In tunnel construction,tunnel boring machine(TBM)tunnelling typically relies on manual experience with sub-optimal control parameters,which can easily lead to inefficiency and high costs.This study proposed an intelli...In tunnel construction,tunnel boring machine(TBM)tunnelling typically relies on manual experience with sub-optimal control parameters,which can easily lead to inefficiency and high costs.This study proposed an intelligent decision-making method for TBM tunnelling control parameters based on multiobjective optimization(MOO).First,the effective TBM operation dataset is obtained through data preprocessing of the Songhua River(YS)tunnel project in China.Next,the proposed method begins with developing machine learning models for predicting TBM tunnelling performance parameters(i.e.total thrust and cutterhead torque),rock mass classification,and hazard risks(i.e.tunnel collapse and shield jamming).Then,considering three optimal objectives,(i.e.,penetration rate,rock-breaking energy consumption,and cutterhead hob wear),the MOO framework and corresponding mathematical expression are established.The Pareto optimal front is solved using DE-NSGA-II algorithm.Finally,the optimal control parameters(i.e.,advance rate and cutterhead rotation speed)are obtained by the satisfactory solution determination criterion,which can balance construction safety and efficiency with satisfaction.Furthermore,the proposed method is validated through 50 cases of TBM tunnelling,showing promising potential of application.展开更多
Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic c...Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic consumption and better real-time performance. In this paper,a direct thrust controller design approach for gas turbine engine based on parameter dependent model is proposed. In order to ensure the stability of DTC control system based on parameter dependent model, there are usually conservatism detects. For the purpose of reducing the conservatism in the solution process of filter and controller, an Equilibrium Manifold Expansion(EME) model with bounded parameter variation of engine is established. The design conditions of Kalman filter for discrete-time EME system are introduced, and the proposed conditions have a certain suppression effect on the input noise of the system with bounded parameter variation.The engine thrust estimator stability and H∞filtering problems are solved by the polytopic quadratic Lyapunov function based on the Linear Matrix Inequalities(LMIs). To meet the performance requirements of thrust control, the Grey Wolf Optimization(GWO) algorithm is applied to optimize the PID control parameters. The proposed method is verified on a Hardware-in-Loop(HIL) platform. The simulation results demonstrate that the DTC framework can ensure the stability of engine closed-loop system in large range deviation tests. The filter and controller solution method considering the parameter variation boundary can obtain a solution that makes the system have better performance parameters. Moreover, the proposed filter has better thrust estimation performance than the traditional Kalman filter under the condition of sensor noise. Compared with Augmented Linear Quadratic Regulator(ALQR) controller, the PID controller optimized by GWO has a faster response in simulation.展开更多
An enhanced least mean square(LMS)error identification algorithm integrated with Kalman filtering is proposed to resolve accuracy degradation induced by nonlinear dynamics and parameter uncertainties in continuous rot...An enhanced least mean square(LMS)error identification algorithm integrated with Kalman filtering is proposed to resolve accuracy degradation induced by nonlinear dynamics and parameter uncertainties in continuous rotary electro-hydraulic servo systems.This enhancement accelerates convergence and improves accuracy compared with traditional LMS.A fifth-order identification mod-el is developed based on valve-controlled hydraulic motors,with parameters identified using Kalman filter state estimation and gradient smoothing.The results indicate that the improved LMS effectively enhances parameter identification.An advanced disturbance rejection controller(ADRC)is de-signed,and its performance is compared with an optimal proportional integral derivative(PID)con-troller through Simulink simulations.The results show that the ADRC fulfills the control specifications and expands the system’s operational bandwidth.展开更多
Dynamic impacts such as wind and earthquakes cause loss of life and economic damage.To ensure safety against these effects,various measures have been taken from past to present and solutions have been developed using ...Dynamic impacts such as wind and earthquakes cause loss of life and economic damage.To ensure safety against these effects,various measures have been taken from past to present and solutions have been developed using different technologies.Tall buildings are more susceptible to vibrations such as wind and earthquakes.Therefore,vibration control has become an important issue in civil engineering.This study optimizes tuned mass damper inerter(TMDI)using far-fault ground motion records.This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm.Structure displacement and total acceleration against earthquake load are analyzed to assess the performance of the TMDI system.The effect of the inerter when connected to different floors is observed,and the results are compared to the conventional tuned mass damper(TMD).It is indicated that the case of connecting the inerter force to the 5th floor gives better results.As a result,TMD and TMDI systems reduce the displacement by 21.87%and 25.45%,respectively,and the total acceleration by 25.45%and 19.59%,respectively.These percentage reductions indicated that the structure resilience against dynamic loads can be increased using control systems.展开更多
