The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compe...The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compensator based on functional link neural network is used to deal with the engine nonlinearity and the hardware-in-loop simulation is also developed. The results show that the nonlinear MRAC controller has the adequate performance of compensating and adapting nonlinearity arising from the change of engine state or working environment. Such feature demonstrates potential practical applications of MRAC for aeroengine control system.展开更多
A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the...A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the model reference adaptive control law is designed and an adaptive compensator is used for improving its self-re- pairing capability. To enhance anti-interference capability of helicopter, quantum control feedforward is added be- tween fault and disturbance. Simulation results illustrate the effectiveness and feasibility of the approach.展开更多
A new decentralized adaptive control scheme is presented for linear time invariant systems with first order interconnections. The proposed control scheme with “proportional plus integral” terms is used to improve ...A new decentralized adaptive control scheme is presented for linear time invariant systems with first order interconnections. The proposed control scheme with “proportional plus integral” terms is used to improve the convergence rate and the ultimate bound of the tracking error. It is important to note that the adaptive scheme uses lower adaptive gains and smaller control inputs to avoid input saturation and oscillatory behavior. Simulation results are illustrated for controlling a dual inverted pendulum and a multivariable turbofan engine using the proposed adaptive scheme. These simulations validate out conclusions.展开更多
Aim To present an adaptive missile control system adaped to the external disturbance and the mobility of target movement. Methods Model reference adaptive control (MRAC) was applied and modified in the light of the ...Aim To present an adaptive missile control system adaped to the external disturbance and the mobility of target movement. Methods Model reference adaptive control (MRAC) was applied and modified in the light of the traits of the anti tank missile. Results Simulation results demonstrated this control system satisfied the requirement of anti tank missile of dive overhead attack. Conclusion It is successful to use MRAC in missile control system design, the quality is better than that designed by classical control theory.展开更多
The existing methods for blade polishing mainly focus on robot polishing and manual grinding.Due to the difficulty in high-precision control of the polishing force,the blade surface precision is very low in robot poli...The existing methods for blade polishing mainly focus on robot polishing and manual grinding.Due to the difficulty in high-precision control of the polishing force,the blade surface precision is very low in robot polishing,in particular,quality of the inlet and exhaust edges can not satisfy the processing requirements.Manual grinding has low efficiency,high labor intensity and unstable processing quality,moreover,the polished surface is vulnerable to burn,and the surface precision and integrity are difficult to ensure.In order to further improve the profile accuracy and surface quality,a pneumatic flexible polishing force-exerting mechanism is designed and a dual-mode switching composite adaptive control(DSCAC) strategy is proposed,which combines Bang-Bang control and model reference adaptive control based on fuzzy neural network(MRACFNN) together.By the mode decision-making mechanism,Bang-Bang control is used to track the control command signal quickly when the actual polishing force is far away from the target value,and MRACFNN is utilized in smaller error ranges to improve the system robustness and control precision.Based on the mathematical model of the force-exerting mechanism,simulation analysis is implemented on DSCAC.Simulation results show that the output polishing force can better track the given signal.Finally,the blade polishing experiments are carried out on the designed polishing equipment.Experimental results show that DSCAC can effectively mitigate the influence of gas compressibility,valve dead-time effect,valve nonlinear flow,cylinder friction,measurement noise and other interference on the control precision of polishing force,which has high control precision,strong robustness,strong anti-interference ability and other advantages compared with MRACFNN.The proposed research achieves high-precision control of the polishing force,effectively improves the blade machining precision and surface consistency,and significantly reduces the surface roughness.展开更多
A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performan...A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performance of the system over the fullflight envelope. Simulation results also show the good effectiveness of reducing interactionin the multivariable system with significant coupling. The control system developed has awide frequency band to satisfy the strict engineering requirement and is practical for engineering applications.展开更多
