The mechanical system with backlash is distinguished between a"backlash mode"and a"contact mode".The inherent switching between the two operating modes makes the system a prime example of hybrid system.For elimina...The mechanical system with backlash is distinguished between a"backlash mode"and a"contact mode".The inherent switching between the two operating modes makes the system a prime example of hybrid system.For eliminating the bad effect of backlash, a piecewise affine(PWA) model of the mechanical servo system with backlash is built.The optimal control of constrained PWA system is obtained by taking advantage of model predictive control(MPC) method, and the explicit solution of MPC in a look-up table form is figured out by combining the dynamic programming and multi-parametric quadratic programming, thereby establishing an explicit hybrid model predictive controller.Furthermore, a piecewise quadratic(PWQ) function for guaranteeing the stability of closed-loop control is found by formulating the search of PWQ function as a semi-definite programming problem.In the tracking experiments, it is demonstrated that the explicit hybrid model predictive controller has a good traction control effect on the mechanical system with backlash.The error meets the demands of real system.Further, compared to the direct on-line computation, the computation burden is reduced by the explicit solution, thereby being suitable for real-time control of system with short sampling time.展开更多
The control problems associated with vehicle height adjustment of electronically controlled air suspension (ECAS) still pose theoretical challenges for researchers, which manifest themselves in the publications on t...The control problems associated with vehicle height adjustment of electronically controlled air suspension (ECAS) still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical (MLD) modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller (HMPC) is tuned based on online mixed-integer quadratic optimization (MIQP). Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology (MPT), thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.展开更多
A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and ...A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and the RH operational guide parameters for different steel grades according to the initial conditions of molten steel,and a three-layer BP neural network was adopted to deal with nonlinear factors for improving and compensating the limitations of technological model for RH process control and end-point prediction.It was verified that the hybrid neural network is effective for improving the precision and calculation efficiency of the model.展开更多
The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memor...The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.展开更多
A hybrid dynamic model was proposed, which considered both the hydrokinetic and the chaotic properties of the blast furnace ironmaking process; and great emphasis was put on its mechanism. The new model took the high ...A hybrid dynamic model was proposed, which considered both the hydrokinetic and the chaotic properties of the blast furnace ironmaking process; and great emphasis was put on its mechanism. The new model took the high complexity of the blast furnace as well as the effects of main parameters of the model into account, and the predicted results were in very good agreement with actual data.展开更多
In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm(HHA), which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from mo...In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm(HHA), which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network(NN)-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function(RBF) NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.展开更多
To resolve the problem of quantitative analysis in hybrid cloud,a quantitative analysis method,which is based on the security entropy,is proposed.Firstly,according to the information theory,the security entropy is put...To resolve the problem of quantitative analysis in hybrid cloud,a quantitative analysis method,which is based on the security entropy,is proposed.Firstly,according to the information theory,the security entropy is put forward to calculate the uncertainty of the system' s determinations on the irregular access behaviors.Secondly,based on the security entropy,security theorems of hybrid cloud are defined.Finally,typical access control models are analyzed by the method,the method's practicability is validated,and security and applicability of these models are compared.Simulation results prove that the proposed method is suitable for the security quantitative analysis of the access control model and evaluation to access control capability in hybrid cloud.展开更多
In this paper, a linear programming method is proposed to solve model predictive control for a class of hybrid systems. Firstly, using the (max, +) algebra, a typical subclass of hybrid systems called max-plus-line...In this paper, a linear programming method is proposed to solve model predictive control for a class of hybrid systems. Firstly, using the (max, +) algebra, a typical subclass of hybrid systems called max-plus-linear (MPL) systems is obtained. And then, model predictive control (MPC) framework is extended to MPL systems. In general, the nonlinear optimization approach or extended linear complementarity problem (ELCP) were applied to solve the MPL-MPC optimization problem. A new optimization method based on canonical forms for max-min-plus-scaling (MMPS) functions (using the operations maximization, minimization, addition and scalar multiplication) with linear constraints on the inputs is presented. The proposed approach consists in solving several linear programming problems and is more efficient than nonlinear optimization. The validity of the algorithm is illustrated by an example.展开更多
In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts ...In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.展开更多