This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater ve...This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.展开更多
Vertical picking method is a predominate method used to harvest cotton crop.However,a vertical picking method may cause spindle bending of the cotton picker if spindles collide with stones on the cotton field.Thus,how...Vertical picking method is a predominate method used to harvest cotton crop.However,a vertical picking method may cause spindle bending of the cotton picker if spindles collide with stones on the cotton field.Thus,how to realize a precise height control of the cotton picker is a crucial issue to be solved.The objective of this study is to design a height control system to avoid the collision.To design it,the mathematical models are established first.Then a multi-objective optimization model represented by structure parameters and control parameters is proposed to take the pressure of chamber without piston,response time and displacement error of the height control system as the opti-mization objectives.An integrated optimization approach that combines optimization via simulation,particle swarm optimization and simulated annealing is proposed to solve the model.Simulation and experimental test results show that the proposed integrated optimization approach can not only reduce the pressure of chamber without piston,but also decrease the response time and displacement error of the height control system.展开更多
A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rat...A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.展开更多
The high-purity distillation column system is strongly nonlinear and coupled,which makes it difficult to control.Active disturbance rejection control(ADRC)has been widely used in distillation systems,but it has limita...The high-purity distillation column system is strongly nonlinear and coupled,which makes it difficult to control.Active disturbance rejection control(ADRC)has been widely used in distillation systems,but it has limitations in controlling distillation systems with large time delays since ADRC employs ESO and feedback control law to estimate the total disturbance of the system without considering the large time delays.This paper designs a proportion integral-type active disturbance rejection generalized predictive control(PI-ADRGPC)algorithm to control the distillation column system with large time delay.It replaces the PD controller in ADRC with a proportion integral-type generalized predictive control(PI-GPC),thereby improving the performance of control systems with large time delays.Since the proposed controller has many parameters and is difficult to tune,this paper proposes to use the grey wolf optimization(GWO)to tune these parameters,whose structure can also be used by other intelligent optimization algorithms.The performance of GWO tuned PI-ADRGPC is compared with the control performance of GWO tuned ADRC method,multi-verse optimizer(MVO)tuned PI-ADRGPC and MVO tuned ADRC.The simulation results show that the proposed strategy can track reference well and has a good disturbance rejection performance.展开更多
The heating technological requirement of the conventional PID control is difficult to guarantee which based on the precise mathematical model,because the heating furnace for heating treatment with the big inertia,the ...The heating technological requirement of the conventional PID control is difficult to guarantee which based on the precise mathematical model,because the heating furnace for heating treatment with the big inertia,the pure time delay and nonlinear time-varying.Proposed one kind optimized variable method of PID controller based on the genetic algorithm with improved BP network that better realized the completely automatic intelligent control of the entire thermal process than the classics critical purporting(Z-N)method.A heating furnace for the object was simulated with MATLAB,simulation results show that the control system has the quicker response characteristic,the better dynamic characteristic and the quite stronger robustness,which has some promotional value for the control of industrial furnace.展开更多
Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by co...Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by competition between distribution populations to reduce the search zone.This method is applied to design of optimal parameters of PID controllers with examples, and thesimulation results show that satisfactory performances are obtained.展开更多
Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical par...Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical parameters were monitored to evaluate their influence on the microbial communities present in composting. The CO2 evolution and the number of microorganisms were measured as the activity of composting. The results demonstrated that the optimum temperature, pH and moisture content were 56.5 - 59.5 degreesC, 7.0 - 8.5 and 55 % - 60%, respectively. Under the optimum conditions, the removal efficiency of petroleum hydrocarbon reached 83.29% after 30 days composting.展开更多
