The evolution of enabling technologies in wireless communications has paved the way for supporting novel applications with more demanding QoS requirements,but at the cost of increasing the complexity of optimizing the...The evolution of enabling technologies in wireless communications has paved the way for supporting novel applications with more demanding QoS requirements,but at the cost of increasing the complexity of optimizing the digital communication chain.In particular,Millimeter Wave(mmWave)communications provide an abundance of bandwidth,and energy harvesting supplies the network with a continual source of energy to facilitate self-sustainability;however,harnessing these technologies is challenging due to the stochastic dynamics of the mmWave channel as well as the random sporadic nature of the harvested energy.In this paper,we aim at the dynamic optimization of update transmissions in mmWave energy harvesting systems in terms of Age of Information(AoI).AoI has recently been introduced to quantify information freshness and is a more stringent QoS metric compared to conventional delay and throughput.However,most prior art has only addressed averagebased AoI metrics,which can be insufficient to capture the occurrence of rare but high-impact freshness violation events in time-critical scenarios.We formulate a control problem that aims to minimize the long-term entropic risk measure of AoI samples by configuring the“sense&transmit”of updates.Due to the high complexity of the exponential cost function,we reformulate the problem with an approximated mean-variance risk measure as the new objective.Under unknown system statistics,we propose a two-timescale model-free risk-sensitive reinforcement learning algorithm to compute a control policy that adapts to the trio of channel,energy,and AoI states.We evaluate the efficiency of the proposed scheme through extensive simulations.展开更多
A stochastic maximum principle for the risk-sensitive optimal control prob- lem of jump diffusion processes with an exponential-of-integral cost functional is derived assuming that the value function is smooth, where ...A stochastic maximum principle for the risk-sensitive optimal control prob- lem of jump diffusion processes with an exponential-of-integral cost functional is derived assuming that the value function is smooth, where the diffusion and jump term may both depend on the control. The form of the maximum principle is similar to its risk-neutral counterpart. But the adjoint equations and the maximum condition heavily depend on the risk-sensitive parameter. As applications, a linear-quadratic risk-sensitive control problem is solved by using the maximum principle derived and explicit optimal control is obtained.展开更多
The authors propose a data-driven direct adaptive control law based on the adaptive dynamic programming(ADP) algorithm for continuous-time stochastic linear systems with partially unknown system dynamics and infinite ...The authors propose a data-driven direct adaptive control law based on the adaptive dynamic programming(ADP) algorithm for continuous-time stochastic linear systems with partially unknown system dynamics and infinite horizon quadratic risk-sensitive indices.The authors use online data of the system to iteratively solve the generalized algebraic Riccati equation(GARE) and to learn the optimal control law directly.For the case with measurable system noises,the authors show that the adaptive control law approximates the optimal control law as time goes on.For the case with unmeasurable system noises,the authors use the least-square solution calculated only from the measurable data instead of the real solution of the regression equation to iteratively solve the GARE.The authors also study the influences of the intensity of the system noises,the intensity of the exploration noises,the initial iterative matrix,and the sampling period on the convergence of the ADP algorithm.Finally,the authors present two numerical simulation examples to demonstrate the effectiveness of the proposed algorithms.展开更多
This study advances the G-stochastic maximum principle(G-SMP)from a risk-neutral framework to a risk-sensitive one.A salient feature of this advancement is its applicability to systems governed by stochastic different...This study advances the G-stochastic maximum principle(G-SMP)from a risk-neutral framework to a risk-sensitive one.A salient feature of this advancement is its applicability to systems governed by stochastic differential equations under G-Brownian motion(G-SDEs),where the control variable may influence all terms.We aim to generalize our findings from a risk-neutral context to a risk-sensitive performance cost.Initially,we introduced an auxiliary process to address risk-sensitive performance costs within the G-expectation framework.Subsequently,we established and validated the correlation between the G-expected exponential utility and the G-quadratic backward stochastic differential equation.Furthermore,we simplified the G-adjoint process from a dual-component structure to a singular component.Moreover,we explained the necessary optimality conditions for this model by considering a convex set of admissible controls.To describe the main findings,we present two examples:the first addresses the linear-quadratic problem and the second examines a Merton-type problem characterized by power utility.展开更多
The optimal control of the partially observable stochastic system at the risk-sensitive cost is considered in this paper. The system dynamics has a general correlation between system and measurement noise. And the ris...The optimal control of the partially observable stochastic system at the risk-sensitive cost is considered in this paper. The system dynamics has a general correlation between system and measurement noise. And the risk-sensitive cost contains a general quadratic term (with cross terms and extra linear terms). The explicit solution of such a problem is presented here using the output feedback control method. This clean and direct derivation enables one to convert such partial observable problems into the equivalent complete observable control problems and use the routine ways to solve them.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
