Fluctuating voltage levels in power grids necessitate automatic voltage regulators(AVRs)to ensure stability.This study examined the modeling and control of AVR in hydroelectric power plants using model predictive cont...Fluctuating voltage levels in power grids necessitate automatic voltage regulators(AVRs)to ensure stability.This study examined the modeling and control of AVR in hydroelectric power plants using model predictive control(MPC),which utilizes an extensive mathe-matical model of the voltage regulation system to optimize the control actions over a defined prediction horizon.This predictive feature enables MPC to minimize voltage deviations while accounting for operational constraints,thereby improving stability and performance under dynamic conditions.Thefindings were compared with those derived from an optimal proportional integral derivative(PID)con-troller designed using the artificial bee colony(ABC)algorithm.Although the ABC-PID method adjusts the PID parameters based on historical data,it may be difficult to adapt to real-time changes in system dynamics under constraints.Comprehensive simulations assessed both frameworks,emphasizing performance metrics such as disturbance rejection,response to load changes,and resilience to uncertainties.The results show that both MPC and ABC-PID methods effectively achieved accurate voltage regulation;however,MPC excelled in controlling overshoot and settling time—recording 0.0%and 0.25 s,respectively.This demonstrates greater robustness compared to conventional control methods that optimize PID parameters based on performance criteria derived from actual system behavior,which exhibited settling times and overshoots exceeding 0.41 s and 5.0%,respectively.The controllers were implemented using MATLAB/Simulink software,indicating a significant advancement for power plant engineers pursuing state-of-the-art automatic voltage regulations.展开更多
The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on t...The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical （MLD） modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller （HMPC） is tuned based on online mixed-integer quadratic optimization （MIQP）. Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology （MPT）, thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.展开更多
By analyzing the output voltage ripple of a buck-boost converter with large equivalent series resistance（ESR） of output capacitor, one valley voltage-mode controller for buck-boost converter is proposed. Considering...By analyzing the output voltage ripple of a buck-boost converter with large equivalent series resistance（ESR） of output capacitor, one valley voltage-mode controller for buck-boost converter is proposed. Considering the fact that the increasing and decreasing slopes of the inductor current are assumed to be constant during each switching cycle, an especial sampleddata model of valley voltage-mode controlled buck-boost converter is established. Based on this model, the dynamical effect of an output-capacitor time-constant on the valley voltage-mode controlled buck-boost converter is revealed and analyzed via the bifurcation diagrams, the movements of eigenvalues, the Lyapunov exponent spectra, the boundary equations,and the operating-state regions. It is found that with gradual reduction of output-capacitor time-constant, the buck-boost converter in continuous conduction mode（CCM） shows the evolutive dynamic behavior from period-1 to period-2, period-4, period-8, chaos, and invalid state. The stability boundary and the invalidated boundary are derived theoretically by stability analysis, where the stable state of valley voltage-mode controlled buck-boost converter can enter into an unstable state, and the converter can shift from the operation region to a forbidden region. These results verified by time-domain waveforms and phase portraits of both simulation and experiment indicate that the sampled-data model is correct and the time constant of the output capacitor is a critical factor for valley voltage-mode controlled buck-boost converter, which has a significant effect on the dynamics as well as control stability.展开更多
Nonlinear model predictive control(NMPC)scheme is an effective method of multi-objective optimization control in complex industrial systems.In this paper,a NMPC scheme for the wet limestone flue gas desulphurization(W...Nonlinear model predictive control(NMPC)scheme is an effective method of multi-objective optimization control in complex industrial systems.In this paper,a NMPC scheme for the wet limestone flue gas desulphurization(WFGD)system is proposed which provides a more flexible framework of optimal control and decision-making compared with PID scheme.At first,a mathematical model of the FGD process is deduced which is suitable for NMPC structure.To equipoise the model’s accuracy and conciseness,the wet limestone FGD system is separated into several modules.Based on the conservation laws,a model with reasonable simplification is developed to describe dynamics of different modules for the purpose of controller design.Then,by addressing economic objectives directly into the NMPC scheme,the NMPC controller can minimize economic cost and track the set-point simultaneously.The accuracy of model is validated by the field data of a 1000 MW thermal power plant in Henan Province,China.The simulation results show that the NMPC strategy improves the economic performance and ensures the emission requirement at the same time.In the meantime,the control scheme satisfies the multiobjective control requirements under complex operation conditions(e.g.,boiler load fluctuation and set point variation).The mathematical model and NMPC structure provides the basic work for the future development of advanced optimized control algorithms in the wet limestone FGD systems.展开更多