To solve the rapid transient control problem of Flight Environment Simulation System(FESS) of Altitude Ground Test Facilities(AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structur...To solve the rapid transient control problem of Flight Environment Simulation System(FESS) of Altitude Ground Test Facilities(AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structure of modified robust optimal adaptive control is presented.The mathematic modeling of FESS is given and the influence of heat transfer is analyzed through energy view. To consider the influence of heat transfer in controller design, we introduce a matched uncertainty that represents heat transfer influence in the linearized system of FESS. Based on this linear system, we deduce the design of modified robust optimal adaptive control law in a general way. Meanwhile, the robust stability of the modified robust optimal adaptive control law is proved through using Lyapunov stability theory. Then, a typical aero-engine test condition with Mach Dash and Zoom-Climb is used to verify the effectiveness of the devised adaptive controller. The simulation results show that the designed controller has servo tracking and disturbance rejection performance under heat transfer uncertainty and disturbance;the relative steady-state and dynamic errors of pressure and temperature are both smaller than 1% and 0.2% respectively. Furthermore,the influence of the modification parameter c is analyzed through simulation. Finally, comparing with the standard ideal model reference adaptive controller, the modified robust optimal adaptive controller obviously provides better control performance than the ideal model reference adaptive controller does.展开更多
Model reference adaptive control is a viable control method to impose the demanded dynamics on plants whose parameters are affected by large uncertainty. In this paper, we show by means of experiments that robust adap...Model reference adaptive control is a viable control method to impose the demanded dynamics on plants whose parameters are affected by large uncertainty. In this paper, we show by means of experiments that robust adaptive methods can effectively face nonlinearities that are common to many automotive electromechanical devices. We consider here, as a representative case study, the control of a strongly nonlinear automotive actuator. The experimental results confirm the effectiveness of the method to cope with unmodeled nonlinear terms and unknown parameters. In addition, the engineering performance indexes computed on experimental data clearly show that the robust adaptive strategy provides better performance compared with those given by a classical model-based control solution with fixed gains.展开更多
A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) frame-work is proposed to account for plant model errors caused by slow aging,drift in operational conditions,...A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) frame-work is proposed to account for plant model errors caused by slow aging,drift in operational conditions,or environmental changes.Since PLS decomposition structure enables multi-loop controller design within latent spaces,a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space.In each latent subspace,once the model error exceeds a specific threshold,online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm.Because the IMC extracts the inverse of the minimum part of the internal model as its structure,the IMC controller is self-tuned by explicitly updating the parameters,which are parts of the internal model.Both parameter convergence and system stability are briefly analyzed,and proved to be effective.Finally,the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay.展开更多
In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight tech...In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.展开更多
Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo...Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo system. The controller design requires no information about the structure of linear servo system, and it is based on the estimation and forecasting of the pseudo-partial derivatives(PPD) which are estimated according to the voltage input and position output of the linear motor. The characteristics and operational mechanism of the permanent magnet synchronous linear motor(PMSLM) are introduced, and the proposed nonparametric model control strategy has been compared with the classic proportional-integral-derivative(PID) control algorithm. Several real-time experiments on the motion control system incorporating a permanent magnet synchronous linear motor showed that the nonparametric model adaptive control method improved the system s response to disturbances and its position-tracking precision, even for a nonlinear system with incompletely known dynamic characteristics.展开更多
This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot...This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.展开更多
For a class of discrete-time systems with unmodeled dynamics and bounded disturbance, the design and analysis of robust indirect model reference adaptive control （MRAC） with normalized adaptive law are investigated....For a class of discrete-time systems with unmodeled dynamics and bounded disturbance, the design and analysis of robust indirect model reference adaptive control （MRAC） with normalized adaptive law are investigated. The main work includes three parts. Firstly, it is shown that the constructed parameter estimation algorithm not only possesses the same properties as those of traditional estimation algorithms, but also avoids the possibility of division by zero. Secondly, by establishing a relationship between the plant parameter estimate and the controller parameter estimate, some similar properties of the latter are also established. Thirdly, by using the relationship between the normalizing signal and all the signals of the closed-loop system, and some important mathematical tools on discrete-time systems, as in the continuous-time case, a systematic stability and robustness analysis approach to the discrete indirect robust MRAC scheme is developed rigorously.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
An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy ...An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.展开更多
