADRC is proposed.This approach employs the system output as the control input o...Aiming at the sensitivity of linear active disturbance rejection control(LADRC)to measurement noise,an improved anti-saturation cascaded LADRC is proposed.This approach employs the system output as the control input of the filtering subsystem,which is then fed back to the secondary LADRC to mitigate measurement noise and uncertain disturbances.While preserving the benefits of precise and stable tracking inherent to traditional cascaded LADRC closed-loop systems,this design omits the outer loop tracking differentiator,thereby simplifying the structure and reducing the number of tunable parameters.Additionally,an error compensation strategy is introduced to address input saturation constraints,thereby equipping the controller with anti-saturation capabilities.Under multi-track surface switching conditions,the effectiveness of the new cascaded active disturbance rejection method is verified by simulation of the optimal adhesion control of the railway train.The results show that the improved cascaded LADRC has stronger rapidity and robustness.展开更多
To effectively select risk control schemes in uncertain environments,this paper has proposed an analysis and evaluation method based on the fuzzy comprehensive evaluation method.Firstly,enterprises have adopted the br...To effectively select risk control schemes in uncertain environments,this paper has proposed an analysis and evaluation method based on the fuzzy comprehensive evaluation method.Firstly,enterprises have adopted the brainstorming method and the Delphi method to identify risks in engineering projects,and organized the identified risks in the form of checklists to facilitate further analysis.Secondly,the fuzzy comprehensive evaluation theory was introduced to determine the comparison matrix of each risk factor and its weight.Furthermore,the top five risk factors in terms of weight ranking were taken as the evaluation factors for the selection of risk control plans.The plans were scored through the weighted scoring method,and the optimal risk control plan was determined based on the score.Finally,the feasibility of the proposed selection technology was verified through A research example of the risk control plan assessment for the construction project of Enterprise A.展开更多
This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target using range-only or bearing-only measurements.The challenge in this study stems from the unc...This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target using range-only or bearing-only measurements.The challenge in this study stems from the uncertainty associated with the positions of the agents,which may experience drift or disturbances during the target localization process.Initially,we derive the Cramer-Rao lower bound(CRLB)of the target position as the primary analytical metric.Subsequently,we establish the necessary and sufficient conditions for the optimal placement of agents.Based on these conditions,we analyze the maximal allowable agent position error for an expected mean squared error(MSE),providing valuable guidance for the selection of agent positioning sensors.The analytical findings are further validated through simulation experiments.展开更多
Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to in...Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to inherent fluctuations,limited data and imperfect measurements resulting in aleatory,epistemic and measurement uncertainties of the degradation process.This paper proposes a degradation model and remaining useful life(RUL)prediction method under triple uncertainties for a category of complex equipment with multi-phase degradation and jumps.First,a multi-phase degradation model with random jumps and measurement errors is constructed based on uncertain random processes.Afterward,the analytic expression of RUL prediction considering the heterogeneity is derived by modeling the uncertainty of degradation states at change points under the concept of first hitting time.A stochastic uncertain approach is utilized for the proposed multi-phase degradation model to identify model parameters based on historical data.Furthermore,the implied degradation features are adaptively updated in online stage using similarity-based weighted stochastic uncertain maximum likelihood estimation and Kalman filtering.Finally,the effectiveness of the method is verified by simulation example and practical case.展开更多
This work presents the application of the recently developed “Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5<sup>th</sup>-CASAM-N)” to a simplified Bernoulli ...This work presents the application of the recently developed “Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5<sup>th</sup>-CASAM-N)” to a simplified Bernoulli model. The 5<sup>th</sup>-CASAM-N builds upon and incorporates all of the lower-order (i.e., the first-, second-, third-, and fourth-order) adjoint sensitivities analysis methodologies. The Bernoulli model comprises a nonlinear model response, uncertain model parameters, uncertain model domain boundaries and uncertain model boundary conditions, admitting closed-form explicit expressions for the response sensitivities of all orders. Illustrating the specific mechanisms and advantages of applying the 5<sup>th</sup>-CASAM-N for the computation of the response sensitivities with respect to the uncertain parameters and boundaries reveals that the 5<sup>th</sup>-CASAM-N provides a fundamental step towards overcoming the curse of dimensionality in sensitivity and uncertainty analysis.展开更多