This paper provides an introduction to a support vector machine, a new kernel-based technique introduced in statistical learning theory and structural risk minimization, then presents a modeling-control framework base...This paper provides an introduction to a support vector machine, a new kernel-based technique introduced in statistical learning theory and structural risk minimization, then presents a modeling-control framework based on SVM. At last a numerical experiment is taken to demonstrate the proposed approach's correctness and effectiveness.展开更多
To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Sh...To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Shunde＂ city as a pilot summer case study,we apply an innovative response surface modeling（RSM） methodology based on the Community Multi-Scale Air Quality（CMAQ） modeling simulations to identify the O_3 regime and provide dynamic analysis of the precursor contributions to effectively assess the O_3 impacts of volatile organic compound（VOC） control strategy.Our results show that Shunde is a typical VOC-limited urban O_3 polluted city.The ＂Jiangmen＂ city,as the main upper wind area during July 2014,its VOCs and nitrogen oxides（NO_x） emissions make up the largest contribution（9.06%）.On the contrary,the contribution from local（Shunde） emission is lowest（6.35%） among the seven neighbor regions.The local VOCs industrial source emission has the largest contribution comparing to other precursor emission sectors in Shunde.The results of dynamic source contribution analysis further show that the local NO_x control could slightly increase the ground O_3 under low（10.00%） and medium（40.00%）reduction ratios,while it could start to turn positive to decrease ground O_3 under the high NO_x abatement ratio（75.00%）.The real-time assessment of O_3 impacts from VOCs control strategies in Pearl River Delta（PRD） shows that the joint regional VOCs emission control policy will effectively reduce the ground O_3 concentration in Shunde.展开更多
Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop cont...Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems.展开更多
The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is...The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is designed. The recursive prediction error (RPE)algorithm which yields faster convergence than back propagation (BP) algorithm is applied to trainthe neural networks. The realization of RPE algorithm is given. The difference of modeling ofartificial muscles using neural networks with different input nodes and different hidden layer nodesis discussed. On this basis the nonlinear control scheme using neural networks for artificialmuscle system has been introduced. The experimental results show that the nonlinear control schemeyields faster response and higher control accuracy than the traditional linear control scheme.展开更多
A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraint...A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraints.First,an NN is used to fit the motion data of robot manipulators for data-driven dynamic modeling,converting it into a linear prediction model through gradients.Then,by statistically analyzing the stochastic characteristics of the NN modeling errors,a distributionally robust model predictive controller is designed based on the chance constraints,and the optimization problem is transformed into a tractable quadratic programming(QP)problem under the distributionally robust optimization(DRO)framework.The recursive feasibility and convergence of the proposed algorithm are proven.Finally,the effectiveness of the proposed algorithm is verified through numerical simulation.展开更多
The control of civil, energy, and power systems presents significant new challenges for modeling and control theory. The purpose of this special issue is to provide a forum for researchers and practical engineers to d...The control of civil, energy, and power systems presents significant new challenges for modeling and control theory. The purpose of this special issue is to provide a forum for researchers and practical engineers to discuss the recent advances in modeling and control technology development for civil, energy, and power systems. Prospective authors are invited to submit their original contributions with the focus on theory or applications of modeling, control and decision. Topics of interest include modeling and control of, but are not limited to, the following：展开更多
The correlation between the grain size of electrodeposited coatings and the current densities was modeled by considering galvanostatic conditions. In order to test the model by experimental results, nanocrystalline ...The correlation between the grain size of electrodeposited coatings and the current densities was modeled by considering galvanostatic conditions. In order to test the model by experimental results, nanocrystalline （NC） nickel samples were deposited at different current densities using a Watts bath. The grain size of the deposits was evaluated by X-ray diffraction （XRD） technique. Model predictions were validated by finding a curve being the best-fit to the experimental results which were gathered from literature for different NC coatings in addition to those data measured in this research for NC nickel coatings. According to our model, the variation of grain size with the reciprocal of the current density follows a power law. A good agreement between the experimental results and model predictions was observed which indicated that the derived analytical model is applicable for producting the nanocrystalline electrodeposits with the desired grain size by controling current density.展开更多
