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
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
This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satis...This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satisfy different performance criteria imposed at different sampling times.In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system,the dual-mode control method is used to design the switching MOMPC controller.In this method,a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC.The correction term is computed if the states are out of the terminal set and the free-parameters of the local control law are computed if the states are in the terminal set.The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions.Finally,implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor.展开更多
It is generally difficult to design feedback controls of nonlinear systems with time delay to meet time domain specifications such as rise time, overshoot, and tracking error. Furthermore, these time domain specificat...It is generally difficult to design feedback controls of nonlinear systems with time delay to meet time domain specifications such as rise time, overshoot, and tracking error. Furthermore, these time domain specifications tend to be conflicting to each other to make the control design even more challenging. This paper presents a cell mapping method for multi-objective optimal feedback control design in time domain for a nonlinear Duffing system with time delay. We first review the multi-objective optimization problem and its formulation for control design. We then introduce the cell mapping method and a hybrid algorithm for global optimal solutions. Numerical simulations of the PID control are presented to show the features of the multi-objective optimal design. @ 2013 The Chinese Society of Theoretical and Applied Mechanics. [doi：10.1063/2.1306306]展开更多
Power systems are pivotal in providing sustainable energy across various sectors.However,optimizing their performance to meet modern demands remains a significant challenge.This paper introduces an innovative strategy...Power systems are pivotal in providing sustainable energy across various sectors.However,optimizing their performance to meet modern demands remains a significant challenge.This paper introduces an innovative strategy to improve the opti-mization of PID controllers within nonlinear oscillatory Automatic Generation Control(AGC)systems,essential for the stability of power systems.Our approach aims to reduce the integrated time squared error,the integrated time absolute error,and the rate of change in deviation,facilitating faster convergence,diminished overshoot,and decreased oscillations.By incorporating the spiral model from the Whale Optimization Algorithm(WOA)into the Multi-Objective Marine Predator Algorithm(MOMPA),our method effectively broadens the diversity of solution sets and finely tunes the balance between exploration and exploitation strategies.Furthermore,the QQSMOMPA framework integrates quasi-oppositional learning and Q-learning to overcome local optima,thereby generating optimal Pareto solutions.When applied to nonlinear AGC systems featuring governor dead zones,the PID controllers optimized by QQSMOMPA not only achieve 14%reduction in the frequency settling time but also exhibit robustness against uncertainties in load disturbance inputs.展开更多
Rollover and jack-knifing of tractor semi-trailer are serious threats for vehicle safety, and accordingly active safety technologies have been widely used to reduce or prevent the occurrence of such accidents. However...Rollover and jack-knifing of tractor semi-trailer are serious threats for vehicle safety, and accordingly active safety technologies have been widely used to reduce or prevent the occurrence of such accidents. However, currently tractor semi-trailer stability control is generally only a single hazardous condition (rollover or jack-knifing) control, it is difficult to ensure the vehicle comprehensive stability of various dangerous conditions. The main objective of this study is to introduce a multi-objective stability control algorithm which can improve the vehicle stability of a tractor semi-trailer by using differential braking. A vehicle controller is designed to minimize the likelihood of rollover and jack-knifing. First a linear vehicle model of tractor semi-trailer is constructed. Then an optimal yaw control for tractor using differential braking is applied to minimize the yaw rate and lateral acceleration deviation of tractor, as well as the hitch articulation angle of tractor semi-trailer, so as to improve the vehicle stability. Second a braking scheme and variable structure control with sliding mode control are introduced in order to achieve the best braking effect. Last Fishhook maneuver is introduced to the active safety simulation and the active control system effect verification. The simulation results show that multi-objective stability control algorithm of semi-trailer could improve the vehicle stability significantly during the transient maneuvers. The proposed multi-objective stability control algorithm is effective to prevent the vehicle rollover and jackknifing.展开更多