Combined with the advantages and disadvantages of tuned liquid damper (TLD) and tuned mass damper (TMD),a double tuned liquid mass damper (TLMD) is proposed by replacing the rigid connection of TLD with the spring str...Combined with the advantages and disadvantages of tuned liquid damper (TLD) and tuned mass damper (TMD),a double tuned liquid mass damper (TLMD) is proposed by replacing the rigid connection of TLD with the spring structure.The motion equation of a single-degree-of-freedom structure with a TLMD attached at its top is found under harmonic excitation.Comparing the energy consumption and amplitude of primary structure with equal mass ratio TMD,it is found that the energy dissipation performance of TLMD is better in the effective phase region.The interaction process between TLMD and structure is analyzed,and the formula of phase deviation between the relative velocity of tank and the displacement of primary structure is deduced.By analyzing the influence of mass ratio,frequency ratio,damping ratio and water depth ratio on the damping effect,the results show that the frequency ratio and liquid depth ratio have great influence on the size and location of deep resonance peak,and the mass ratio and damping ratio have great influence on the width of the effective frequency band.The formula of equivalent damping ratio is proposed based on the principle of energy and it is found that the equivalent damping ratio is related to the phase deviation and change with the frequency ratio of the external excitation.展开更多
As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was...As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was introduced for optimal design of EWMA and multivariate EWMA （MEWMA） control charts, in which the optimal parameter pair （ λ, k） or （ λ, h ） was searched by using the generalized regression neural network （GRNN）. The results indicate that the optimal parameter pair can be obtained effectively by the proposed strategy for a given in-control average running length （ARLo） and shift to detect under any conditions, removing the drawback of incompleteness existing in the tables that had been reported.展开更多
Trajectory planning under uncertain dynamics is critical for safety-critical systems like Unmanned Aerial Vehicles(UAVs),where uncertainties in aerodynamic force and control surface failure can lead to mission failure...Trajectory planning under uncertain dynamics is critical for safety-critical systems like Unmanned Aerial Vehicles(UAVs),where uncertainties in aerodynamic force and control surface failure can lead to mission failure.This paper proposes a Multi-stage Robust Optimization(MRO)framework to address nonlinear trajectory planning with bounded but unknown parameters.By integrating first-order sensitivity analysis and sequential optimization,the proposed method ensures robustness against worst-case parameter deviations while maintaining high terminal accuracy.Unlike existing approaches,this paper explicitly quantifies uncertainty propagation through sensitivity bounds and divides long-term planning into sub-stages to reduce cumulative errors.Simulations on a UAV model with uncertainties in aerodynamic coefficients,wind fields and coefficients of control inputs demonstrate that MRO achieves high terminal state accuracy and strong robustness.展开更多
This paper introduces an optimized backstepping control method for Flexible Airbreathing Hypersonic Vehicles(FAHVs).The approach incorporates nonlinear disturbance observation and reinforcement learning to address com...This paper introduces an optimized backstepping control method for Flexible Airbreathing Hypersonic Vehicles(FAHVs).The approach incorporates nonlinear disturbance observation and reinforcement learning to address complex control challenges.The Minimal Learning Parameter(MLP)technique is applied to manage unknown nonlinear dynamics,significantly reducing the computational load usually associated with Neural Network(NN)weight updates.To improve the control system robustness,an MLP-based nonlinear disturbance observer is designed,which estimates lumped disturbances,including flexibility effects,model uncertainties,and external disruptions within the FAHVs.In parallel,the control strategy integrates reinforcement learning using an MLP-based actor-critic framework within the backstepping design to achieve both optimality and robustness.The actor performs control actions,while the critic assesses the optimal performance index function.To minimize this index function,an adaptive gradient descent method constructs both the actor and critic.Lyapunov analysis is employed to demonstrate that all signals in the closed-loop system are semiglobally uniformly ultimately bounded.Simulation results confirm that the proposed control strategy delivers high control performance,marked by improved accuracy and reduced energy consumption.展开更多
Thin-walled aluminum alloy tube numerical control （NC） bending with small bending radius is a complex process with multi-factor coupling effects and multi-die constraints. A significance-based optimization method of...Thin-walled aluminum alloy tube numerical control （NC） bending with small bending radius is a complex process with multi-factor coupling effects and multi-die constraints. A significance-based optimization method of the parameters was proposed based on the finite element （FE） simulation, and the significance analysis of the processing parameters on the forming quality in terms of the maximum wall thinning ratio and the maximum cross section distortion degree was implemented using the fractional factorial design. The optimum value of the significant parameter, the clearance between the tube and the wiper die, was obtained, and the values of the other parameters, including the friction coefficients and the clearances between the tube and the dies, the mandrel extension length and the boost velocity were estimated. The results are applied to aluminum alloy tube NC bending d50 mm×1 mm×75 mm and d70 mm×1.5 mm×105 mm （initial tube outside diameter D0 × initial tube wall thickness t0 × bending radius R）, and qualified tubes are produced.展开更多