The minimal controller synthesis （MCS） is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the p...The minimal controller synthesis （MCS） is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the presence of plant parameter variations, external disturbances, dynamic coupling within the plant and plant nonlinearities. The minimal controller synthesis algorithm was successfully applied to the problem of decentralized adaptive schemes. The decentralized minimal controller synthesis adaptive control strategy for controlling the attitude of a rigid body satellite is adopted in this paper. A model reference adaptive control strategy which uses one single three-axis slew is proposed for the purpose of controlling the attitude of a rigid body satellite. The simulation results are excellent and show that the controlled system is robust against disturbances.展开更多
Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model referen...Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.展开更多
Motivated by the autopilot of an unmanned aerial vehicle（UAV） with a wide flight envelope span experiencing large parametric variations in the presence of uncertainties, a fuzzy adaptive tracking controller（FATC） ...Motivated by the autopilot of an unmanned aerial vehicle（UAV） with a wide flight envelope span experiencing large parametric variations in the presence of uncertainties, a fuzzy adaptive tracking controller（FATC） is proposed. The controller consists of a fuzzy baseline controller and an adaptive increment, and the main highlight is that the fuzzy baseline controller and adaptation laws are both based on the fuzzy multiple Lyapunov function approach, which helps to reduce the conservatism for the large envelope and guarantees satisfactory tracking performances with strong robustness simultaneously within the whole envelope. The constraint condition of the fuzzy baseline controller is provided in the form of linear matrix inequality（LMI）, and it specifies the satisfactory tracking performances in the absence of uncertainties. The adaptive increment ensures the uniformly ultimately bounded（UUB） predication errors to recover satisfactory responses in the presence of uncertainties. Simulation results show that the proposed controller helps to achieve high-accuracy tracking of airspeed and altitude desirable commands with strong robustness to uncertainties throughout the entire flight envelope.展开更多
In this paper,a new model free adaptive control method based on self-adjusting PID algorithm(MFACSA-PID)is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the ne...In this paper,a new model free adaptive control method based on self-adjusting PID algorithm(MFACSA-PID)is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the neutralization point.The MFAC-SA-PID method also solves the problem that the parameters of the model free adaptive control(MFAC)method are not easy to be adjusted and the effect is not obvious by introducing a fuzzy self-adjusting algorithm to adjust the controller parameters.Then the convergence and stability of the MFAC-SA-PID method are proved in this paper.In the simulation study,the control performance of the MFAC-SA-PID method proposed in this paper is compared with the traditional MFAC method and the improved model free adaptive control(IMFAC)method,respectively.The results show that the proposed MFAC-SA-PID method has better control effect on the pH neutralization process.The MFAC-SA-PID control performance also outperforms the traditional MFAC method and IMFAC method when step input disturbances are added,which indicates that the MFAC-SA-PID method has better robustness and stability.展开更多
Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccu...Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccurate driver operations,and mismatched model errors.Furthermore,misleading sensing information or malicious attacks in vehicular wireless networks can jeopardize CAVs’perception and platoon safety.In this paper,we develop a two-dimensional robust control method for a mixed platoon,including a single leading CAV and multiple following HDVs that incorpo-rate robust information sensing and platoon control.To effectively detect and locate unknown obstacles ahead of the leading CAV,we propose a cooperative vehicle-infrastructure sensing scheme and integrate it with an adaptive model predictive control scheme for the leading CAV.This sensing scheme fuses information from multiple nodes while suppressing malicious data from attackers to enhance robustness and attack resilience in a distributed and adaptive manner.Additionally,we propose a distributed car-following control scheme with robustness to guarantee the following HDVs,considering uncertain disturbances.We also provide theoretical proof of the string stability under this control framework.Finally,extensive simulations are conducted to validate our approach.The simulation results demonstrate that our method can effectively filter out misleading sensing information from malicious attackers,significantly reduce the mean-square deviation in obstacle sensing,and approach the theoretical error lower bound.Moreover,the proposed control method successfully achieves obstacle avoidance for the mixed platoon while ensuring stability and robustness in the face of external attacks and uncertain disturbances.展开更多
文摘The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compensator based on functional link neural network is used to deal with the engine nonlinearity and the hardware-in-loop simulation is also developed. The results show that the nonlinear MRAC controller has the adequate performance of compensating and adapting nonlinearity arising from the change of engine state or working environment. Such feature demonstrates potential practical applications of MRAC for aeroengine control system.