A new algorithm is proposed, which immolates the optimality of control policies potentially to obtain the robnsticity of solutions. The robnsticity of solutions maybe becomes a very important property for a learning s...A new algorithm is proposed, which immolates the optimality of control policies potentially to obtain the robnsticity of solutions. The robnsticity of solutions maybe becomes a very important property for a learning system when there exists non-matching between theory models and practical physical system, or the practical system is not static, or the availability of a control action changes along with the variety of time. The main contribution is that a set of approximation algorithms and their convergence results are given. A generalized average operator instead of the general optimal operator max （or rain） is applied to study a class of important learning algorithms, dynamic prOgramming algorithms, and discuss their convergences from theoretic point of view. The purpose for this research is to improve the robnsticity of reinforcement learning algorithms theoretically.展开更多
The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,...The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.展开更多
The risk-sensitive filtering design problem with respect to the exponential mean-square cost criterion is con-sidered for stochastic Gaussian systems with polynomial of second and third degree drift terms and intensit...The risk-sensitive filtering design problem with respect to the exponential mean-square cost criterion is con-sidered for stochastic Gaussian systems with polynomial of second and third degree drift terms and intensity parameters multiplying diffusion terms in the state and observations equations. The closed-form optimal fil-tering equations are obtained using quadratic value functions as solutions to the corresponding Focker- Plank-Kolmogorov equation. The performance of the obtained risk-sensitive filtering equations for stochastic polynomial systems of second and third degree is verified in a numerical example against the optimal po-lynomial filtering equations (and extended Kalman-Bucy for system polynomial of second degree), through comparing the exponential mean-square cost criterion values. The simulation results reveal strong advan-tages in favor of the designed risk-sensitive equations for some values of the intensity parameters.展开更多
This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic mo...This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.展开更多
The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow ...The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow controller(CFC)are demanded to ensure the multiterminal DC grid to operates reliably and flexibly.However,since the CFC and the DCCB are all based on fully controlled semiconductor switches(e.g.,insulated gate bipolar transistor,integrated gate commutated thyristor,etc.),their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses.To solve these problems,integrated equipment with both current flow control and fault isolation abilities is proposed,which shares the expensive and duplicated components of CFCs and DCCBs among adjacent lines.In addition,the complicated coordination control of CFCs and DCCBs can be avoided by adopting the integrated equipment in themultiterminal DC grid.In order to examine the current flow control and fault isolation abilities of the integrated equipment,the simulation model of a specific meshed four-terminal DC grid is constructed in the PSCAD/EMTDC software.Finally,the comparison between the integrated equipment and the separate solution is presented a specific result or conclusion needs to be added to the abstract.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
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
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
Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these...Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.展开更多
This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Ham...This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.展开更多
Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter us...Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.展开更多
Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford...Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.展开更多
文摘The evolution of enabling technologies in wireless communications has paved the way for supporting novel applications with more demanding QoS requirements,but at the cost of increasing the complexity of optimizing the digital communication chain.In particular,Millimeter Wave(mmWave)communications provide an abundance of bandwidth,and energy harvesting supplies the network with a continual source of energy to facilitate self-sustainability;however,harnessing these technologies is challenging due to the stochastic dynamics of the mmWave channel as well as the random sporadic nature of the harvested energy.In this paper,we aim at the dynamic optimization of update transmissions in mmWave energy harvesting systems in terms of Age of Information(AoI).AoI has recently been introduced to quantify information freshness and is a more stringent QoS metric compared to conventional delay and throughput.However,most prior art has only addressed averagebased AoI metrics,which can be insufficient to capture the occurrence of rare but high-impact freshness violation events in time-critical scenarios.We formulate a control problem that aims to minimize the long-term entropic risk measure of AoI samples by configuring the“sense&transmit”of updates.Due to the high complexity of the exponential cost function,we reformulate the problem with an approximated mean-variance risk measure as the new objective.Under unknown system statistics,we propose a two-timescale model-free risk-sensitive reinforcement learning algorithm to compute a control policy that adapts to the trio of channel,energy,and AoI states.We evaluate the efficiency of the proposed scheme through extensive simulations.
