This paper presents a simple and systematic approach to design second order sliding mode controller for buck converters.The second order sliding mode control(SOSMC)based on twisting algorithm has been implemented to c...This paper presents a simple and systematic approach to design second order sliding mode controller for buck converters.The second order sliding mode control(SOSMC)based on twisting algorithm has been implemented to control buck switch mode converter.The idea behind this strategy is to suppress chattering and maintain robustness and finite time convergence properties of the output voltage error to the equilibrium point under the load variations and parametric uncertainties.In addition,the influence of the twisting algorithm on the performance of closed-loop system is investigated and compared with other algorithms of first order sliding mode control such as adaptive sliding mode control(ASMC),nonsingular terminal sliding mode control(NTSMC).In comparative evaluation,the transient response of the output voltage with the step change in the load and the start-up response of the output voltage with the step change in the input voltage of buck converter were compared.Experimental results were obtained from a hardware setup constructed in laboratory.Finally,for all of the surveyed control methods,the theoretical considerations,numerical simulations,and experimental measurements from a laboratory prototype are compared for different operating points.It is shown that the proposed twisting method presents an improvement in steady state error and settling time of output voltage during load changes.展开更多
In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(S...In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.展开更多
This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the ...This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the first step, a direct neural model(DNM)is used to learn the behavior of the system, then, an inverse neural model(INM) is synthesized using a specialized learning technique and cascaded to the uncertain system as a controller. In previous works, the neural models are trained classically by backpropagation(BP) algorithm. In this work, the sliding mode-backpropagation(SM-BP) algorithm, presenting some important properties such as robustness and speedy learning, is investigated. Moreover, four combinations using classical BP and SM-BP are tested to determine the best configuration for the robust control of uncertain nonlinear systems. Two simulation examples are treated to illustrate the effectiveness of the proposed control strategy.展开更多
A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The f...A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.展开更多
A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency ...A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency analysis. The original data is divided into some segments with the same length. Each segment data is processed based on the principle of the first-level EMD decomposition. The algorithm is compared with the traditional EMD and results show that it is more useful and effective for analyzing nonlinear and non-stationary signals.展开更多
This paper has developed a genetic algorithm (GA) optimization approach to search for the optimal locations to install bearings on the motorized spindle shaft to maximize its first-mode natural frequency (FMNF). First...This paper has developed a genetic algorithm (GA) optimization approach to search for the optimal locations to install bearings on the motorized spindle shaft to maximize its first-mode natural frequency (FMNF). First, a finite element method (FEM) dynamic model of the spindle-bearing system is formulated, and by solving the eigenvalue problem derived from the equations of motion, the natural frequencies of the spindle system can be acquired. Next, the mathematical model is built, which includes the objective function to maximize FMNF and the constraints to limit the locations of the bearings with respect to the geometrical boundaries of the segments they located and the spacings between adjacent bearings. Then, the Sequential Decoding Process (SDP) GA is designed to accommodate the dependent characteristics of the constraints in the mathematical model. To verify the proposed SDP-GA optimization approach, a four-bearing installation optimazation problem of an illustrative spindle system is investigated. The results show that the SDP-GA provides well convergence for the optimization searching process. By applying design of experiments and analysis of variance, the optimal values of GA parameters are determined under a certain number restriction in executing the eigenvalue calculation subroutine. A linear regression equation is derived also to estimate necessary calculation efforts with respect to the specific quality of the optimization solution. From the results of this illustrative example, we can conclude that the proposed SDP-GA optimization approach is effective and efficient.展开更多
To alleviate the chattering problem, a new type of fuzzy global sliding mode controller （FGSMC） is presented. In this controller, the switching gain is estimated by fuzzy logic system based on the reachable conditio...To alleviate the chattering problem, a new type of fuzzy global sliding mode controller （FGSMC） is presented. In this controller, the switching gain is estimated by fuzzy logic system based on the reachable conditions of sliding mode controller（SMC）, and genetic algorithm （GA） is used to optimize scaling factor of the switching gain, thus the switch chattering of SMC can be alleviated. Moreover, global sliding mode is realized by designing an exponential dynamic sliding surface. Simulation and real-time application for flight simulator servo system with Lugre friction are given to indicate that the proposed controller can guarantee high robust performance all the time and can alleviate chattering phenomenon effectively.展开更多
For a class of aeroengine nonlinear systems,a novel nonlinear sliding mode controller(SMC)design method based on artificial bee colony(ABC)algorithm is proposed.In view of the strong nonlinearity and uncertainty of ae...For a class of aeroengine nonlinear systems,a novel nonlinear sliding mode controller(SMC)design method based on artificial bee colony(ABC)algorithm is proposed.In view of the strong nonlinearity and uncertainty of aeroengines,sliding mode control strategy is adopted to design controller for the aeroengine.On basis of exact linearization approach,the nonlinear sliding mode controller is obtained conveniently.By using ABC algorithm,the parameters in the designed controller can be tuned to achieve optimal performance,resulting in a closedloop system with satisfactory dynamic performance and high steady accuracy.Simulation on an aeroengine verifies the effectiveness of the presented method.展开更多
Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be imp...Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be implemented. Under the consideration of cooperative communication systems, the scenario includes one information source, M relay stations and N destinations. This work proposes a relay selection algorithm in the Raleigh fading channel. Based on the exhaustive search method, easily to realize, the optimal selection scheme can be found with a highly complicated calculation. In order to reduce the computational complexity, an approximate optimal solution with a greedy algorithm applied for the relay station selection is proposed. With different situations of the communication systems, the performance evaluation obtained by both the proposed algorithm and the exhaustive search algorithm are given for comparison. It shows the proposed algorithm could provide a solution approach to the optimal one.展开更多
The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such...The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such as matching attributes selection, similarity measure calculation, weights learning and training evaluation policies are carefully studied. The testing applications illustrate that an accuracy of 74.67 % can be achieved with 75 balanced-distributed failure cases covering 3 failure modes, and that the resulting learning weight vector can be well applied to the other 2 failure modes, achieving 73.3 % of recognition accuracy. It is also proved that its popularizing capability is good to the recognition of even more mixed failure modes.展开更多
The Electromagnetic Compatibility (EMC) of direct current (DC) motor windings is a system model which is used to reflect the functional characters of the system in the whole EMC specified frequency (150 KHz ~ 30 MHz)....The Electromagnetic Compatibility (EMC) of direct current (DC) motor windings is a system model which is used to reflect the functional characters of the system in the whole EMC specified frequency (150 KHz ~ 30 MHz). For most motor designing process, it is always used to evaluate the inductance of windings in lower or working frequency;however, when analyzing the conducted interference, it is necessary to take some pa-rameters in high frequency into account in building up the EMC model, such as the noticeable capacitance distributed among the windings or between windings and shells. Past research neglected the common-mode current generated by the high frequency interference within motor bearings coupled with shells, since the parasitic capacitance of rotor core comes from armature windings supplied sufficient paths. In EMC model-ing process for DC motor problem, first, test the impedance of windings by experiments;then, generate the equivalent circuit with overall parameters. At present, it is a difficulty that how to choose the parameters. Most researchers preferred to adopt analytical calculation results, however, it could not reflect the essence of the model since it requires many simplification. Based on this point, this paper adopted ant colony algorithm (ACA) with positive feedback to intelligently search and globally optimize the parameters of equivalent cir-cuit. Simulation result showed that the impedance of equivalent circuit calculated by this algorithm was the same as experimental result in the whole EMC frequency. In order to further confirm the validity of ACA, PSPICE circuit simulation was implemented to simulate the spectrum of common mode Electromagnetic Interference (EMI) of equivalent circuit. The simulation result accords well with the experiment result re-ceived by EMI receiver. So it sufficiently demonstrated correctness of ACA in the analysis of high frequency equivalent circuit.展开更多
文摘This paper presents a simple and systematic approach to design second order sliding mode controller for buck converters.The second order sliding mode control(SOSMC)based on twisting algorithm has been implemented to control buck switch mode converter.The idea behind this strategy is to suppress chattering and maintain robustness and finite time convergence properties of the output voltage error to the equilibrium point under the load variations and parametric uncertainties.In addition,the influence of the twisting algorithm on the performance of closed-loop system is investigated and compared with other algorithms of first order sliding mode control such as adaptive sliding mode control(ASMC),nonsingular terminal sliding mode control(NTSMC).In comparative evaluation,the transient response of the output voltage with the step change in the load and the start-up response of the output voltage with the step change in the input voltage of buck converter were compared.Experimental results were obtained from a hardware setup constructed in laboratory.Finally,for all of the surveyed control methods,the theoretical considerations,numerical simulations,and experimental measurements from a laboratory prototype are compared for different operating points.It is shown that the proposed twisting method presents an improvement in steady state error and settling time of output voltage during load changes.
基金Projects(61471370,61401479)supported by the National Natural Science Foundation of China
文摘In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.
文摘This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the first step, a direct neural model(DNM)is used to learn the behavior of the system, then, an inverse neural model(INM) is synthesized using a specialized learning technique and cascaded to the uncertain system as a controller. In previous works, the neural models are trained classically by backpropagation(BP) algorithm. In this work, the sliding mode-backpropagation(SM-BP) algorithm, presenting some important properties such as robustness and speedy learning, is investigated. Moreover, four combinations using classical BP and SM-BP are tested to determine the best configuration for the robust control of uncertain nonlinear systems. Two simulation examples are treated to illustrate the effectiveness of the proposed control strategy.
基金supported by the National Natural Science Foundation of China(71171038)
文摘A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
文摘A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency analysis. The original data is divided into some segments with the same length. Each segment data is processed based on the principle of the first-level EMD decomposition. The algorithm is compared with the traditional EMD and results show that it is more useful and effective for analyzing nonlinear and non-stationary signals.