For different flight phases in an overall flight mission,different control and allocation preferences should be pursued considering lift,drag or maneuverability characteristics.The multi-objective flight control alloc...For different flight phases in an overall flight mission,different control and allocation preferences should be pursued considering lift,drag or maneuverability characteristics.The multi-objective flight control allocation problem for a multi-phase flight mission is studied.For an overall flight mission,different flight phases namely climbing,cruise,maneuver and gliding phases are defined.Firstly,a multi-objective control allocation problem considering drag,lift or control energy preference is constructed.Secondly,considering different control preferences at different flight phases,the analytic hierarchical process method is used to construct a comprehensive performance index from different objectives such as lift or drag preferences.The active set based dynamic programming optimization method is used to solve the real-time optimization problem.For the validation,the Innovative Control Effector(ICE)tailless aircraft nonlinear model and the angular acceleration measurements based adaptive Incremental Backstepping(IBKS)are used to construct the validation platform.Finally,an overall flight mission is simulated to demonstrate the efficiency of the proposed multi-phase and multi-objective flight control allocation method.The results show that the comprehensive performance index for different phases,which are determined from the Analytic Hierarchy Process(AHP)method,can suitably satisfy the preference requirements for different flight phases.展开更多
For automated vehicles,comfortable driving will improve passengers’ satisfaction.Reducing fuel consumption brings economic profits for car owners,decreases the impact on the environment and increases energy sustainab...For automated vehicles,comfortable driving will improve passengers’ satisfaction.Reducing fuel consumption brings economic profits for car owners,decreases the impact on the environment and increases energy sustainability.In addition to comfort and fuel-economy,automated vehicles also have the basic requirements of safety and car-following.For this purpose,an adaptive cruise control (ACC) algorithm with multi-objectives is proposed based on a model predictive control (MPC) framework.In the proposed ACC algorithm,safety is guaranteed by constraining the inter-distance within a safe range; the requirements of comfort and car-following are considered to be the performance criteria and some optimal reference trajectories are introduced to increase fuel-economy.The performances of the proposed ACC algorithm are simulated and analyzed in five representative traffic scenarios and multiple experiments.The results show that not only are safety and car-following objectives satisfied,but also driving comfort and fuel-economy are improved significantly.展开更多
This paper presents a numerical algorithm tuning aircraft landing gear control system with three objectives,including reducing relative vibration, reducing hydraulic strut force and controlling energy consumption. Sli...This paper presents a numerical algorithm tuning aircraft landing gear control system with three objectives,including reducing relative vibration, reducing hydraulic strut force and controlling energy consumption. Sliding mode control is applied to the vibration control of a simplified landing gear model with uncertainty. A two-stage generalized cell mapping algorithm is applied to search the Pareto set with gradient-free scheme. Drop test simulations over uneven runway show that the vibration and force interaction can be considerably reduced, and the Pareto optimum form a tight range in time domain.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2 (GH2) conditions to a set of new linear matrix inequality (LMI) constra...This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2 (GH2) conditions to a set of new linear matrix inequality (LMI) constraints based on a new stability condition. A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables. Consequently, the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.展开更多
A model-assistant extended state observer(MESO)-based decoupling control strategy is proposed for boiler-turbine units in the presence of unknown external disturbance and model-plant mismatch. For ease of implementati...A model-assistant extended state observer(MESO)-based decoupling control strategy is proposed for boiler-turbine units in the presence of unknown external disturbance and model-plant mismatch. For ease of implementation, the decoupling compensator is reduced to the proportion integration(PI) decoupler with the frequency domain analysis, where the decoupling error in collusion of uncertainties and disturbances can be estimated by the proposed MESO and then compensated. To decrease the sensitivity of the dynamic error for the decoupling control and fulfill various requirements of constraints, such as safety operation, energy conservation, emission reduction, etc., the plant is transmitted through a scheduled steady state region which is achieved from the optimized reference governor in advance. Simulation results show that the proposed control strategy can well suppress various disturbances including a decoupling error, and multi-objective optimization can meet multiple requirements with the premise of safety production.展开更多
CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system efficiency.It has a highly nonlinear characteristic that includes complexities...CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system efficiency.It has a highly nonlinear characteristic that includes complexities in its control and design.Dynamic performance is compassionate to change in system parameterswhich need more effort for planning a significant controller for CSTR.The reactor temperature changes in either direction from the defined reference value.It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature,and deviation from reference values may cause degradation of biomass quality.Design and implementation of an appropriate adaptive controller for such a nonlinear system are essential.In this paper,a conventional Proportional Integral Derivative(PID)controller is designed.The conventional techniques to deal with constraints suffer severe limitations like it has fixed controller parameters.Hence,A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s limitation.In the proposed technique,PID parameters are tuned by Particle Swarm Optimization(PSO).It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal response.In this article,a multi-objective function is proposed for PSO based controller design of CSTR.展开更多
The output uncertainty of high-proportion distributed power generation severely affects the system voltage and frequency.Simultaneously,controllable loads have also annually increased,which markedly improve the capabi...The output uncertainty of high-proportion distributed power generation severely affects the system voltage and frequency.Simultaneously,controllable loads have also annually increased,which markedly improve the capability for nodal-power control.To maintain the system frequency and voltage magnitude around rated values,a new multi-objective optimization model for both voltage and frequency control is proposed.Moreover,a great similarity between the multiobjective optimization and game problems appears.To reduce the strong subjectivity of the traditional methods,the idea and method of the game theory are introduced into the solution.According to the present situational data and analysis of the voltage and frequency sensitivities to nodal-power variations,the design variables involved in the voltage and frequency control are classified into two strategy spaces for players using hierarchical clustering.Finally,the effectiveness and rationality of the proposed control are verified in MATLAB.展开更多
This article studies the existence and uniqueness of the mild solution of a family of control systems with a delay that are governed by the nonlinear fractional evolution differential equations in Banach spaces.Moreov...This article studies the existence and uniqueness of the mild solution of a family of control systems with a delay that are governed by the nonlinear fractional evolution differential equations in Banach spaces.Moreover,we establish the controllability of the considered system.To do so,first,we investigate the approximate controllability of the corresponding linear system.Subsequently,we prove the nonlinear system is approximately controllable if the corresponding linear system is approximately controllable.To reach the conclusions,the theory of resolvent operators,the Banach contraction mapping principle,and fixed point theorems are used.While concluding,some examples are given to demonstrate the efficacy of the proposed results.展开更多
In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range pre...In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.展开更多
The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces ...The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.展开更多
To deal with the increasing demand for low-volume customization of the mechanical properties of cold-rolled products, a two-way control method based on mechanical property prediction and process parameter optimization...To deal with the increasing demand for low-volume customization of the mechanical properties of cold-rolled products, a two-way control method based on mechanical property prediction and process parameter optimization(PPO) has become an effective solution. Aiming at the multi-objective quality control problem of a company's cold-rolled products, based on industrial production data, we proposed a process parameter design and optimization method that combined multi-objective quality prediction and PPO. This method used the multi-output support vector regression(MSVR) method to simultaneously predict multiple quality indices. The MSVR prediction model was used as the effect verification model of the PPO results. It performed multi-process parameter collaborative design and realized the optimization of production process parameters for customized multi-objective quality requirements. The experimental results showed that, compared with the traditional single-objective quality prediction model based on support vector regression(SVR), the multi-objective prediction model could better take into account the coupling effect between process parameters and quality index, the MSVR model prediction accuracy was higher than that of the SVR, and the optimized process parameters were more capable and reflected the influence of metallurgical mechanism on the quality index,which were more in line with actual production process requirements.展开更多