基金Supported by the National Natural Science Foundation of China(61074080)the Innovation Foundation for Aeronautical Science and Technology(08C52001)~~
文摘A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the model reference adaptive control law is designed and an adaptive compensator is used for improving its self-re- pairing capability. To enhance anti-interference capability of helicopter, quantum control feedforward is added be- tween fault and disturbance. Simulation results illustrate the effectiveness and feasibility of the approach.
文摘A new decentralized adaptive control scheme is presented for linear time invariant systems with first order interconnections. The proposed control scheme with “proportional plus integral” terms is used to improve the convergence rate and the ultimate bound of the tracking error. It is important to note that the adaptive scheme uses lower adaptive gains and smaller control inputs to avoid input saturation and oscillatory behavior. Simulation results are illustrated for controlling a dual inverted pendulum and a multivariable turbofan engine using the proposed adaptive scheme. These simulations validate out conclusions.
文摘Aim To present an adaptive missile control system adaped to the external disturbance and the mobility of target movement. Methods Model reference adaptive control (MRAC) was applied and modified in the light of the traits of the anti tank missile. Results Simulation results demonstrated this control system satisfied the requirement of anti tank missile of dive overhead attack. Conclusion It is successful to use MRAC in missile control system design, the quality is better than that designed by classical control theory.
基金supported by National Natural Science Foundation of China(Grant No.51005184)National Science and Technology Major Project of Ministry of Science and Technology of China(Grant No.2009ZX04014-053)
文摘The existing methods for blade polishing mainly focus on robot polishing and manual grinding.Due to the difficulty in high-precision control of the polishing force,the blade surface precision is very low in robot polishing,in particular,quality of the inlet and exhaust edges can not satisfy the processing requirements.Manual grinding has low efficiency,high labor intensity and unstable processing quality,moreover,the polished surface is vulnerable to burn,and the surface precision and integrity are difficult to ensure.In order to further improve the profile accuracy and surface quality,a pneumatic flexible polishing force-exerting mechanism is designed and a dual-mode switching composite adaptive control(DSCAC) strategy is proposed,which combines Bang-Bang control and model reference adaptive control based on fuzzy neural network(MRACFNN) together.By the mode decision-making mechanism,Bang-Bang control is used to track the control command signal quickly when the actual polishing force is far away from the target value,and MRACFNN is utilized in smaller error ranges to improve the system robustness and control precision.Based on the mathematical model of the force-exerting mechanism,simulation analysis is implemented on DSCAC.Simulation results show that the output polishing force can better track the given signal.Finally,the blade polishing experiments are carried out on the designed polishing equipment.Experimental results show that DSCAC can effectively mitigate the influence of gas compressibility,valve dead-time effect,valve nonlinear flow,cylinder friction,measurement noise and other interference on the control precision of polishing force,which has high control precision,strong robustness,strong anti-interference ability and other advantages compared with MRACFNN.The proposed research achieves high-precision control of the polishing force,effectively improves the blade machining precision and surface consistency,and significantly reduces the surface roughness.
文摘A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan engine.Simulation studies show good static and dynamic performance of the system over the fullflight envelope. Simulation results also show the good effectiveness of reducing interactionin the multivariable system with significant coupling. The control system developed has awide frequency band to satisfy the strict engineering requirement and is practical for engineering applications.
基金funded by China Scholarship Council (CSC)and National Science and Technology Major Project,China(No. 2017-V-0015-0067)。
文摘To solve the rapid transient control problem of Flight Environment Simulation System(FESS) of Altitude Ground Test Facilities(AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structure of modified robust optimal adaptive control is presented.The mathematic modeling of FESS is given and the influence of heat transfer is analyzed through energy view. To consider the influence of heat transfer in controller design, we introduce a matched uncertainty that represents heat transfer influence in the linearized system of FESS. Based on this linear system, we deduce the design of modified robust optimal adaptive control law in a general way. Meanwhile, the robust stability of the modified robust optimal adaptive control law is proved through using Lyapunov stability theory. Then, a typical aero-engine test condition with Mach Dash and Zoom-Climb is used to verify the effectiveness of the devised adaptive controller. The simulation results show that the designed controller has servo tracking and disturbance rejection performance under heat transfer uncertainty and disturbance;the relative steady-state and dynamic errors of pressure and temperature are both smaller than 1% and 0.2% respectively. Furthermore,the influence of the modification parameter c is analyzed through simulation. Finally, comparing with the standard ideal model reference adaptive controller, the modified robust optimal adaptive controller obviously provides better control performance than the ideal model reference adaptive controller does.