A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that...A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that AGA takes objective function as adaptability function directly,so it cuts down some unnecessary time expense because of float-point calculation of function conversion.The difference from SAA is that AGA need not execute a very long Markov chain iteration at each point of temperature, so it speeds up the convergence of solution and makes no assumption on the search space,so it is simple and easy to be implemented.It can be applied to a wide class of problems.The optimizing principle and the implementing steps of AGA were expounded. The example of the parameter optimization of a typical complex electromechanical system named temper mill shows that AGA is effective and superior to the conventional GA and SAA.The control system of temper mill optimized by AGA has the optimal performance in the adjustable ranges of its parameters.展开更多
An improved model of reciprocating compressor operation cycle with a stepless capacity control system is presented and influence of the key parameters of the system is evaluated. In the stepless capacity control syste...An improved model of reciprocating compressor operation cycle with a stepless capacity control system is presented and influence of the key parameters of the system is evaluated. In the stepless capacity control system of a reciprocating compressor,mechanical unloaders are used to partially hold suction valves open for a certain time during the compression stroke. The typical working process of the reciprocating compressor is changed by capacity regulation apparatus. However,some critical parameters like the hydraulic force acting at the unloader have not been rigorously studied in previous researches. Here an improved numerical model of a double acting reciprocating compressor under the control stepless capacity is proposed and verified by experimental trials. Numerical simulations are carried out to select and evaluate the acting force which definitely has an influence on indicator diagrams of compressors. It is observed that the optimized range of 350 N to 380 N is preferable for the unloader force such that the intensity of opening and closing impacts are minimized.展开更多
Based on the concept of optimal control solution to dynamic system parameters identification and the optimal control theory of deterministic system,dyna-mics system parameters identfication problem is brought into cor...Based on the concept of optimal control solution to dynamic system parameters identification and the optimal control theory of deterministic system,dyna-mics system parameters identfication problem is brought into correspondence with optimal control problem. Then the theory and algorithm of optimal control are introduced into the study of dynamic system parameters identification. According to the theory of Hamilton-Jacobi-Bellman (HJB) equations solution, the existence and uniqueness of optimal control solution to dynamic system parameters identification are resolved in this paper. At last, the parameters identification algorithm of determi-nistic dynamic system is presented also based on above mentioned theory and concept.展开更多
Based on the contents Of part (Ⅰ) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness o...Based on the contents Of part (Ⅰ) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness of the theory developed in this paper and part (Ⅰ), then the procedure of establishing HamiltonJacobi-Bellman (HJB) equations of parameters identification problem is presented.And then, parameters identification algorithm of stochastic dynamic system is introduced. At last, an application example-local nonlinear parameters identification of dynamic system is presented.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52179105)China Postdoctoral Science Foundation(Grant No.2024M762193)。
文摘In tunnel construction,tunnel boring machine(TBM)tunnelling typically relies on manual experience with sub-optimal control parameters,which can easily lead to inefficiency and high costs.This study proposed an intelligent decision-making method for TBM tunnelling control parameters based on multiobjective optimization(MOO).First,the effective TBM operation dataset is obtained through data preprocessing of the Songhua River(YS)tunnel project in China.Next,the proposed method begins with developing machine learning models for predicting TBM tunnelling performance parameters(i.e.total thrust and cutterhead torque),rock mass classification,and hazard risks(i.e.tunnel collapse and shield jamming).Then,considering three optimal objectives,(i.e.,penetration rate,rock-breaking energy consumption,and cutterhead hob wear),the MOO framework and corresponding mathematical expression are established.The Pareto optimal front is solved using DE-NSGA-II algorithm.Finally,the optimal control parameters(i.e.,advance rate and cutterhead rotation speed)are obtained by the satisfactory solution determination criterion,which can balance construction safety and efficiency with satisfaction.Furthermore,the proposed method is validated through 50 cases of TBM tunnelling,showing promising potential of application.