The modeling and motion control of a universal part feeder is addressed. The feeder consists of a flat plate （or called bed） and a part placed on the plate. The bed can vibrate side-by-side （in x axis）, back and f...The modeling and motion control of a universal part feeder is addressed. The feeder consists of a flat plate （or called bed） and a part placed on the plate. The bed can vibrate side-by-side （in x axis）, back and forth （in y axis）, clockwise and counter clockwise （about z axis）, actuated by three linear motors （voice coils）. When the bed does these vibrations, the part placed on the plat will have position and/or orientation change due to the interaction between the two contact surfaces. By controlling the ways in which the plate vibrates, the position and orientation of the part can be controlled. The two vibration profiles of the bed are investigated in the research： the high-low vibration mode and the bang-bang vibration mode. The motion equations of the bed and the part as well as the control schemes for the high-low vibration mode are presented. Both simulation and real-time testing verify the system＇s dynamic model and indicate the feasibilities of the developed control laws.展开更多
A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by t...A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.展开更多
Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the s...Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilizatio...Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilization of train adhesion within the total torque command,reduce the train skidding/sliding phenomenon and achieve optimal adhesion utilization for each axle,thus realizing the optimal allocation of the multi-motor electric locomotives.Design/methodology/approach–In this study,a model predictive control(MPC)-based cooperative maximum adhesion tracking control method for multi-motor electric locomotives is presented.Firstly,train traction system with multiple motors is constructed in accordance with Newton’s second law.These equations include the train dynamics equations,the axle dynamics equations,and the wheel-rail adhesion coefficient equations.Then,a new MPC-based multi-axle adhesion co-optimization method is put forward.This method calculates the optimal output torque through real-time iteration based on the known reference slip speed to achieve multi-axle co-optimization under different circumstances.Findings–This paper presents a MPC system designed for the cooperative control of multi-axle adhesion.The results indicate that the proposed control system is able to optimize the adhesion of multiple axles under numerous different conditions and achieve the optimal power distribution based on the reduction of train skidding/sliding.Originality/value–This study presents a novel cooperative adhesion tracking control scheme.It is designed for multi-motor electric locomotives,which has rarely been studied before.And simulations are carried out in different conditions,including variable surfaces and motor failing.展开更多
Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluct...Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluctuation caused by new energy units,this paper proposes a new energy power system frequency regulation strategy with multiple units including the doubly-fed pumped storage unit(DFPSU).Firstly,based on the model predictive control(MPC)theory,the state space equations are established by considering the operating characteristics of the units and the dynamic behavior of the system;secondly,the proportional-differential control link is introduced to minimize the frequency deviation to further optimize the frequency modulation(FM)output of the DFPSU and inhibit the rapid fluctuation of the frequency;lastly,it is verified on theMatlab/Simulink simulation platform,and the results show that the model predictive control with proportional-differential control link can further release the FM potential of the DFPSU,increase the depth of its FM,effectively reduce the frequency deviation of the system and its rate of change,realize the optimization of the active output of the DFPSU and that of other units,and improve the frequency response capability of the system.展开更多
With regards to the assembly line of cost control of Dechang company,the motor housing′s cost control of process will be necessarily appreciated.Though the supply quantity is large in a machine and the price of motor...With regards to the assembly line of cost control of Dechang company,the motor housing′s cost control of process will be necessarily appreciated.Though the supply quantity is large in a machine and the price of motor housing is cheaper,the cost control of automatic production line is significant in this respection.It is found that insufficiency power is main cause for production line failure.The cost control of equipment includes to structure wheel,conveyor and motor for benefit which also needs to be controlled in detail.Only in this way can we fundamentally resolve the main problem of high cost process.When the capital price L increases,Avc also increases too with nonlinear meantime,and Tc&Vc increase in proportion to K.Among them,the Tc increases the highest and then Vc increases lightly.Generally when labour quantity L and capital quantity K increase cost increases in proportion.展开更多
This article proposes an algebraic model predictive control(MPC)method for automatic landing.While defining the constraint functions in the optimization problem,the tangent hyperbolic function is preferred.Therefore,t...This article proposes an algebraic model predictive control(MPC)method for automatic landing.While defining the constraint functions in the optimization problem,the tangent hyperbolic function is preferred.Therefore,the optimization problem turns into an unconstrained,continuous,and differentiable form.An analytical two-step method is also proposed to solve the rest of the problem.In the first step,it is assumed that only input constraints are active and states are unconstrained.The optimal solution for this case is calculated directly with the optimality condition.The calculated control signal is revised in the second step according to system dynamics and state constraints.Simulation results of the auto-landing system show that the MPC computation speed is significantly increased by the new algebraic MPC(AMPC)without compromising the control performance,which makes the method realistic for using MPC in systems with high-speed changing dynamics.展开更多