文摘This paper has developed a genetic algorithm (GA) optimization approach to search for the optimal locations to install bearings on the motorized spindle shaft to maximize its first-mode natural frequency (FMNF). First, a finite element method (FEM) dynamic model of the spindle-bearing system is formulated, and by solving the eigenvalue problem derived from the equations of motion, the natural frequencies of the spindle system can be acquired. Next, the mathematical model is built, which includes the objective function to maximize FMNF and the constraints to limit the locations of the bearings with respect to the geometrical boundaries of the segments they located and the spacings between adjacent bearings. Then, the Sequential Decoding Process (SDP) GA is designed to accommodate the dependent characteristics of the constraints in the mathematical model. To verify the proposed SDP-GA optimization approach, a four-bearing installation optimazation problem of an illustrative spindle system is investigated. The results show that the SDP-GA provides well convergence for the optimization searching process. By applying design of experiments and analysis of variance, the optimal values of GA parameters are determined under a certain number restriction in executing the eigenvalue calculation subroutine. A linear regression equation is derived also to estimate necessary calculation efforts with respect to the specific quality of the optimization solution. From the results of this illustrative example, we can conclude that the proposed SDP-GA optimization approach is effective and efficient.
基金This project is supported by Aeronautics Foundation of China (No. 00E51022)
文摘To alleviate the chattering problem, a new type of fuzzy global sliding mode controller （FGSMC） is presented. In this controller, the switching gain is estimated by fuzzy logic system based on the reachable conditions of sliding mode controller（SMC）, and genetic algorithm （GA） is used to optimize scaling factor of the switching gain, thus the switch chattering of SMC can be alleviated. Moreover, global sliding mode is realized by designing an exponential dynamic sliding surface. Simulation and real-time application for flight simulator servo system with Lugre friction are given to indicate that the proposed controller can guarantee high robust performance all the time and can alleviate chattering phenomenon effectively.
基金supported by the Fundamental Research Funds for the Central Universities(NS2016027)
文摘For a class of aeroengine nonlinear systems,a novel nonlinear sliding mode controller(SMC)design method based on artificial bee colony(ABC)algorithm is proposed.In view of the strong nonlinearity and uncertainty of aeroengines,sliding mode control strategy is adopted to design controller for the aeroengine.On basis of exact linearization approach,the nonlinear sliding mode controller is obtained conveniently.By using ABC algorithm,the parameters in the designed controller can be tuned to achieve optimal performance,resulting in a closedloop system with satisfactory dynamic performance and high steady accuracy.Simulation on an aeroengine verifies the effectiveness of the presented method.
基金supported by National Science Council under Grant No.101-2221-E-029-020-MY3
文摘Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be implemented. Under the consideration of cooperative communication systems, the scenario includes one information source, M relay stations and N destinations. This work proposes a relay selection algorithm in the Raleigh fading channel. Based on the exhaustive search method, easily to realize, the optimal selection scheme can be found with a highly complicated calculation. In order to reduce the computational complexity, an approximate optimal solution with a greedy algorithm applied for the relay station selection is proposed. With different situations of the communication systems, the performance evaluation obtained by both the proposed algorithm and the exhaustive search algorithm are given for comparison. It shows the proposed algorithm could provide a solution approach to the optimal one.
文摘The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such as matching attributes selection, similarity measure calculation, weights learning and training evaluation policies are carefully studied. The testing applications illustrate that an accuracy of 74.67 % can be achieved with 75 balanced-distributed failure cases covering 3 failure modes, and that the resulting learning weight vector can be well applied to the other 2 failure modes, achieving 73.3 % of recognition accuracy. It is also proved that its popularizing capability is good to the recognition of even more mixed failure modes.
文摘The Electromagnetic Compatibility (EMC) of direct current (DC) motor windings is a system model which is used to reflect the functional characters of the system in the whole EMC specified frequency (150 KHz ~ 30 MHz). For most motor designing process, it is always used to evaluate the inductance of windings in lower or working frequency;however, when analyzing the conducted interference, it is necessary to take some pa-rameters in high frequency into account in building up the EMC model, such as the noticeable capacitance distributed among the windings or between windings and shells. Past research neglected the common-mode current generated by the high frequency interference within motor bearings coupled with shells, since the parasitic capacitance of rotor core comes from armature windings supplied sufficient paths. In EMC model-ing process for DC motor problem, first, test the impedance of windings by experiments;then, generate the equivalent circuit with overall parameters. At present, it is a difficulty that how to choose the parameters. Most researchers preferred to adopt analytical calculation results, however, it could not reflect the essence of the model since it requires many simplification. Based on this point, this paper adopted ant colony algorithm (ACA) with positive feedback to intelligently search and globally optimize the parameters of equivalent cir-cuit. Simulation result showed that the impedance of equivalent circuit calculated by this algorithm was the same as experimental result in the whole EMC frequency. In order to further confirm the validity of ACA, PSPICE circuit simulation was implemented to simulate the spectrum of common mode Electromagnetic Interference (EMI) of equivalent circuit. The simulation result accords well with the experiment result re-ceived by EMI receiver. So it sufficiently demonstrated correctness of ACA in the analysis of high frequency equivalent circuit.