基金supported by the National Natural Science Foundation of China(No.52372371)the Science Center for Gas Turbine Project,China(Nos.P2022-B-V-002-001,P2022-B-V-001-001).
文摘Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic consumption and better real-time performance. In this paper,a direct thrust controller design approach for gas turbine engine based on parameter dependent model is proposed. In order to ensure the stability of DTC control system based on parameter dependent model, there are usually conservatism detects. For the purpose of reducing the conservatism in the solution process of filter and controller, an Equilibrium Manifold Expansion(EME) model with bounded parameter variation of engine is established. The design conditions of Kalman filter for discrete-time EME system are introduced, and the proposed conditions have a certain suppression effect on the input noise of the system with bounded parameter variation.The engine thrust estimator stability and H∞filtering problems are solved by the polytopic quadratic Lyapunov function based on the Linear Matrix Inequalities(LMIs). To meet the performance requirements of thrust control, the Grey Wolf Optimization(GWO) algorithm is applied to optimize the PID control parameters. The proposed method is verified on a Hardware-in-Loop(HIL) platform. The simulation results demonstrate that the DTC framework can ensure the stability of engine closed-loop system in large range deviation tests. The filter and controller solution method considering the parameter variation boundary can obtain a solution that makes the system have better performance parameters. Moreover, the proposed filter has better thrust estimation performance than the traditional Kalman filter under the condition of sensor noise. Compared with Augmented Linear Quadratic Regulator(ALQR) controller, the PID controller optimized by GWO has a faster response in simulation.
基金Supported by the National Natural Science Foundation of China(No.52375037)the Outstanding Youth of Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture(No.GDRC 20220801)+1 种基金the Graduate Innovation Fund Project of Beijing University of Civil Engineering and Architecture(No.PG2025160)the Special Fund for Cultivation Projects of Beijing University of Civil Engineering and Architecture(No.X24026).
文摘An enhanced least mean square(LMS)error identification algorithm integrated with Kalman filtering is proposed to resolve accuracy degradation induced by nonlinear dynamics and parameter uncertainties in continuous rotary electro-hydraulic servo systems.This enhancement accelerates convergence and improves accuracy compared with traditional LMS.A fifth-order identification mod-el is developed based on valve-controlled hydraulic motors,with parameters identified using Kalman filter state estimation and gradient smoothing.The results indicate that the improved LMS effectively enhances parameter identification.An advanced disturbance rejection controller(ADRC)is de-signed,and its performance is compared with an optimal proportional integral derivative(PID)con-troller through Simulink simulations.The results show that the ADRC fulfills the control specifications and expands the system’s operational bandwidth.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP)and the Ministry of Trade,Industry&Energy,Republic of Korea (RS-2024-00441420RS-2024-00442817).