It is particularly challenging to develop a new control theory like human intelligence,as human cognition and decisionmaking are variable in changing environments.In this article,the idea of variable stability is adop...It is particularly challenging to develop a new control theory like human intelligence,as human cognition and decisionmaking are variable in changing environments.In this article,the idea of variable stability is adopted to design a human-like control algorithm,referred to as variable stability control.A variable model perturbation put into the system dynamics model is computed by model game control,which simulates changes in human cognition.Lyapunov stability control is employed to formulate a backstepping control law that mimics the underlying logic algorithm in human decision-making.Some variable algorithm parameters embedded into the control law are calculated using model predictive control,which imitates dynamic tuning in human decision-making.From another perspective,variable stability control is an algorithm-hybrid control approach validated in a steer-by-wire system for angle tracking.According to the experimental results,variable stability control is a promising candidate for angle tracking in steer-by-wire systems.展开更多
文摘Fluctuating voltage levels in power grids necessitate automatic voltage regulators(AVRs)to ensure stability.This study examined the modeling and control of AVR in hydroelectric power plants using model predictive control(MPC),which utilizes an extensive mathe-matical model of the voltage regulation system to optimize the control actions over a defined prediction horizon.This predictive feature enables MPC to minimize voltage deviations while accounting for operational constraints,thereby improving stability and performance under dynamic conditions.Thefindings were compared with those derived from an optimal proportional integral derivative(PID)con-troller designed using the artificial bee colony(ABC)algorithm.Although the ABC-PID method adjusts the PID parameters based on historical data,it may be difficult to adapt to real-time changes in system dynamics under constraints.Comprehensive simulations assessed both frameworks,emphasizing performance metrics such as disturbance rejection,response to load changes,and resilience to uncertainties.The results show that both MPC and ABC-PID methods effectively achieved accurate voltage regulation;however,MPC excelled in controlling overshoot and settling time—recording 0.0%and 0.25 s,respectively.This demonstrates greater robustness compared to conventional control methods that optimize PID parameters based on performance criteria derived from actual system behavior,which exhibited settling times and overshoots exceeding 0.41 s and 5.0%,respectively.The controllers were implemented using MATLAB/Simulink software,indicating a significant advancement for power plant engineers pursuing state-of-the-art automatic voltage regulations.
基金Supported by National Natural Science Foundation of China(Grant No.51375212)Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions of China+1 种基金Research Fund for the Doctoral Program of Higher Education of China(Grant No.20133227130001)China Postdoctoral Science Foundation(Grant No.2014M551518)
文摘The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical （MLD） modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller （HMPC） is tuned based on online mixed-integer quadratic optimization （MIQP）. Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology （MPT）, thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61371033 and 51407054)the Foundation for the Author of National Excellent Doctoral Dissertation of China(Grant No.201442)the Fundamental Research Funds for the Central Universities of China(Grant No.2682016CX035)
文摘By analyzing the output voltage ripple of a buck-boost converter with large equivalent series resistance（ESR） of output capacitor, one valley voltage-mode controller for buck-boost converter is proposed. Considering the fact that the increasing and decreasing slopes of the inductor current are assumed to be constant during each switching cycle, an especial sampleddata model of valley voltage-mode controlled buck-boost converter is established. Based on this model, the dynamical effect of an output-capacitor time-constant on the valley voltage-mode controlled buck-boost converter is revealed and analyzed via the bifurcation diagrams, the movements of eigenvalues, the Lyapunov exponent spectra, the boundary equations,and the operating-state regions. It is found that with gradual reduction of output-capacitor time-constant, the buck-boost converter in continuous conduction mode（CCM） shows the evolutive dynamic behavior from period-1 to period-2, period-4, period-8, chaos, and invalid state. The stability boundary and the invalidated boundary are derived theoretically by stability analysis, where the stable state of valley voltage-mode controlled buck-boost converter can enter into an unstable state, and the converter can shift from the operation region to a forbidden region. These results verified by time-domain waveforms and phase portraits of both simulation and experiment indicate that the sampled-data model is correct and the time constant of the output capacitor is a critical factor for valley voltage-mode controlled buck-boost converter, which has a significant effect on the dynamics as well as control stability.