To get the satisfying performance of a PID controller, this paper presents a novel Pareto-based multi-objective genetic algorithm (MOGA), which can be used to find the appropriate setting of the PID controller by anal...To get the satisfying performance of a PID controller, this paper presents a novel Pareto-based multi-objective genetic algorithm (MOGA), which can be used to find the appropriate setting of the PID controller by analyzing the pareto optimal surfaces. Rated settings of the controller by two criteria, the error between output and reference signals and control moves, are listed on the pareto surface. Appropriate setting can be chosen under a balance between two criteria for different control purposes. A controller tuning problem for a plant with high order and time delay is chosen as an example. Simulation results show that the method of MOGA is more efficient compared with traditional tuning methods.展开更多
The aircraft engine multi-loop control system is described and the switching control theory is introduced to solve the regulating and protecting control problems in this paper. The aircraft engine multi-loop control s...The aircraft engine multi-loop control system is described and the switching control theory is introduced to solve the regulating and protecting control problems in this paper. The aircraft engine multi-loop control system is firstly described and the control problems are formulated. Secondly, the theory of the smooth switching control is devoted and a new extended scheme for the smooth switching of a switched control system is introduced. Then, for the key technologies of aero-engines switching control, a design algorithm is presented which can determine which candidate controller should be put in feedback with the plant to achieve a desired performance and the procedure to design the aircraft engine multi-loop control system is detailed. The switching performance objectives and the switching scheme are given and a family of PID controllers and compensators is designed. The simulation shows that using the switching control design method can not only improve the dynamic performance of the aircraft engine control system and reduce the switching times, but also guarantee the stability in some peculiar occasions.展开更多
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 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(61374111)the Natural Science Foundation of Zhejiang Province(LY13F030006)Agricultural Key Program of Ningbo City(2014C10068)
文摘This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satisfy different performance criteria imposed at different sampling times.In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system,the dual-mode control method is used to design the switching MOMPC controller.In this method,a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC.The correction term is computed if the states are out of the terminal set and the free-parameters of the local control law are computed if the states are in the terminal set.The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions.Finally,implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor.
基金supported by the UC MEXUSCONACyT("Cell-to-cell Mapping for Global Multi-objective Optimization")the National Natural Science Foundation of China(11172197)+1 种基金the Natural Science Foundation of Tianjin through a key-project grantsupport from CONACyT through a scholarship to pursue graduate studies at the Computer Science Department of CINVESTAV-IPN
文摘It is generally difficult to design feedback controls of nonlinear systems with time delay to meet time domain specifications such as rise time, overshoot, and tracking error. Furthermore, these time domain specifications tend to be conflicting to each other to make the control design even more challenging. This paper presents a cell mapping method for multi-objective optimal feedback control design in time domain for a nonlinear Duffing system with time delay. We first review the multi-objective optimization problem and its formulation for control design. We then introduce the cell mapping method and a hybrid algorithm for global optimal solutions. Numerical simulations of the PID control are presented to show the features of the multi-objective optimal design. @ 2013 The Chinese Society of Theoretical and Applied Mechanics. [doi：10.1063/2.1306306]
基金supported in part by the National Natural Science Foundation of China under Grant 61873130in part by the Chunhui Program Collaborative Scientific Research Project under Grant 202202004+4 种基金in part by the Foundation of the Key Laboratory of Industrial Internet of Things and Networked Control of the Ministry of Education of China under Grant 2021FF01in part by the Natural Science Foundation of Nanjing University of Posts and Telecommunications under Grant NY221082,Grant NY222144,and Grant NY223075in part by the Huali Program for Excellent Talents in Nanjing University of Posts and Telecommunicationsin part by the Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grantin part by the Fundamental Research Funds for the Central Universities under WUT:104972024KFYjc0072.