In this paper, a new hybrid control technique, based on a combination of base-isolation and semi-active variable stiffness/damping in a superstructure, is presented. To illustrate the efficiency of the proposed contro...In this paper, a new hybrid control technique, based on a combination of base-isolation and semi-active variable stiffness/damping in a superstructure, is presented. To illustrate the efficiency of the proposed control system, model tests on a mini-electromagnetic shaking table and a numerical simulation were performed. The test and numerical calculation results indicate that this new hybrid control mode with additional damping and smaller additional stiffness can achieve a better control efficiency.展开更多
This paper presents a novel adaptive scheme for energy management in stand-alone hybrid power systems. The proposed management system is designed to manage the power flow between the hybrid power system and energy sto...This paper presents a novel adaptive scheme for energy management in stand-alone hybrid power systems. The proposed management system is designed to manage the power flow between the hybrid power system and energy storage elements in order to satisfy the load requirements based on artificial neural network (ANN) and fuzzy logic controllers. The neural network controller is employed to achieve the maximum power point (MPP) for different types of photovoltaic (PV) panels. The advance fuzzy logic controller is developed to distribute the power among the hybrid system and to manage the charge and discharge current flow for performance optimization. The developed management system performance was assessed using a hybrid system comprised PV panels, wind turbine (WT), battery storage, and proton exchange membrane fuel cell (PEMFC). To improve the generating performance of the PEMFC and prolong its life, stack temperature is controlled by a fuzzy logic controller. The dynamic behavior of the proposed model is examined under different operating conditions. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for optimizing hybrid power system performance, such as that used in smart-house applications.展开更多
The control strategy is presented using passive and active hybrid magnetically suspended flywheels(P&A MSFWs),which can help meet the requirements of high precision and high stability for earth-observation satellit...The control strategy is presented using passive and active hybrid magnetically suspended flywheels(P&A MSFWs),which can help meet the requirements of high precision and high stability for earth-observation satellites.Compared with the conventional flywheel,P&A MSFW has more rotation degrees of freedom(DOFs)since the rotor is suspended by magnetic bearings,and thus requires more efficient controllers.A modified sliding mode control law(SMC)to our novel nonlinear and coupled system is presented,which is interrupted by inertia matrix uncertainties and external disturbances.SMC law via Lyapunov method is improved,and a fuzzy control scheme is used to attenuate the chatting and control attitude accuracy and maintain the robustness of SMC.Simulation results are provided to illustrate the efficiency of our model by using our control law.展开更多
基金supported by the Beijing Education Committee Cooperation Building Foundation Project (XK100070532)
文摘The mechanical system with backlash is distinguished between a"backlash mode"and a"contact mode".The inherent switching between the two operating modes makes the system a prime example of hybrid system.For eliminating the bad effect of backlash, a piecewise affine(PWA) model of the mechanical servo system with backlash is built.The optimal control of constrained PWA system is obtained by taking advantage of model predictive control(MPC) method, and the explicit solution of MPC in a look-up table form is figured out by combining the dynamic programming and multi-parametric quadratic programming, thereby establishing an explicit hybrid model predictive controller.Furthermore, a piecewise quadratic(PWQ) function for guaranteeing the stability of closed-loop control is found by formulating the search of PWQ function as a semi-definite programming problem.In the tracking experiments, it is demonstrated that the explicit hybrid model predictive controller has a good traction control effect on the mechanical system with backlash.The error meets the demands of real system.Further, compared to the direct on-line computation, the computation burden is reduced by the explicit solution, thereby being suitable for real-time control of system with short sampling time.
基金Supported by National Natural Science Foundation of China(Grant No.51375212)Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions of China+1 种基金Research Fund for the Doctoral Program of Higher Education of China(Grant No.20133227130001)China Postdoctoral Science Foundation(Grant No.2014M551518)
文摘The control problems associated with vehicle height adjustment of electronically controlled air suspension (ECAS) still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical (MLD) modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller (HMPC) is tuned based on online mixed-integer quadratic optimization (MIQP). Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology (MPT), thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.
基金Item Sponsored by National Natural Science Foundation of China(50074026)
文摘A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and the RH operational guide parameters for different steel grades according to the initial conditions of molten steel,and a three-layer BP neural network was adopted to deal with nonlinear factors for improving and compensating the limitations of technological model for RH process control and end-point prediction.It was verified that the hybrid neural network is effective for improving the precision and calculation efficiency of the model.
基金Project(51105170) supported by the National Natural Science Foundation of ChinaProject supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Education,China
文摘The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.