基金Financial support from the National Key R&D Program of China(No.2017YFB0601805)。
文摘Nonlinear model predictive control(NMPC)scheme is an effective method of multi-objective optimization control in complex industrial systems.In this paper,a NMPC scheme for the wet limestone flue gas desulphurization(WFGD)system is proposed which provides a more flexible framework of optimal control and decision-making compared with PID scheme.At first,a mathematical model of the FGD process is deduced which is suitable for NMPC structure.To equipoise the model’s accuracy and conciseness,the wet limestone FGD system is separated into several modules.Based on the conservation laws,a model with reasonable simplification is developed to describe dynamics of different modules for the purpose of controller design.Then,by addressing economic objectives directly into the NMPC scheme,the NMPC controller can minimize economic cost and track the set-point simultaneously.The accuracy of model is validated by the field data of a 1000 MW thermal power plant in Henan Province,China.The simulation results show that the NMPC strategy improves the economic performance and ensures the emission requirement at the same time.In the meantime,the control scheme satisfies the multiobjective control requirements under complex operation conditions(e.g.,boiler load fluctuation and set point variation).The mathematical model and NMPC structure provides the basic work for the future development of advanced optimized control algorithms in the wet limestone FGD systems.
文摘This paper provides an introduction to a support vector machine, a new kernel-based technique introduced in statistical learning theory and structural risk minimization, then presents a modeling-control framework based on SVM. At last a numerical experiment is taken to demonstrate the proposed approach's correctness and effectiveness.
基金Financial support for this work is provided by the Shunde Environment ProtectionTransportation and Urban Administration Bureau(no.0851-1361FS02CL51)+5 种基金the Guangdong Provincial Science and Technology Plan Projects(no.2014A050503019)Guangzhou Environmental Protection Bureau(no.x2hjB2150020)supported by the funding of State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complexthe project of Atmospheric Haze Collaboration Control Technology Design(no.XDB05030400)from Chinese Academy of Sciencesthe Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund(U1501501)(the second phase)the Guangdong Provincial Engineering and Technology Research Center for Environmental Risk Prevention and Emergency Disposal(no.b2152120)
文摘To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Shunde＂ city as a pilot summer case study,we apply an innovative response surface modeling（RSM） methodology based on the Community Multi-Scale Air Quality（CMAQ） modeling simulations to identify the O_3 regime and provide dynamic analysis of the precursor contributions to effectively assess the O_3 impacts of volatile organic compound（VOC） control strategy.Our results show that Shunde is a typical VOC-limited urban O_3 polluted city.The ＂Jiangmen＂ city,as the main upper wind area during July 2014,its VOCs and nitrogen oxides（NO_x） emissions make up the largest contribution（9.06%）.On the contrary,the contribution from local（Shunde） emission is lowest（6.35%） among the seven neighbor regions.The local VOCs industrial source emission has the largest contribution comparing to other precursor emission sectors in Shunde.The results of dynamic source contribution analysis further show that the local NO_x control could slightly increase the ground O_3 under low（10.00%） and medium（40.00%）reduction ratios,while it could start to turn positive to decrease ground O_3 under the high NO_x abatement ratio（75.00%）.The real-time assessment of O_3 impacts from VOCs control strategies in Pearl River Delta（PRD） shows that the joint regional VOCs emission control policy will effectively reduce the ground O_3 concentration in Shunde.