文摘Power systems are pivotal in providing sustainable energy across various sectors.However,optimizing their performance to meet modern demands remains a significant challenge.This paper introduces an innovative strategy to improve the opti-mization of PID controllers within nonlinear oscillatory Automatic Generation Control(AGC)systems,essential for the stability of power systems.Our approach aims to reduce the integrated time squared error,the integrated time absolute error,and the rate of change in deviation,facilitating faster convergence,diminished overshoot,and decreased oscillations.By incorporating the spiral model from the Whale Optimization Algorithm(WOA)into the Multi-Objective Marine Predator Algorithm(MOMPA),our method effectively broadens the diversity of solution sets and finely tunes the balance between exploration and exploitation strategies.Furthermore,the QQSMOMPA framework integrates quasi-oppositional learning and Q-learning to overcome local optima,thereby generating optimal Pareto solutions.When applied to nonlinear AGC systems featuring governor dead zones,the PID controllers optimized by QQSMOMPA not only achieve 14%reduction in the frequency settling time but also exhibit robustness against uncertainties in load disturbance inputs.
基金supported by Open Research Fund of State Key Laboratory of Automobile Dynamics Simulation, China (Grant No. 20101103)National Natural Science Foundation of China (Grant No. 51075176)
文摘Rollover and jack-knifing of tractor semi-trailer are serious threats for vehicle safety, and accordingly active safety technologies have been widely used to reduce or prevent the occurrence of such accidents. However, currently tractor semi-trailer stability control is generally only a single hazardous condition (rollover or jack-knifing) control, it is difficult to ensure the vehicle comprehensive stability of various dangerous conditions. The main objective of this study is to introduce a multi-objective stability control algorithm which can improve the vehicle stability of a tractor semi-trailer by using differential braking. A vehicle controller is designed to minimize the likelihood of rollover and jack-knifing. First a linear vehicle model of tractor semi-trailer is constructed. Then an optimal yaw control for tractor using differential braking is applied to minimize the yaw rate and lateral acceleration deviation of tractor, as well as the hitch articulation angle of tractor semi-trailer, so as to improve the vehicle stability. Second a braking scheme and variable structure control with sliding mode control are introduced in order to achieve the best braking effect. Last Fishhook maneuver is introduced to the active safety simulation and the active control system effect verification. The simulation results show that multi-objective stability control algorithm of semi-trailer could improve the vehicle stability significantly during the transient maneuvers. The proposed multi-objective stability control algorithm is effective to prevent the vehicle rollover and jackknifing.
基金co-supported by the National Natural Science Foundation of China(No.11502008)Aeronautical Science Foundation of China(Nos.2017ZA51002,20185702003)the Fundamental Research Funds for the Central Universities of China(No.YWF-19-BJ-J-280)。
文摘For different flight phases in an overall flight mission,different control and allocation preferences should be pursued considering lift,drag or maneuverability characteristics.The multi-objective flight control allocation problem for a multi-phase flight mission is studied.For an overall flight mission,different flight phases namely climbing,cruise,maneuver and gliding phases are defined.Firstly,a multi-objective control allocation problem considering drag,lift or control energy preference is constructed.Secondly,considering different control preferences at different flight phases,the analytic hierarchical process method is used to construct a comprehensive performance index from different objectives such as lift or drag preferences.The active set based dynamic programming optimization method is used to solve the real-time optimization problem.For the validation,the Innovative Control Effector(ICE)tailless aircraft nonlinear model and the angular acceleration measurements based adaptive Incremental Backstepping(IBKS)are used to construct the validation platform.Finally,an overall flight mission is simulated to demonstrate the efficiency of the proposed multi-phase and multi-objective flight control allocation method.The results show that the comprehensive performance index for different phases,which are determined from the Analytic Hierarchy Process(AHP)method,can suitably satisfy the preference requirements for different flight phases.