基金supported by the National Basic Research Program of China (973 Program, 2007CB814904)the National Natural Science Foundations of China (10921101)+2 种基金Shandong Province (2008BS01024, ZR2010AQ004)the Science Funds for Distinguished Young Scholars of Shandong Province (JQ200801)Shandong University (2009JQ004),the Independent Innovation Foundations of Shandong University (IIFSDU,2009TS036, 2010TS060)
文摘A stochastic maximum principle for the risk-sensitive optimal control prob- lem of jump diffusion processes with an exponential-of-integral cost functional is derived assuming that the value function is smooth, where the diffusion and jump term may both depend on the control. The form of the maximum principle is similar to its risk-neutral counterpart. But the adjoint equations and the maximum condition heavily depend on the risk-sensitive parameter. As applications, a linear-quadratic risk-sensitive control problem is solved by using the maximum principle derived and explicit optimal control is obtained.
基金supported in part by the National Natural Science Foundation of China under Grant No.62261136550in part by the Basic Research Project of Shanghai Science and Technology Commission under Grant No.20JC1414000。
文摘The authors propose a data-driven direct adaptive control law based on the adaptive dynamic programming(ADP) algorithm for continuous-time stochastic linear systems with partially unknown system dynamics and infinite horizon quadratic risk-sensitive indices.The authors use online data of the system to iteratively solve the generalized algebraic Riccati equation(GARE) and to learn the optimal control law directly.For the case with measurable system noises,the authors show that the adaptive control law approximates the optimal control law as time goes on.For the case with unmeasurable system noises,the authors use the least-square solution calculated only from the measurable data instead of the real solution of the regression equation to iteratively solve the GARE.The authors also study the influences of the intensity of the system noises,the intensity of the exploration noises,the initial iterative matrix,and the sampling period on the convergence of the ADP algorithm.Finally,the authors present two numerical simulation examples to demonstrate the effectiveness of the proposed algorithms.
基金supported by PRFU project N(Grant No.C00L03UN070120220004).
文摘This study advances the G-stochastic maximum principle(G-SMP)from a risk-neutral framework to a risk-sensitive one.A salient feature of this advancement is its applicability to systems governed by stochastic differential equations under G-Brownian motion(G-SDEs),where the control variable may influence all terms.We aim to generalize our findings from a risk-neutral context to a risk-sensitive performance cost.Initially,we introduced an auxiliary process to address risk-sensitive performance costs within the G-expectation framework.Subsequently,we established and validated the correlation between the G-expected exponential utility and the G-quadratic backward stochastic differential equation.Furthermore,we simplified the G-adjoint process from a dual-component structure to a singular component.Moreover,we explained the necessary optimality conditions for this model by considering a convex set of admissible controls.To describe the main findings,we present two examples:the first addresses the linear-quadratic problem and the second examines a Merton-type problem characterized by power utility.
基金This project was supported by the National Natural Science Foundation of China(60004005)the Excellent Young Teacher Program of MOE.