基金supported by the Major Science and Technology Projects of Gansu Province(Grant No.20ZD7GF011)Gansu Province Higher Education Industry Support Plan Project:Research on the Collaborative Operation of Solar Thermal Storage+Wind-Solar Hybrid Power Generation--Based on“Integrated Energy Demonstration of Wind-Solar Energy Storage in Gansu Province”(Project No.2022CYZC-34).
文摘Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems.
基金This project is supported by Foundation of Public Laboratory on Robotics of Chinese Academy of Sciences.
文摘The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is designed. The recursive prediction error (RPE)algorithm which yields faster convergence than back propagation (BP) algorithm is applied to trainthe neural networks. The realization of RPE algorithm is given. The difference of modeling ofartificial muscles using neural networks with different input nodes and different hidden layer nodesis discussed. On this basis the nonlinear control scheme using neural networks for artificialmuscle system has been introduced. The experimental results show that the nonlinear control schemeyields faster response and higher control accuracy than the traditional linear control scheme.
基金Project supported by the National Natural Science Foundation of China(Nos.62273245 and 62173033)the Sichuan Science and Technology Program of China(No.2024NSFSC1486)the Opening Project of Robotic Satellite Key Laboratory of Sichuan Province of China。
文摘A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraints.First,an NN is used to fit the motion data of robot manipulators for data-driven dynamic modeling,converting it into a linear prediction model through gradients.Then,by statistically analyzing the stochastic characteristics of the NN modeling errors,a distributionally robust model predictive controller is designed based on the chance constraints,and the optimization problem is transformed into a tractable quadratic programming(QP)problem under the distributionally robust optimization(DRO)framework.The recursive feasibility and convergence of the proposed algorithm are proven.Finally,the effectiveness of the proposed algorithm is verified through numerical simulation.
文摘The control of civil, energy, and power systems presents significant new challenges for modeling and control theory. The purpose of this special issue is to provide a forum for researchers and practical engineers to discuss the recent advances in modeling and control technology development for civil, energy, and power systems. Prospective authors are invited to submit their original contributions with the focus on theory or applications of modeling, control and decision. Topics of interest include modeling and control of, but are not limited to, the following：
文摘The correlation between the grain size of electrodeposited coatings and the current densities was modeled by considering galvanostatic conditions. In order to test the model by experimental results, nanocrystalline （NC） nickel samples were deposited at different current densities using a Watts bath. The grain size of the deposits was evaluated by X-ray diffraction （XRD） technique. Model predictions were validated by finding a curve being the best-fit to the experimental results which were gathered from literature for different NC coatings in addition to those data measured in this research for NC nickel coatings. According to our model, the variation of grain size with the reciprocal of the current density follows a power law. A good agreement between the experimental results and model predictions was observed which indicated that the derived analytical model is applicable for producting the nanocrystalline electrodeposits with the desired grain size by controling current density.
文摘The modeling and motion control of a universal part feeder is addressed. The feeder consists of a flat plate （or called bed） and a part placed on the plate. The bed can vibrate side-by-side （in x axis）, back and forth （in y axis）, clockwise and counter clockwise （about z axis）, actuated by three linear motors （voice coils）. When the bed does these vibrations, the part placed on the plat will have position and/or orientation change due to the interaction between the two contact surfaces. By controlling the ways in which the plate vibrates, the position and orientation of the part can be controlled. The two vibration profiles of the bed are investigated in the research： the high-low vibration mode and the bang-bang vibration mode. The motion equations of the bed and the part as well as the control schemes for the high-low vibration mode are presented. Both simulation and real-time testing verify the system＇s dynamic model and indicate the feasibilities of the developed control laws.
基金Project(51005086)supported by the National Natural Science Foundation of ChinaProject(2010MS085)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(DMETKF2013008)supported by the Open Project of the State Key Laboratory of Digital Manufacturing Equipment and Technology,China
文摘A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.
基金supported in part by the National Natural Science Foundation of China under Grant 52077002。
文摘Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
基金supported by Scientific Research Projects of China Association of Metros(CAMET-KY-2022039)State Key Laboratory of Traction and Control System of EMU and Locomotive(2023YJ386).