基金Project supported by the National Hi-Tech Research and Develop-ment Program (863) of China (No. 2006AA11Z204)the Qianji-ang Program of Zhejiang Province (No. 2009R10008)
文摘For automated vehicles,comfortable driving will improve passengers’ satisfaction.Reducing fuel consumption brings economic profits for car owners,decreases the impact on the environment and increases energy sustainability.In addition to comfort and fuel-economy,automated vehicles also have the basic requirements of safety and car-following.For this purpose,an adaptive cruise control (ACC) algorithm with multi-objectives is proposed based on a model predictive control (MPC) framework.In the proposed ACC algorithm,safety is guaranteed by constraining the inter-distance within a safe range; the requirements of comfort and car-following are considered to be the performance criteria and some optimal reference trajectories are introduced to increase fuel-economy.The performances of the proposed ACC algorithm are simulated and analyzed in five representative traffic scenarios and multiple experiments.The results show that not only are safety and car-following objectives satisfied,but also driving comfort and fuel-economy are improved significantly.
基金Supported by the National Natural Science Foundation of China(No.11172197 and No.11332008)a key-project grant from the Natural Science Foundation of Tianjin(No.010413595)
文摘This paper presents a numerical algorithm tuning aircraft landing gear control system with three objectives,including reducing relative vibration, reducing hydraulic strut force and controlling energy consumption. Sliding mode control is applied to the vibration control of a simplified landing gear model with uncertainty. A two-stage generalized cell mapping algorithm is applied to search the Pareto set with gradient-free scheme. Drop test simulations over uneven runway show that the vibration and force interaction can be considerably reduced, and the Pareto optimum form a tight range in time domain.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
基金Project supported by the National Natural Science Foundation ofChina (No. 60374028) and the Scientific Research Foundation forReturned Overseas Chinese Scholars Ministry of Education (No.[2004]176)
文摘This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2 (GH2) conditions to a set of new linear matrix inequality (LMI) constraints based on a new stability condition. A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables. Consequently, the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.
基金The National Natural Science Foundation of China(No.51576041,51506029)
文摘A model-assistant extended state observer(MESO)-based decoupling control strategy is proposed for boiler-turbine units in the presence of unknown external disturbance and model-plant mismatch. For ease of implementation, the decoupling compensator is reduced to the proportion integration(PI) decoupler with the frequency domain analysis, where the decoupling error in collusion of uncertainties and disturbances can be estimated by the proposed MESO and then compensated. To decrease the sensitivity of the dynamic error for the decoupling control and fulfill various requirements of constraints, such as safety operation, energy conservation, emission reduction, etc., the plant is transmitted through a scheduled steady state region which is achieved from the optimized reference governor in advance. Simulation results show that the proposed control strategy can well suppress various disturbances including a decoupling error, and multi-objective optimization can meet multiple requirements with the premise of safety production.
基金University Malaysia Sabah fully funds this research under the grant number F08/PGRG/1908/2019,Ag.Asri Ag.Ibrahim received the grant,sponsors’websites:https://www.u ms.edu.my.Conflicts of Interest。
文摘CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system efficiency.It has a highly nonlinear characteristic that includes complexities in its control and design.Dynamic performance is compassionate to change in system parameterswhich need more effort for planning a significant controller for CSTR.The reactor temperature changes in either direction from the defined reference value.It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature,and deviation from reference values may cause degradation of biomass quality.Design and implementation of an appropriate adaptive controller for such a nonlinear system are essential.In this paper,a conventional Proportional Integral Derivative(PID)controller is designed.The conventional techniques to deal with constraints suffer severe limitations like it has fixed controller parameters.Hence,A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s limitation.In the proposed technique,PID parameters are tuned by Particle Swarm Optimization(PSO).It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal response.In this article,a multi-objective function is proposed for PSO based controller design of CSTR.
基金the National Key Research and Development Program of China(Basic Research Class)(No.2017YFB0903000)the National Natural Science Foundation of China(No.U1909201).
文摘The output uncertainty of high-proportion distributed power generation severely affects the system voltage and frequency.Simultaneously,controllable loads have also annually increased,which markedly improve the capability for nodal-power control.To maintain the system frequency and voltage magnitude around rated values,a new multi-objective optimization model for both voltage and frequency control is proposed.Moreover,a great similarity between the multiobjective optimization and game problems appears.To reduce the strong subjectivity of the traditional methods,the idea and method of the game theory are introduced into the solution.According to the present situational data and analysis of the voltage and frequency sensitivities to nodal-power variations,the design variables involved in the voltage and frequency control are classified into two strategy spaces for players using hierarchical clustering.Finally,the effectiveness and rationality of the proposed control are verified in MATLAB.