文摘Model reference adaptive control is a viable control method to impose the demanded dynamics on plants whose parameters are affected by large uncertainty. In this paper, we show by means of experiments that robust adaptive methods can effectively face nonlinearities that are common to many automotive electromechanical devices. We consider here, as a representative case study, the control of a strongly nonlinear automotive actuator. The experimental results confirm the effectiveness of the method to cope with unmodeled nonlinear terms and unknown parameters. In addition, the engineering performance indexes computed on experimental data clearly show that the robust adaptive strategy provides better performance compared with those given by a classical model-based control solution with fixed gains.
基金Project supported by the National Natural Science Foundation of China (No.60574047)the National High-Tech R & D Program (863)of China (No.2007AA04Z168)the Research Fund for the Doctoral Program of Higher Education of China (No.20050335018)
文摘A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) frame-work is proposed to account for plant model errors caused by slow aging,drift in operational conditions,or environmental changes.Since PLS decomposition structure enables multi-loop controller design within latent spaces,a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space.In each latent subspace,once the model error exceeds a specific threshold,online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm.Because the IMC extracts the inverse of the minimum part of the internal model as its structure,the IMC controller is self-tuned by explicitly updating the parameters,which are parts of the internal model.Both parameter convergence and system stability are briefly analyzed,and proved to be effective.Finally,the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay.
基金supported by the Foundation of Shanghai Aerospace Science and Technology(SAST2016077)。
文摘In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.
基金supported by Beijing Natural Science Foundation(No.4142017)International Cooperation Project of National Natural Science Foundation of China(No.61120106009)Beijing Science and Technology Commission Precision Machinery Projects(No.Z121100001612007)
文摘Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo system. The controller design requires no information about the structure of linear servo system, and it is based on the estimation and forecasting of the pseudo-partial derivatives(PPD) which are estimated according to the voltage input and position output of the linear motor. The characteristics and operational mechanism of the permanent magnet synchronous linear motor(PMSLM) are introduced, and the proposed nonparametric model control strategy has been compared with the classic proportional-integral-derivative(PID) control algorithm. Several real-time experiments on the motion control system incorporating a permanent magnet synchronous linear motor showed that the nonparametric model adaptive control method improved the system s response to disturbances and its position-tracking precision, even for a nonlinear system with incompletely known dynamic characteristics.
基金The work was supported by the National Science Foundation，the Office of Naval Research grant，the AFOSR (Air Force Office of Scientific Research) EOARD (European Office of Aerospace Research and Development) grant，the U.S. Army Research Office grant
文摘This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.
基金supported by National Natural Science Foundation of China (No. 60774010, 10971256, 60974028)Natural Science Foundation of Jiangsu Province (No. BK2009083)+2 种基金Program for Fundamental Research of Natural Sciences in Universities of Jiangsu Province(No. 07KJB510114)Shandong Provincial Natural Science Foundation of China (No. ZR2009GM008)Natural Science Foundation of Jining University (No. 2009KJLX02)
文摘For a class of discrete-time systems with unmodeled dynamics and bounded disturbance, the design and analysis of robust indirect model reference adaptive control （MRAC） with normalized adaptive law are investigated. The main work includes three parts. Firstly, it is shown that the constructed parameter estimation algorithm not only possesses the same properties as those of traditional estimation algorithms, but also avoids the possibility of division by zero. Secondly, by establishing a relationship between the plant parameter estimate and the controller parameter estimate, some similar properties of the latter are also established. Thirdly, by using the relationship between the normalizing signal and all the signals of the closed-loop system, and some important mathematical tools on discrete-time systems, as in the continuous-time case, a systematic stability and robustness analysis approach to the discrete indirect robust MRAC scheme is developed rigorously.