基金Item Sponsored by National Basic Research Programof China (2005EC000166) Ningbo Natural Science Foundation ofChina (2006A610032)
文摘A hybrid dynamic model was proposed, which considered both the hydrokinetic and the chaotic properties of the blast furnace ironmaking process; and great emphasis was put on its mechanism. The new model took the high complexity of the blast furnace as well as the effects of main parameters of the model into account, and the predicted results were in very good agreement with actual data.
基金supported by National Basic Research and Development Program of China (973 Program, Grant No. 2006CB705402)
文摘In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm(HHA), which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network(NN)-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function(RBF) NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.
基金Supported by the National Natural Science Foundation of China(No.60872041,61072066)Fundamental Research Funds for the Central Universities(JYI0000903001,JYI0000901034)
文摘To resolve the problem of quantitative analysis in hybrid cloud,a quantitative analysis method,which is based on the security entropy,is proposed.Firstly,according to the information theory,the security entropy is put forward to calculate the uncertainty of the system' s determinations on the irregular access behaviors.Secondly,based on the security entropy,security theorems of hybrid cloud are defined.Finally,typical access control models are analyzed by the method,the method's practicability is validated,and security and applicability of these models are compared.Simulation results prove that the proposed method is suitable for the security quantitative analysis of the access control model and evaluation to access control capability in hybrid cloud.
基金This work was supported by the National Science Foundation of China (No. 60474051)the program for New Century Excellent Talents in University of China (NCET).
文摘In this paper, a linear programming method is proposed to solve model predictive control for a class of hybrid systems. Firstly, using the (max, +) algebra, a typical subclass of hybrid systems called max-plus-linear (MPL) systems is obtained. And then, model predictive control (MPC) framework is extended to MPL systems. In general, the nonlinear optimization approach or extended linear complementarity problem (ELCP) were applied to solve the MPL-MPC optimization problem. A new optimization method based on canonical forms for max-min-plus-scaling (MMPS) functions (using the operations maximization, minimization, addition and scalar multiplication) with linear constraints on the inputs is presented. The proposed approach consists in solving several linear programming problems and is more efficient than nonlinear optimization. The validity of the algorithm is illustrated by an example.
基金Project(61175128) supported by the National Natural Science Foundation of ChinaProject(2008AA040203) supported by the National High Technology Research and Development Program of ChinaProject(QC2010009) supported by the Natural Science Foundation of Heilongjiang Province,China
文摘In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.
基金Societal Commonweal Fund Project (2001DIB20098) Earthquake Science Associate Fund (603011)
文摘In this paper, a new hybrid control technique, based on a combination of base-isolation and semi-active variable stiffness/damping in a superstructure, is presented. To illustrate the efficiency of the proposed control system, model tests on a mini-electromagnetic shaking table and a numerical simulation were performed. The test and numerical calculation results indicate that this new hybrid control mode with additional damping and smaller additional stiffness can achieve a better control efficiency.
文摘This paper presents a novel adaptive scheme for energy management in stand-alone hybrid power systems. The proposed management system is designed to manage the power flow between the hybrid power system and energy storage elements in order to satisfy the load requirements based on artificial neural network (ANN) and fuzzy logic controllers. The neural network controller is employed to achieve the maximum power point (MPP) for different types of photovoltaic (PV) panels. The advance fuzzy logic controller is developed to distribute the power among the hybrid system and to manage the charge and discharge current flow for performance optimization. The developed management system performance was assessed using a hybrid system comprised PV panels, wind turbine (WT), battery storage, and proton exchange membrane fuel cell (PEMFC). To improve the generating performance of the PEMFC and prolong its life, stack temperature is controlled by a fuzzy logic controller. The dynamic behavior of the proposed model is examined under different operating conditions. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for optimizing hybrid power system performance, such as that used in smart-house applications.
文摘The control strategy is presented using passive and active hybrid magnetically suspended flywheels(P&A MSFWs),which can help meet the requirements of high precision and high stability for earth-observation satellites.Compared with the conventional flywheel,P&A MSFW has more rotation degrees of freedom(DOFs)since the rotor is suspended by magnetic bearings,and thus requires more efficient controllers.A modified sliding mode control law(SMC)to our novel nonlinear and coupled system is presented,which is interrupted by inertia matrix uncertainties and external disturbances.SMC law via Lyapunov method is improved,and a fuzzy control scheme is used to attenuate the chatting and control attitude accuracy and maintain the robustness of SMC.Simulation results are provided to illustrate the efficiency of our model by using our control law.