文摘Dynamic impacts such as wind and earthquakes cause loss of life and economic damage.To ensure safety against these effects,various measures have been taken from past to present and solutions have been developed using different technologies.Tall buildings are more susceptible to vibrations such as wind and earthquakes.Therefore,vibration control has become an important issue in civil engineering.This study optimizes tuned mass damper inerter(TMDI)using far-fault ground motion records.This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm.Structure displacement and total acceleration against earthquake load are analyzed to assess the performance of the TMDI system.The effect of the inerter when connected to different floors is observed,and the results are compared to the conventional tuned mass damper(TMD).It is indicated that the case of connecting the inerter force to the 5th floor gives better results.As a result,TMD and TMDI systems reduce the displacement by 21.87%and 25.45%,respectively,and the total acceleration by 25.45%and 19.59%,respectively.These percentage reductions indicated that the structure resilience against dynamic loads can be increased using control systems.
基金supported by the National Natural Science Foundation of China (6197317561973172)Tianjin Natural Science Foundation (19JCZDJC32800)。
文摘This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.
基金Supported by National Natural Science Foundation of China(Grant No.51905448)Chongqing Technology Innovation and Application Program of China(Grant No.cstc2018jszx-cyzdX0183)Fundamental Research Funds for the Central Universities of China(Grant No.SWU119060).
文摘Vertical picking method is a predominate method used to harvest cotton crop.However,a vertical picking method may cause spindle bending of the cotton picker if spindles collide with stones on the cotton field.Thus,how to realize a precise height control of the cotton picker is a crucial issue to be solved.The objective of this study is to design a height control system to avoid the collision.To design it,the mathematical models are established first.Then a multi-objective optimization model represented by structure parameters and control parameters is proposed to take the pressure of chamber without piston,response time and displacement error of the height control system as the opti-mization objectives.An integrated optimization approach that combines optimization via simulation,particle swarm optimization and simulated annealing is proposed to solve the model.Simulation and experimental test results show that the proposed integrated optimization approach can not only reduce the pressure of chamber without piston,but also decrease the response time and displacement error of the height control system.
基金Project(2013CB733605)supported by the National Basic Research Program of ChinaProject(21176073)supported by the National Natural Science Foundation of China
文摘A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
基金funded by the National Natural Science Foundation of China(61973175,62073177 and 61973172)South African National Research Foundation(132797)+2 种基金South African National Research Foundation Incentive(114911)Eskom Tertiary Education Support Programme Grant of South AfricaTianjin Research Innovation Project for Postgraduate Students(2021YJSB018,2020YJSB003)。
文摘The high-purity distillation column system is strongly nonlinear and coupled,which makes it difficult to control.Active disturbance rejection control(ADRC)has been widely used in distillation systems,but it has limitations in controlling distillation systems with large time delays since ADRC employs ESO and feedback control law to estimate the total disturbance of the system without considering the large time delays.This paper designs a proportion integral-type active disturbance rejection generalized predictive control(PI-ADRGPC)algorithm to control the distillation column system with large time delay.It replaces the PD controller in ADRC with a proportion integral-type generalized predictive control(PI-GPC),thereby improving the performance of control systems with large time delays.Since the proposed controller has many parameters and is difficult to tune,this paper proposes to use the grey wolf optimization(GWO)to tune these parameters,whose structure can also be used by other intelligent optimization algorithms.The performance of GWO tuned PI-ADRGPC is compared with the control performance of GWO tuned ADRC method,multi-verse optimizer(MVO)tuned PI-ADRGPC and MVO tuned ADRC.The simulation results show that the proposed strategy can track reference well and has a good disturbance rejection performance.
基金This work was supported by the youth backbone teachers training program of Henan colleges and universities under Grant No.2016ggjs-287the project of science and technology of Henan province under Grant No.172102210124the Key Scientific Research projects in Colleges and Universities in Henan(Grant No.18B460003).
文摘The heating technological requirement of the conventional PID control is difficult to guarantee which based on the precise mathematical model,because the heating furnace for heating treatment with the big inertia,the pure time delay and nonlinear time-varying.Proposed one kind optimized variable method of PID controller based on the genetic algorithm with improved BP network that better realized the completely automatic intelligent control of the entire thermal process than the classics critical purporting(Z-N)method.A heating furnace for the object was simulated with MATLAB,simulation results show that the control system has the quicker response characteristic,the better dynamic characteristic and the quite stronger robustness,which has some promotional value for the control of industrial furnace.