文摘This article studies the existence and uniqueness of the mild solution of a family of control systems with a delay that are governed by the nonlinear fractional evolution differential equations in Banach spaces.Moreover,we establish the controllability of the considered system.To do so,first,we investigate the approximate controllability of the corresponding linear system.Subsequently,we prove the nonlinear system is approximately controllable if the corresponding linear system is approximately controllable.To reach the conclusions,the theory of resolvent operators,the Banach contraction mapping principle,and fixed point theorems are used.While concluding,some examples are given to demonstrate the efficacy of the proposed results.
基金This work was supported by the UK EPSRC (GR/N13319, GR/R10875).
文摘In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.
基金The work was supported by the Science Challenge Project(Grant No.TZ2018007)The authors also thank the National Natural Science Foundation of China(Grant Nos.11872059,11702279)National Defense Technology Foundation of China(Grant No.JSUS2018212C)for providing the financial support for this project.
文摘The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.
基金financially supported by the Fundamental Research Funds for the Central Universities (No.FRF-MP20-08)。
文摘To deal with the increasing demand for low-volume customization of the mechanical properties of cold-rolled products, a two-way control method based on mechanical property prediction and process parameter optimization(PPO) has become an effective solution. Aiming at the multi-objective quality control problem of a company's cold-rolled products, based on industrial production data, we proposed a process parameter design and optimization method that combined multi-objective quality prediction and PPO. This method used the multi-output support vector regression(MSVR) method to simultaneously predict multiple quality indices. The MSVR prediction model was used as the effect verification model of the PPO results. It performed multi-process parameter collaborative design and realized the optimization of production process parameters for customized multi-objective quality requirements. The experimental results showed that, compared with the traditional single-objective quality prediction model based on support vector regression(SVR), the multi-objective prediction model could better take into account the coupling effect between process parameters and quality index, the MSVR model prediction accuracy was higher than that of the SVR, and the optimized process parameters were more capable and reflected the influence of metallurgical mechanism on the quality index,which were more in line with actual production process requirements.
基金Sponsored by the National Natural Science Foundation of China (Grant No. 60504033)
文摘To get the satisfying performance of a PID controller, this paper presents a novel Pareto-based multi-objective genetic algorithm (MOGA), which can be used to find the appropriate setting of the PID controller by analyzing the pareto optimal surfaces. Rated settings of the controller by two criteria, the error between output and reference signals and control moves, are listed on the pareto surface. Appropriate setting can be chosen under a balance between two criteria for different control purposes. A controller tuning problem for a plant with high order and time delay is chosen as an example. Simulation results show that the method of MOGA is more efficient compared with traditional tuning methods.
基金supported by the National Natural Science Foundation of China (Grant No. 61104146/F030203)Innovation Plan of Aero Engine Complex System Safety by the Ministry of Education Chang Jiang Scholars of China (Grant No. IRT0905)
文摘The aircraft engine multi-loop control system is described and the switching control theory is introduced to solve the regulating and protecting control problems in this paper. The aircraft engine multi-loop control system is firstly described and the control problems are formulated. Secondly, the theory of the smooth switching control is devoted and a new extended scheme for the smooth switching of a switched control system is introduced. Then, for the key technologies of aero-engines switching control, a design algorithm is presented which can determine which candidate controller should be put in feedback with the plant to achieve a desired performance and the procedure to design the aircraft engine multi-loop control system is detailed. The switching performance objectives and the switching scheme are given and a family of PID controllers and compensators is designed. The simulation shows that using the switching control design method can not only improve the dynamic performance of the aircraft engine control system and reduce the switching times, but also guarantee the stability in some peculiar occasions.