The multiple attribute group decision making problem in which the input arguments take the form of intuitionistic uncertain linguistic information is studied in the paper.Based on the operational principles of intuiti...The multiple attribute group decision making problem in which the input arguments take the form of intuitionistic uncertain linguistic information is studied in the paper.Based on the operational principles of intuitionistic uncertain linguistic variables and the concept of the expected value and accuracy function,some new dependent aggregation operators with intuitionistic uncertain linguistic information including the dependent intuitionistic uncertain linguistic ordered weighted average(DIULOWA)operator,the dependent intuitionistic uncertain linguistic ordered weighted geometric(DIULOWG)operator,the generalized dependent intuitionistic uncertain linguistic ordered weighted aggregation(GDIULOWA)operator and so on are developed,in which the associated weights only depend on the aggregated arguments.Also,we study some desirable properties of the aggregation operators.Moreover,the approach of multiple attribute group decision making with intuitionistic uncertain linguistic information based on the developed operators is proposed.Finally,an illustrative numerical example is given to show the practicality and effectiveness of the proposed approaches.展开更多
In order to guarantee the safety service and life-span of long-span cable-stayed bridges, the uncertain type of analytic hierarchy process （AHP） method is adopted to access the bridge condition. The correlative theo...In order to guarantee the safety service and life-span of long-span cable-stayed bridges, the uncertain type of analytic hierarchy process （AHP） method is adopted to access the bridge condition. The correlative theory and applied objects of uncertain type of AHP are introduced, and then the optimal transitive matrix method is chosen to calculate the interval number judgment matrix, which makes the weights of indices more reliable and accurate. Finally, with Harbin Songhua River Cable-Stayed Bridge as an example, an index system and an assessment model are proposed for the condition assessment of this bridge, and by using uncertain type of AHP, the weights of assessment indices are fixed and the final assessment results of the bridge are calculated, which proves the feasibility and practicability of this method. The application of this assessment method can provide the scientific basis for maintenance and management of long-span cable-stayed bridges.展开更多
This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appea...This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appear on both the state and output matrices. The observer design problem is formulated as a set of linear constraints which can be easily solved using linear matrix inequalities (LMI) technique. An application based on manipulator arm actuated by a direct current (DC) motor is presented to evaluate the performance of the proposed observer. The observer is applied to estimate both state and faults.展开更多
This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters＇ variations of t...This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters＇ variations of the nonlinear system. Linear matri~ inequalities （LMIs） have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.展开更多
Uncertain data are common due to the increasing usage of sensors, radio frequency identification(RFID), GPS and similar devices for data collection. The causes of uncertainty include limitations of measurements, inclu...Uncertain data are common due to the increasing usage of sensors, radio frequency identification(RFID), GPS and similar devices for data collection. The causes of uncertainty include limitations of measurements, inclusion of noise, inconsistent supply voltage and delay or loss of data in transfer. In order to manage, query or mine such data, data uncertainty needs to be considered. Hence,this paper studies the problem of top-k distance-based outlier detection from uncertain data objects. In this work, an uncertain object is modelled by a probability density function of a Gaussian distribution. The naive approach of distance-based outlier detection makes use of nested loop. This approach is very costly due to the expensive distance function between two uncertain objects. Therefore,a populated-cells list(PC-list) approach of outlier detection is proposed. Using the PC-list, the proposed top-k outlier detection algorithm needs to consider only a fraction of dataset objects and hence quickly identifies candidate objects for top-k outliers. Two approximate top-k outlier detection algorithms are presented to further increase the efficiency of the top-k outlier detection algorithm.An extensive empirical study on synthetic and real datasets is also presented to prove the accuracy, efficiency and scalability of the proposed algorithms.展开更多
We consider quadratic stabilization for a class of switched systems which are composed of a finite set of continuoustime linear subsystems with norm bounded uncertainties. Under the assumption that there is no single ...We consider quadratic stabilization for a class of switched systems which are composed of a finite set of continuoustime linear subsystems with norm bounded uncertainties. Under the assumption that there is no single quadratically stable subsystem, if a convex combination of subsystems is quadratically stable, then we propose a state-dependent switching law, based on the convex combination of subsystems, such that the entire switched linear system is quadratically stable. When the state information is not available, we extend the discussion to designing an outputdependent switching law by constructing a robust Luenberger observer for each subsystem.展开更多