文摘Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by competition between distribution populations to reduce the search zone.This method is applied to design of optimal parameters of PID controllers with examples, and thesimulation results show that satisfactory performances are obtained.
文摘Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical parameters were monitored to evaluate their influence on the microbial communities present in composting. The CO2 evolution and the number of microorganisms were measured as the activity of composting. The results demonstrated that the optimum temperature, pH and moisture content were 56.5 - 59.5 degreesC, 7.0 - 8.5 and 55 % - 60%, respectively. Under the optimum conditions, the removal efficiency of petroleum hydrocarbon reached 83.29% after 30 days composting.
基金the National Natural Science Foundation of China(Nos.51578434 and 51378500)。
文摘Combined with the advantages and disadvantages of tuned liquid damper (TLD) and tuned mass damper (TMD),a double tuned liquid mass damper (TLMD) is proposed by replacing the rigid connection of TLD with the spring structure.The motion equation of a single-degree-of-freedom structure with a TLMD attached at its top is found under harmonic excitation.Comparing the energy consumption and amplitude of primary structure with equal mass ratio TMD,it is found that the energy dissipation performance of TLMD is better in the effective phase region.The interaction process between TLMD and structure is analyzed,and the formula of phase deviation between the relative velocity of tank and the displacement of primary structure is deduced.By analyzing the influence of mass ratio,frequency ratio,damping ratio and water depth ratio on the damping effect,the results show that the frequency ratio and liquid depth ratio have great influence on the size and location of deep resonance peak,and the mass ratio and damping ratio have great influence on the width of the effective frequency band.The formula of equivalent damping ratio is proposed based on the principle of energy and it is found that the equivalent damping ratio is related to the phase deviation and change with the frequency ratio of the external excitation.
基金Funded by the National Key Technologies R&D Programs of China (No.2002BA105C)
文摘As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was introduced for optimal design of EWMA and multivariate EWMA （MEWMA） control charts, in which the optimal parameter pair （ λ, k） or （ λ, h ） was searched by using the generalized regression neural network （GRNN）. The results indicate that the optimal parameter pair can be obtained effectively by the proposed strategy for a given in-control average running length （ARLo） and shift to detect under any conditions, removing the drawback of incompleteness existing in the tables that had been reported.
基金supported by the National Natural Science Foundation of China(No.92471204)Youth Innovation Promotion Association,CAS,China。
文摘Trajectory planning under uncertain dynamics is critical for safety-critical systems like Unmanned Aerial Vehicles(UAVs),where uncertainties in aerodynamic force and control surface failure can lead to mission failure.This paper proposes a Multi-stage Robust Optimization(MRO)framework to address nonlinear trajectory planning with bounded but unknown parameters.By integrating first-order sensitivity analysis and sequential optimization,the proposed method ensures robustness against worst-case parameter deviations while maintaining high terminal accuracy.Unlike existing approaches,this paper explicitly quantifies uncertainty propagation through sensitivity bounds and divides long-term planning into sub-stages to reduce cumulative errors.Simulations on a UAV model with uncertainties in aerodynamic coefficients,wind fields and coefficients of control inputs demonstrate that MRO achieves high terminal state accuracy and strong robustness.
基金co-supported by the National Natural Science Foundation of China(Nos.62303380,62176214,62101590,62003268)。
文摘This paper introduces an optimized backstepping control method for Flexible Airbreathing Hypersonic Vehicles(FAHVs).The approach incorporates nonlinear disturbance observation and reinforcement learning to address complex control challenges.The Minimal Learning Parameter(MLP)technique is applied to manage unknown nonlinear dynamics,significantly reducing the computational load usually associated with Neural Network(NN)weight updates.To improve the control system robustness,an MLP-based nonlinear disturbance observer is designed,which estimates lumped disturbances,including flexibility effects,model uncertainties,and external disruptions within the FAHVs.In parallel,the control strategy integrates reinforcement learning using an MLP-based actor-critic framework within the backstepping design to achieve both optimality and robustness.The actor performs control actions,while the critic assesses the optimal performance index function.To minimize this index function,an adaptive gradient descent method constructs both the actor and critic.Lyapunov analysis is employed to demonstrate that all signals in the closed-loop system are semiglobally uniformly ultimately bounded.Simulation results confirm that the proposed control strategy delivers high control performance,marked by improved accuracy and reduced energy consumption.
