We propose a novel parameter value selection strategy for the Lüsystem to construct a chaotic robot to accomplish the complete coverage path planning(CCPP)task.The algorithm can meet the requirements of high rand...We propose a novel parameter value selection strategy for the Lüsystem to construct a chaotic robot to accomplish the complete coverage path planning(CCPP)task.The algorithm can meet the requirements of high randomness and coverage rate to perform specific types of missions.First,we roughly determine the value range of the parameter of the Lüsystem to meet the requirement of being a dissipative system.Second,we calculate the Lyapunov exponents to narrow the value range further.Next,we draw the phase planes of the system to approximately judge the topological distribution characteristics of its trajectories.Furthermore,we calculate the Pearson correlation coefficient of the variable for those good ones to judge its random characteristics.Finally,we construct a chaotic robot using variables with the determined parameter values and simulate and test the coverage rate to study the relationship between the coverage rate and the random characteristics of the variables.The above selection strategy gradually narrows the value range of the system parameter according to the randomness requirement of the coverage trajectory.Using the proposed strategy,proper variables can be chosen with a larger Lyapunov exponent to construct a chaotic robot with a higher coverage rate.Another chaotic system,the Lorenz system,is used to verify the feasibility and effectiveness of the designed strategy.The proposed strategy for enhancing the coverage rate of the mobile robot can improve the efficiency of accomplishing CCPP tasks under specific types of missions.展开更多
Solving a quantified constraint satisfaction problem(QCSP)is usually a hard task due to its computational complexity.Exact algorithms play an important role in solving this problem,among which backtrack algorithms are...Solving a quantified constraint satisfaction problem(QCSP)is usually a hard task due to its computational complexity.Exact algorithms play an important role in solving this problem,among which backtrack algorithms are effective.In a backtrack algorithm,an important step is assigning a variable by a chosen value when exploiting a branch,and thus a good value selection rule may speed up greatly.In this paper,we propose two value selection rules for existentially and universally quantified variables,respectively,to avoid unnecessary searching.The rule for universally quantified variables is prior to trying failure values in previous branches,and the rule for existentially quantified variables selects the promising values first.Two rules are integrated into the state-of-the-art QCSP solver,i.e.,QCSP-Solve,which is an exact solver based on backtracking.We perform a number of experiments to evaluate improvements brought by our rules.From computational results,we can conclude that the new value selection rules speed up the solver by 5 times on average and 30 times at most.We also show both rules perform well particularly on instances with existentially and universally quantified variables occurring alternatively.展开更多
At present,electrode line impedance supervision(ELIS)based protection is widely used to detect faults on grounding electrode lines,which are indispensable elements of high-voltage direct current(HVDC)systems.The exist...At present,electrode line impedance supervision(ELIS)based protection is widely used to detect faults on grounding electrode lines,which are indispensable elements of high-voltage direct current(HVDC)systems.The existing theoretical analysis of measured impedance is based on lumped line model and the threshold value is generally set according to engineering experience,which have caused the dead zone problem and even accidents.Therefore,a study on measured impedance of ELIS-based protection and its threshold value selection method is carried out to solve this problem.In this study,the expressions of measured impedance under normal operation and fault conditions are deduced based on rigorous and accurate line model.Based on the expressions,the characteristics of the measured impedance are calculated and analyzed.With the characteristics of the measured impedance,the applicability of the protection with the traditional threshold value is further discussed and the distribution of the dead zone can be located.Then,the method to calculate the threshold value of ELIS-based protection is proposed.With a proper threshold value selected by the proposed method,the dead zone of ELIS-based protection is effectively eliminated,and the protection can identify all types of faults even with large transition resistances.Case studies on PSCAD/EMTDC have been conducted to verify the conclusion.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.61973184 and 61473179)the Natural Science Foundation of Shandong Province,China(No.ZR2021MF072)。
文摘We propose a novel parameter value selection strategy for the Lüsystem to construct a chaotic robot to accomplish the complete coverage path planning(CCPP)task.The algorithm can meet the requirements of high randomness and coverage rate to perform specific types of missions.First,we roughly determine the value range of the parameter of the Lüsystem to meet the requirement of being a dissipative system.Second,we calculate the Lyapunov exponents to narrow the value range further.Next,we draw the phase planes of the system to approximately judge the topological distribution characteristics of its trajectories.Furthermore,we calculate the Pearson correlation coefficient of the variable for those good ones to judge its random characteristics.Finally,we construct a chaotic robot using variables with the determined parameter values and simulate and test the coverage rate to study the relationship between the coverage rate and the random characteristics of the variables.The above selection strategy gradually narrows the value range of the system parameter according to the randomness requirement of the coverage trajectory.Using the proposed strategy,proper variables can be chosen with a larger Lyapunov exponent to construct a chaotic robot with a higher coverage rate.Another chaotic system,the Lorenz system,is used to verify the feasibility and effectiveness of the designed strategy.The proposed strategy for enhancing the coverage rate of the mobile robot can improve the efficiency of accomplishing CCPP tasks under specific types of missions.
基金We would like to thank Dr.Peter Nightingale for the source code of QCSP-Solve.The work described in this paper was supported by the National Natural Science Foundation of China(Granted Nos.61972063,61763003,61672122,61602077,61402070)the Fundamental Research Funds for the Central Universities(3132019029,3132019355).
文摘Solving a quantified constraint satisfaction problem(QCSP)is usually a hard task due to its computational complexity.Exact algorithms play an important role in solving this problem,among which backtrack algorithms are effective.In a backtrack algorithm,an important step is assigning a variable by a chosen value when exploiting a branch,and thus a good value selection rule may speed up greatly.In this paper,we propose two value selection rules for existentially and universally quantified variables,respectively,to avoid unnecessary searching.The rule for universally quantified variables is prior to trying failure values in previous branches,and the rule for existentially quantified variables selects the promising values first.Two rules are integrated into the state-of-the-art QCSP solver,i.e.,QCSP-Solve,which is an exact solver based on backtracking.We perform a number of experiments to evaluate improvements brought by our rules.From computational results,we can conclude that the new value selection rules speed up the solver by 5 times on average and 30 times at most.We also show both rules perform well particularly on instances with existentially and universally quantified variables occurring alternatively.
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars(No.52025071)the Joint Funds of the National Natural Science Foundation of China(No.U1866205)。
文摘At present,electrode line impedance supervision(ELIS)based protection is widely used to detect faults on grounding electrode lines,which are indispensable elements of high-voltage direct current(HVDC)systems.The existing theoretical analysis of measured impedance is based on lumped line model and the threshold value is generally set according to engineering experience,which have caused the dead zone problem and even accidents.Therefore,a study on measured impedance of ELIS-based protection and its threshold value selection method is carried out to solve this problem.In this study,the expressions of measured impedance under normal operation and fault conditions are deduced based on rigorous and accurate line model.Based on the expressions,the characteristics of the measured impedance are calculated and analyzed.With the characteristics of the measured impedance,the applicability of the protection with the traditional threshold value is further discussed and the distribution of the dead zone can be located.Then,the method to calculate the threshold value of ELIS-based protection is proposed.With a proper threshold value selected by the proposed method,the dead zone of ELIS-based protection is effectively eliminated,and the protection can identify all types of faults even with large transition resistances.Case studies on PSCAD/EMTDC have been conducted to verify the conclusion.