An uncertain multi-objective programming problem is a special type of mathematical multi-objective programming involving uncertain variables. This type of problem is important because there are several uncertain varia...An uncertain multi-objective programming problem is a special type of mathematical multi-objective programming involving uncertain variables. This type of problem is important because there are several uncertain variables in real-world problems.Therefore, research on the uncertain multi-objective programming problem is highly relevant, particularly those problems whose objective functions are correlated. In this paper, an approach that solves an uncertain multi-objective programming problem under the expected-variance value criterion is proposed. First, we define the basic framework of the approach and review concepts such as a Pareto efficient solution and expected-variance value criterion using an order relation between various uncertain variables.Second, the uncertain multi-objective problem is converted into an uncertain single-objective programming problem via a linear weighted method or ideal point method. Then the problem is transformed into a deterministic single objective programming problem under the expected-variance value criterion. Third, four lemmas and two theorems are proved to illustrate that the optimal solution of the deterministic single-objective programming problem is an efficient solution to the original uncertainty problem. Finally, two numerical examples are presented to validate the effectiveness of the proposed approach.展开更多
This paper introduces uncertainty theory to deal with non-deterministic factors in ranking alternatives. The uncertain variable method (UVM) and the definition of consistency for uncertainty comparison matrices are pr...This paper introduces uncertainty theory to deal with non-deterministic factors in ranking alternatives. The uncertain variable method (UVM) and the definition of consistency for uncertainty comparison matrices are proposed. A simple yet pragmatic approach for testing whether or not an uncertainty comparison matrix is consistent is put forward. In cases where an uncertainty comparison matrix is inconsistent, an algorithm is used to generate consistent matrix. And then the consistent uncertainty comparison matrix can derive the uncertainty weights. The final ranking is given by uncertainty weighs if they are acceptable;otherwise we rely on the ranks of expected values of uncertainty weights instead. Three numerical examples including a hierarchical (AHP) decision problem are examined to illustrate the validity and practicality of the proposed methods.展开更多
A linear matrix inequality(LMI)-based sliding surface design method for integral sliding mode control of uncertain time-delay systems with mismatching uncertainties is proposed.The uncertain time-delay system under co...A linear matrix inequality(LMI)-based sliding surface design method for integral sliding mode control of uncertain time-delay systems with mismatching uncertainties is proposed.The uncertain time-delay system under consideration may have mis-matching norm bounded uncertainties in the state matrix as well as the input matrix,A sufficient condition for the existence of a sliding surface is given to guarantee asymptotic stability of the full order slJdJng mode dynamics.An LMI characterization of the slid-ing surface is given,together with an integral sliding mode control law guaranteeing the existence of a sliding mode from the initial time.Finally,a simulation is given to show the effectiveness of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China(72571094,72271076,71871079)。
文摘Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.
基金National Natural Science Foundation of China (61773044,62073009)National key Laboratory of Science and Technology on Reliability and Environmental Engineering(WDZC2019601A301)。
文摘Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.
基金supported by the CAS Project for Young Scientists in Basic Research under Grant YSBR-035Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2.
文摘In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.
文摘2025 has,so far,been a year of surprises.The United States under its reelected president,Donald Trump,has not only ramped up the U.S.trade war with China that he began in his first term,but has also unleashed a verbal assault and a barrage of tariffs against its neighbors,Canada and Mexico.It appears the age of globalization and rules-based free trade is over,at least as far as the giant U.S.economy is concerned.
基金supported by the National Natural Science Foundation of China(No.92471204)Youth Innovation Promotion Association,CAS,China。
文摘Trajectory planning under uncertain dynamics is critical for safety-critical systems like Unmanned Aerial Vehicles(UAVs),where uncertainties in aerodynamic force and control surface failure can lead to mission failure.This paper proposes a Multi-stage Robust Optimization(MRO)framework to address nonlinear trajectory planning with bounded but unknown parameters.By integrating first-order sensitivity analysis and sequential optimization,the proposed method ensures robustness against worst-case parameter deviations while maintaining high terminal accuracy.Unlike existing approaches,this paper explicitly quantifies uncertainty propagation through sensitivity bounds and divides long-term planning into sub-stages to reduce cumulative errors.Simulations on a UAV model with uncertainties in aerodynamic coefficients,wind fields and coefficients of control inputs demonstrate that MRO achieves high terminal state accuracy and strong robustness.