文摘Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilization of train adhesion within the total torque command,reduce the train skidding/sliding phenomenon and achieve optimal adhesion utilization for each axle,thus realizing the optimal allocation of the multi-motor electric locomotives.Design/methodology/approach–In this study,a model predictive control(MPC)-based cooperative maximum adhesion tracking control method for multi-motor electric locomotives is presented.Firstly,train traction system with multiple motors is constructed in accordance with Newton’s second law.These equations include the train dynamics equations,the axle dynamics equations,and the wheel-rail adhesion coefficient equations.Then,a new MPC-based multi-axle adhesion co-optimization method is put forward.This method calculates the optimal output torque through real-time iteration based on the known reference slip speed to achieve multi-axle co-optimization under different circumstances.Findings–This paper presents a MPC system designed for the cooperative control of multi-axle adhesion.The results indicate that the proposed control system is able to optimize the adhesion of multiple axles under numerous different conditions and achieve the optimal power distribution based on the reduction of train skidding/sliding.Originality/value–This study presents a novel cooperative adhesion tracking control scheme.It is designed for multi-motor electric locomotives,which has rarely been studied before.And simulations are carried out in different conditions,including variable surfaces and motor failing.
基金supported by the National Natural Science Foundation of China(Project No.52377082)the Scientific Research Program of Jilin Provincial Department of Education(Project No.JJKH20230123KJ).
文摘Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluctuation caused by new energy units,this paper proposes a new energy power system frequency regulation strategy with multiple units including the doubly-fed pumped storage unit(DFPSU).Firstly,based on the model predictive control(MPC)theory,the state space equations are established by considering the operating characteristics of the units and the dynamic behavior of the system;secondly,the proportional-differential control link is introduced to minimize the frequency deviation to further optimize the frequency modulation(FM)output of the DFPSU and inhibit the rapid fluctuation of the frequency;lastly,it is verified on theMatlab/Simulink simulation platform,and the results show that the model predictive control with proportional-differential control link can further release the FM potential of the DFPSU,increase the depth of its FM,effectively reduce the frequency deviation of the system and its rate of change,realize the optimization of the active output of the DFPSU and that of other units,and improve the frequency response capability of the system.
文摘With regards to the assembly line of cost control of Dechang company,the motor housing′s cost control of process will be necessarily appreciated.Though the supply quantity is large in a machine and the price of motor housing is cheaper,the cost control of automatic production line is significant in this respection.It is found that insufficiency power is main cause for production line failure.The cost control of equipment includes to structure wheel,conveyor and motor for benefit which also needs to be controlled in detail.Only in this way can we fundamentally resolve the main problem of high cost process.When the capital price L increases,Avc also increases too with nonlinear meantime,and Tc&Vc increase in proportion to K.Among them,the Tc increases the highest and then Vc increases lightly.Generally when labour quantity L and capital quantity K increase cost increases in proportion.
文摘This article proposes an algebraic model predictive control(MPC)method for automatic landing.While defining the constraint functions in the optimization problem,the tangent hyperbolic function is preferred.Therefore,the optimization problem turns into an unconstrained,continuous,and differentiable form.An analytical two-step method is also proposed to solve the rest of the problem.In the first step,it is assumed that only input constraints are active and states are unconstrained.The optimal solution for this case is calculated directly with the optimality condition.The calculated control signal is revised in the second step according to system dynamics and state constraints.Simulation results of the auto-landing system show that the MPC computation speed is significantly increased by the new algebraic MPC(AMPC)without compromising the control performance,which makes the method realistic for using MPC in systems with high-speed changing dynamics.
文摘It is particularly challenging to develop a new control theory like human intelligence,as human cognition and decisionmaking are variable in changing environments.In this article,the idea of variable stability is adopted to design a human-like control algorithm,referred to as variable stability control.A variable model perturbation put into the system dynamics model is computed by model game control,which simulates changes in human cognition.Lyapunov stability control is employed to formulate a backstepping control law that mimics the underlying logic algorithm in human decision-making.Some variable algorithm parameters embedded into the control law are calculated using model predictive control,which imitates dynamic tuning in human decision-making.From another perspective,variable stability control is an algorithm-hybrid control approach validated in a steer-by-wire system for angle tracking.According to the experimental results,variable stability control is a promising candidate for angle tracking in steer-by-wire systems.