文摘The optimal control of the partially observable stochastic system at the risk-sensitive cost is considered in this paper. The system dynamics has a general correlation between system and measurement noise. And the risk-sensitive cost contains a general quadratic term (with cross terms and extra linear terms). The explicit solution of such a problem is presented here using the output feedback control method. This clean and direct derivation enables one to convert such partial observable problems into the equivalent complete observable control problems and use the routine ways to solve them.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金Supported by National Natural Science Foundation of China （10671112）, National Basic Research Program of China （973 Program） （2007CB814904）, the Natural Science Foundation of Shandong Province （Z2006A01）, and the Chinese New Century Young Teachers Program The authors would like to thank the referees for a careful reading of this paper and helpful suggestions which made the revised version more readable.
基金Project supported by the National Natural Science Foundation of China (Nos. 10471088 and 60572126)
文摘A new algorithm is proposed, which immolates the optimality of control policies potentially to obtain the robnsticity of solutions. The robnsticity of solutions maybe becomes a very important property for a learning system when there exists non-matching between theory models and practical physical system, or the practical system is not static, or the availability of a control action changes along with the variety of time. The main contribution is that a set of approximation algorithms and their convergence results are given. A generalized average operator instead of the general optimal operator max （or rain） is applied to study a class of important learning algorithms, dynamic prOgramming algorithms, and discuss their convergences from theoretic point of view. The purpose for this research is to improve the robnsticity of reinforcement learning algorithms theoretically.
基金supported by the State Grid Corporation of China Science and Technology Project,grant number 52270723000900K.
文摘The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.
文摘The risk-sensitive filtering design problem with respect to the exponential mean-square cost criterion is con-sidered for stochastic Gaussian systems with polynomial of second and third degree drift terms and intensity parameters multiplying diffusion terms in the state and observations equations. The closed-form optimal fil-tering equations are obtained using quadratic value functions as solutions to the corresponding Focker- Plank-Kolmogorov equation. The performance of the obtained risk-sensitive filtering equations for stochastic polynomial systems of second and third degree is verified in a numerical example against the optimal po-lynomial filtering equations (and extended Kalman-Bucy for system polynomial of second degree), through comparing the exponential mean-square cost criterion values. The simulation results reveal strong advan-tages in favor of the designed risk-sensitive equations for some values of the intensity parameters.
基金supported by the National Natural Science Foundation of China(Nos.62103052 and No.52175214)。
文摘This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.
基金supported in part by Natural Science Foundation of Jiangsu Province under Grant BK20230255Natural Science Foundation of Shandong Province under Grant ZR2023QE281.
文摘The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow controller(CFC)are demanded to ensure the multiterminal DC grid to operates reliably and flexibly.However,since the CFC and the DCCB are all based on fully controlled semiconductor switches(e.g.,insulated gate bipolar transistor,integrated gate commutated thyristor,etc.),their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses.To solve these problems,integrated equipment with both current flow control and fault isolation abilities is proposed,which shares the expensive and duplicated components of CFCs and DCCBs among adjacent lines.In addition,the complicated coordination control of CFCs and DCCBs can be avoided by adopting the integrated equipment in themultiterminal DC grid.In order to examine the current flow control and fault isolation abilities of the integrated equipment,the simulation model of a specific meshed four-terminal DC grid is constructed in the PSCAD/EMTDC software.Finally,the comparison between the integrated equipment and the separate solution is presented a specific result or conclusion needs to be added to the abstract.
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 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 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 Fundamental Research Funds for Central Public Welfare Research Institute,No.2020CZ-5(to WS and GS)the National Natural Science Foundation of China,No.31970970(to JSR)Fundamental Research Funds for the Central Universities,No.YWF-23-YG-QB-010(to JSR)。
文摘Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.
基金financially supported by Sichuan Science and Technology Program(Grant No.2023NSFSC1980).
文摘This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.
基金supported in part by the National Natural Science Foundation of China(61873348,6230 3266,62273200)JSPS(Japan Society for the Promotion of Science) KAKENHI(22H03998,23K25252)
文摘Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.
基金supported in part by the Universitat Politècnica de València under grant PAID-10-21supported through AMRITA Seed Grant(Proposal ID:ASG2022188)。
文摘Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.