基金supported in part by the Brazilian research agencies CNPq and CAPESby the Fundação Carlos Chagas Filho de AmparoàPesquisa do Estado do Rio de Janeiro,FAPERJ-Brasil(Project E-26/210.425/2024).
文摘This paper proposes an extension of the Modified-Plant ADRC(MP-ADRC)strategy to broaden its application to minimum phase dynamical systems.The main features of the MP-ADRC method are the inclusion of a constant gain in series with the plant output error and a linear filter in parallel with the overall error system.These structural changes do not influence the input/output dynamics of the original plant,but are intentionally introduced to modify the dynamics to be estimated by the extended state observer(ESO)and,thus,promote an increase in the robustness of the method.Some advantages can also be attributed to the proposed methodology,such as(i)the design procedures of both the controller and the ESO only require knowledge of the sign(±)of the plant input channel coefficient(or control gain);(ii)the plant control input is generated directly by a single ESO state variable.Despite the advantages and the characteristics of MP-ADRC mentioned earlier,closed-loop stability cannot be guaranteed when it is applied to dynamical systems that have finite zeros.To overcome this difficulty,this work introduces an extension in the MP-ADRC method.It basically consists of rewriting the minimum phase plant dynamics according to its relative order,and then follows with the design of the ESO by conveniently increasing the number of ESO state variables.The simulation results are also presented to illustrate the application of the proposed method.
基金supported by the State Key Laboratory of Heavy-duty and Express High-power Electric Locomotive open project(Grant No.QZKFKT2023-012).
文摘Aiming at the sensitivity of linear active disturbance rejection control(LADRC)to measurement noise,an improved anti-saturation cascaded LADRC is proposed.This approach employs the system output as the control input of the filtering subsystem,which is then fed back to the secondary LADRC to mitigate measurement noise and uncertain disturbances.While preserving the benefits of precise and stable tracking inherent to traditional cascaded LADRC closed-loop systems,this design omits the outer loop tracking differentiator,thereby simplifying the structure and reducing the number of tunable parameters.Additionally,an error compensation strategy is introduced to address input saturation constraints,thereby equipping the controller with anti-saturation capabilities.Under multi-track surface switching conditions,the effectiveness of the new cascaded active disturbance rejection method is verified by simulation of the optimal adhesion control of the railway train.The results show that the improved cascaded LADRC has stronger rapidity and robustness.
文摘To effectively select risk control schemes in uncertain environments,this paper has proposed an analysis and evaluation method based on the fuzzy comprehensive evaluation method.Firstly,enterprises have adopted the brainstorming method and the Delphi method to identify risks in engineering projects,and organized the identified risks in the form of checklists to facilitate further analysis.Secondly,the fuzzy comprehensive evaluation theory was introduced to determine the comparison matrix of each risk factor and its weight.Furthermore,the top five risk factors in terms of weight ranking were taken as the evaluation factors for the selection of risk control plans.The plans were scored through the weighted scoring method,and the optimal risk control plan was determined based on the score.Finally,the feasibility of the proposed selection technology was verified through A research example of the risk control plan assessment for the construction project of Enterprise A.
文摘This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target using range-only or bearing-only measurements.The challenge in this study stems from the uncertainty associated with the positions of the agents,which may experience drift or disturbances during the target localization process.Initially,we derive the Cramer-Rao lower bound(CRLB)of the target position as the primary analytical metric.Subsequently,we establish the necessary and sufficient conditions for the optimal placement of agents.Based on these conditions,we analyze the maximal allowable agent position error for an expected mean squared error(MSE),providing valuable guidance for the selection of agent positioning sensors.The analytical findings are further validated through simulation experiments.
基金supported by the National Key Research and Development Program of China(2021YFB3301200)the National Natural Science Foundation of China(NSFC)(U21A20483,62373040,62203042).