基金Projects (50905144, 50875216) supported by the National Natural Science Foundation of ChinaProject (09-10) supported by the State Key Laboratory of Materials Processing and Die & Mould Technology, ChinaProject (JC201028) supported by the Northwestern Polytechnical University Foundation for Fundamental Research, China
文摘Thin-walled aluminum alloy tube numerical control （NC） bending with small bending radius is a complex process with multi-factor coupling effects and multi-die constraints. A significance-based optimization method of the parameters was proposed based on the finite element （FE） simulation, and the significance analysis of the processing parameters on the forming quality in terms of the maximum wall thinning ratio and the maximum cross section distortion degree was implemented using the fractional factorial design. The optimum value of the significant parameter, the clearance between the tube and the wiper die, was obtained, and the values of the other parameters, including the friction coefficients and the clearances between the tube and the dies, the mandrel extension length and the boost velocity were estimated. The results are applied to aluminum alloy tube NC bending d50 mm×1 mm×75 mm and d70 mm×1.5 mm×105 mm （initial tube outside diameter D0 × initial tube wall thickness t0 × bending radius R）, and qualified tubes are produced.
文摘A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that AGA takes objective function as adaptability function directly,so it cuts down some unnecessary time expense because of float-point calculation of function conversion.The difference from SAA is that AGA need not execute a very long Markov chain iteration at each point of temperature, so it speeds up the convergence of solution and makes no assumption on the search space,so it is simple and easy to be implemented.It can be applied to a wide class of problems.The optimizing principle and the implementing steps of AGA were expounded. The example of the parameter optimization of a typical complex electromechanical system named temper mill shows that AGA is effective and superior to the conventional GA and SAA.The control system of temper mill optimized by AGA has the optimal performance in the adjustable ranges of its parameters.
基金Supported by the National Key Research and Development Plan(No.2016YFF0203305)the National High Technology Research and Development Programme of China(No.2014AA041806)the Fundamental Research Funds for the Central Universities(No.ZY1617)
文摘An improved model of reciprocating compressor operation cycle with a stepless capacity control system is presented and influence of the key parameters of the system is evaluated. In the stepless capacity control system of a reciprocating compressor,mechanical unloaders are used to partially hold suction valves open for a certain time during the compression stroke. The typical working process of the reciprocating compressor is changed by capacity regulation apparatus. However,some critical parameters like the hydraulic force acting at the unloader have not been rigorously studied in previous researches. Here an improved numerical model of a double acting reciprocating compressor under the control stepless capacity is proposed and verified by experimental trials. Numerical simulations are carried out to select and evaluate the acting force which definitely has an influence on indicator diagrams of compressors. It is observed that the optimized range of 350 N to 380 N is preferable for the unloader force such that the intensity of opening and closing impacts are minimized.
文摘Based on the concept of optimal control solution to dynamic system parameters identification and the optimal control theory of deterministic system,dyna-mics system parameters identfication problem is brought into correspondence with optimal control problem. Then the theory and algorithm of optimal control are introduced into the study of dynamic system parameters identification. According to the theory of Hamilton-Jacobi-Bellman (HJB) equations solution, the existence and uniqueness of optimal control solution to dynamic system parameters identification are resolved in this paper. At last, the parameters identification algorithm of determi-nistic dynamic system is presented also based on above mentioned theory and concept.
文摘Based on the contents Of part (Ⅰ) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness of the theory developed in this paper and part (Ⅰ), then the procedure of establishing HamiltonJacobi-Bellman (HJB) equations of parameters identification problem is presented.And then, parameters identification algorithm of stochastic dynamic system is introduced. At last, an application example-local nonlinear parameters identification of dynamic system is presented.