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(61333010,21376077,61203157)the Natural Science Foundation of Shanghai(14ZR1421800)State Key Laboratory of Synthetical Automation for Process Industries(PAL-N201404)
文摘An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.
基金This work was supported by Deanship of Research and Graduate Studies at Applied Science University, Amman, Jordan
文摘The minimal controller synthesis （MCS） is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the presence of plant parameter variations, external disturbances, dynamic coupling within the plant and plant nonlinearities. The minimal controller synthesis algorithm was successfully applied to the problem of decentralized adaptive schemes. The decentralized minimal controller synthesis adaptive control strategy for controlling the attitude of a rigid body satellite is adopted in this paper. A model reference adaptive control strategy which uses one single three-axis slew is proposed for the purpose of controlling the attitude of a rigid body satellite. The simulation results are excellent and show that the controlled system is robust against disturbances.
文摘Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.
文摘Motivated by the autopilot of an unmanned aerial vehicle（UAV） with a wide flight envelope span experiencing large parametric variations in the presence of uncertainties, a fuzzy adaptive tracking controller（FATC） is proposed. The controller consists of a fuzzy baseline controller and an adaptive increment, and the main highlight is that the fuzzy baseline controller and adaptation laws are both based on the fuzzy multiple Lyapunov function approach, which helps to reduce the conservatism for the large envelope and guarantees satisfactory tracking performances with strong robustness simultaneously within the whole envelope. The constraint condition of the fuzzy baseline controller is provided in the form of linear matrix inequality（LMI）, and it specifies the satisfactory tracking performances in the absence of uncertainties. The adaptive increment ensures the uniformly ultimately bounded（UUB） predication errors to recover satisfactory responses in the presence of uncertainties. Simulation results show that the proposed controller helps to achieve high-accuracy tracking of airspeed and altitude desirable commands with strong robustness to uncertainties throughout the entire flight envelope.
基金supported by the National Natural Science Foundation of China(61771034).
文摘In this paper,a new model free adaptive control method based on self-adjusting PID algorithm(MFACSA-PID)is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the neutralization point.The MFAC-SA-PID method also solves the problem that the parameters of the model free adaptive control(MFAC)method are not easy to be adjusted and the effect is not obvious by introducing a fuzzy self-adjusting algorithm to adjust the controller parameters.Then the convergence and stability of the MFAC-SA-PID method are proved in this paper.In the simulation study,the control performance of the MFAC-SA-PID method proposed in this paper is compared with the traditional MFAC method and the improved model free adaptive control(IMFAC)method,respectively.The results show that the proposed MFAC-SA-PID method has better control effect on the pH neutralization process.The MFAC-SA-PID control performance also outperforms the traditional MFAC method and IMFAC method when step input disturbances are added,which indicates that the MFAC-SA-PID method has better robustness and stability.
基金supported by the National Key Research and the Development Program of China(2022YFC3803700)the National Natural Science Foundation of China(52202391 and U20A20155).
文摘Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccurate driver operations,and mismatched model errors.Furthermore,misleading sensing information or malicious attacks in vehicular wireless networks can jeopardize CAVs’perception and platoon safety.In this paper,we develop a two-dimensional robust control method for a mixed platoon,including a single leading CAV and multiple following HDVs that incorpo-rate robust information sensing and platoon control.To effectively detect and locate unknown obstacles ahead of the leading CAV,we propose a cooperative vehicle-infrastructure sensing scheme and integrate it with an adaptive model predictive control scheme for the leading CAV.This sensing scheme fuses information from multiple nodes while suppressing malicious data from attackers to enhance robustness and attack resilience in a distributed and adaptive manner.Additionally,we propose a distributed car-following control scheme with robustness to guarantee the following HDVs,considering uncertain disturbances.We also provide theoretical proof of the string stability under this control framework.Finally,extensive simulations are conducted to validate our approach.The simulation results demonstrate that our method can effectively filter out misleading sensing information from malicious attackers,significantly reduce the mean-square deviation in obstacle sensing,and approach the theoretical error lower bound.Moreover,the proposed control method successfully achieves obstacle avoidance for the mixed platoon while ensuring stability and robustness in the face of external attacks and uncertain disturbances.