文摘Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to inherent fluctuations,limited data and imperfect measurements resulting in aleatory,epistemic and measurement uncertainties of the degradation process.This paper proposes a degradation model and remaining useful life(RUL)prediction method under triple uncertainties for a category of complex equipment with multi-phase degradation and jumps.First,a multi-phase degradation model with random jumps and measurement errors is constructed based on uncertain random processes.Afterward,the analytic expression of RUL prediction considering the heterogeneity is derived by modeling the uncertainty of degradation states at change points under the concept of first hitting time.A stochastic uncertain approach is utilized for the proposed multi-phase degradation model to identify model parameters based on historical data.Furthermore,the implied degradation features are adaptively updated in online stage using similarity-based weighted stochastic uncertain maximum likelihood estimation and Kalman filtering.Finally,the effectiveness of the method is verified by simulation example and practical case.
文摘This work presents the application of the recently developed “Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5<sup>th</sup>-CASAM-N)” to a simplified Bernoulli model. The 5<sup>th</sup>-CASAM-N builds upon and incorporates all of the lower-order (i.e., the first-, second-, third-, and fourth-order) adjoint sensitivities analysis methodologies. The Bernoulli model comprises a nonlinear model response, uncertain model parameters, uncertain model domain boundaries and uncertain model boundary conditions, admitting closed-form explicit expressions for the response sensitivities of all orders. Illustrating the specific mechanisms and advantages of applying the 5<sup>th</sup>-CASAM-N for the computation of the response sensitivities with respect to the uncertain parameters and boundaries reveals that the 5<sup>th</sup>-CASAM-N provides a fundamental step towards overcoming the curse of dimensionality in sensitivity and uncertainty analysis.
基金Supported by the National Natural Science Foundation of China(71761027)Ningbo Natural Science Foundation(2015A610161)。
文摘The multiple attribute group decision making problem in which the input arguments take the form of intuitionistic uncertain linguistic information is studied in the paper.Based on the operational principles of intuitionistic uncertain linguistic variables and the concept of the expected value and accuracy function,some new dependent aggregation operators with intuitionistic uncertain linguistic information including the dependent intuitionistic uncertain linguistic ordered weighted average(DIULOWA)operator,the dependent intuitionistic uncertain linguistic ordered weighted geometric(DIULOWG)operator,the generalized dependent intuitionistic uncertain linguistic ordered weighted aggregation(GDIULOWA)operator and so on are developed,in which the associated weights only depend on the aggregated arguments.Also,we study some desirable properties of the aggregation operators.Moreover,the approach of multiple attribute group decision making with intuitionistic uncertain linguistic information based on the developed operators is proposed.Finally,an illustrative numerical example is given to show the practicality and effectiveness of the proposed approaches.
基金Specialized Research Fund for the Doctoral Programof Higher Education (No20050213008)the Scientific and TechnicalPlan Item of Communications Department of Heilongjiang Province ofChina (2004)
文摘In order to guarantee the safety service and life-span of long-span cable-stayed bridges, the uncertain type of analytic hierarchy process （AHP） method is adopted to access the bridge condition. The correlative theory and applied objects of uncertain type of AHP are introduced, and then the optimal transitive matrix method is chosen to calculate the interval number judgment matrix, which makes the weights of indices more reliable and accurate. Finally, with Harbin Songhua River Cable-Stayed Bridge as an example, an index system and an assessment model are proposed for the condition assessment of this bridge, and by using uncertain type of AHP, the weights of assessment indices are fixed and the final assessment results of the bridge are calculated, which proves the feasibility and practicability of this method. The application of this assessment method can provide the scientific basis for maintenance and management of long-span cable-stayed bridges.
文摘This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appear on both the state and output matrices. The observer design problem is formulated as a set of linear constraints which can be easily solved using linear matrix inequalities (LMI) technique. An application based on manipulator arm actuated by a direct current (DC) motor is presented to evaluate the performance of the proposed observer. The observer is applied to estimate both state and faults.
文摘This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters＇ variations of the nonlinear system. Linear matri~ inequalities （LMIs） have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.
基金supported by Grant-in-Aid for Scientific Research(A)(#24240015A)
文摘Uncertain data are common due to the increasing usage of sensors, radio frequency identification(RFID), GPS and similar devices for data collection. The causes of uncertainty include limitations of measurements, inclusion of noise, inconsistent supply voltage and delay or loss of data in transfer. In order to manage, query or mine such data, data uncertainty needs to be considered. Hence,this paper studies the problem of top-k distance-based outlier detection from uncertain data objects. In this work, an uncertain object is modelled by a probability density function of a Gaussian distribution. The naive approach of distance-based outlier detection makes use of nested loop. This approach is very costly due to the expensive distance function between two uncertain objects. Therefore,a populated-cells list(PC-list) approach of outlier detection is proposed. Using the PC-list, the proposed top-k outlier detection algorithm needs to consider only a fraction of dataset objects and hence quickly identifies candidate objects for top-k outliers. Two approximate top-k outlier detection algorithms are presented to further increase the efficiency of the top-k outlier detection algorithm.An extensive empirical study on synthetic and real datasets is also presented to prove the accuracy, efficiency and scalability of the proposed algorithms.
基金supported in part by the Japan Ministry of Education,Sciences and Culture under Grants-in-Aid for Scientific Research(C)(21560471)the Green Industry Leading Program of Hubei University of Technology(CPYF2017003)the National Natural Science Foundation of China(1160147411461082)
文摘We consider quadratic stabilization for a class of switched systems which are composed of a finite set of continuoustime linear subsystems with norm bounded uncertainties. Under the assumption that there is no single quadratically stable subsystem, if a convex combination of subsystems is quadratically stable, then we propose a state-dependent switching law, based on the convex combination of subsystems, such that the entire switched linear system is quadratically stable. When the state information is not available, we extend the discussion to designing an outputdependent switching law by constructing a robust Luenberger observer for each subsystem.
基金supported by the National Natural Science Foundation of China(71601183 71571190)
文摘An uncertain multi-objective programming problem is a special type of mathematical multi-objective programming involving uncertain variables. This type of problem is important because there are several uncertain variables in real-world problems.Therefore, research on the uncertain multi-objective programming problem is highly relevant, particularly those problems whose objective functions are correlated. In this paper, an approach that solves an uncertain multi-objective programming problem under the expected-variance value criterion is proposed. First, we define the basic framework of the approach and review concepts such as a Pareto efficient solution and expected-variance value criterion using an order relation between various uncertain variables.Second, the uncertain multi-objective problem is converted into an uncertain single-objective programming problem via a linear weighted method or ideal point method. Then the problem is transformed into a deterministic single objective programming problem under the expected-variance value criterion. Third, four lemmas and two theorems are proved to illustrate that the optimal solution of the deterministic single-objective programming problem is an efficient solution to the original uncertainty problem. Finally, two numerical examples are presented to validate the effectiveness of the proposed approach.
文摘This paper introduces uncertainty theory to deal with non-deterministic factors in ranking alternatives. The uncertain variable method (UVM) and the definition of consistency for uncertainty comparison matrices are proposed. A simple yet pragmatic approach for testing whether or not an uncertainty comparison matrix is consistent is put forward. In cases where an uncertainty comparison matrix is inconsistent, an algorithm is used to generate consistent matrix. And then the consistent uncertainty comparison matrix can derive the uncertainty weights. The final ranking is given by uncertainty weighs if they are acceptable;otherwise we rely on the ranks of expected values of uncertainty weights instead. Three numerical examples including a hierarchical (AHP) decision problem are examined to illustrate the validity and practicality of the proposed methods.
基金supported in part by the National Basic Research Program of China(973 Program)(61334)
文摘A linear matrix inequality(LMI)-based sliding surface design method for integral sliding mode control of uncertain time-delay systems with mismatching uncertainties is proposed.The uncertain time-delay system under consideration may have mis-matching norm bounded uncertainties in the state matrix as well as the input matrix,A sufficient condition for the existence of a sliding surface is given to guarantee asymptotic stability of the full order slJdJng mode dynamics.An LMI characterization of the slid-ing surface is given,together with an integral sliding mode control law guaranteeing the existence of a sliding mode from the initial time.Finally,a simulation is given to show the effectiveness of the proposed method.
