Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output （MIMO） random vibration test. During the control process with the difference control algorithm （DCA）, a lower tri...Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output （MIMO） random vibration test. During the control process with the difference control algorithm （DCA）, a lower triangular matrix is derived from Cholesky decomposition of a reference spectrum matrix. The diagonal elements of the lower triangular matrix （DELTM） may become negative. These negative values have no meaning in physical significance and can cause divergence of auto-power spectrum control. A proportional root mean square control algorithm （PRMSCA） provides another method to avoid the divergence caused by negative values of DELTM, but PRMSCA cannot control the cross-power spectrum. A new control algorithm named matrix power control algorithm （MPCA） is proposed in the paper. MPCA can guarantee that DELTM is always positive in the auto-power spectrum control. MPCA can also control the cross-power spectrum. After these three control algorithms are analyzed, three-input three-output random vibration control tests are implemented on a three-axis vibration shaker. The results show the validity of the proposed MPCA.展开更多
A control method for Multi-Input Multi-Output（MIMO） non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified ...A control method for Multi-Input Multi-Output（MIMO） non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified references composed of auto spectral densities, cross spectral densities and kurtoses on the test article in the laboratory. It is found that the cross spectral densities will bring intractable coupling problems and induce difficulty for the control of the multioutput kurtoses. Hence, a sequential phase modification method is put forward to solve the coupling problems in multi-input multi-output non-Gaussian random vibration test. To achieve the specified responses, an improved zero memory nonlinear transformation is utilized first to modify the Fourier phases of the signals with sequential phase modification method to obtain one frame reference response signals which satisfy the reference spectra and reference kurtoses. Then, an inverse system method is used in frequency domain to obtain the continuous stationary drive signals. At the same time, the matrix power control algorithm is utilized to control the spectra and kurtoses of the response signals further. At the end of the paper, a simulation example with a cantilever beam and a vibration shaker test are implemented and the results support the proposed method very well.展开更多
Noises always disturb the control effect of an environment test especially in multi-input multi-output(MIMO) systems. If the frequency response function matrices are ill-conditioned, the noises in the driving forces w...Noises always disturb the control effect of an environment test especially in multi-input multi-output(MIMO) systems. If the frequency response function matrices are ill-conditioned, the noises in the driving forces will be amplified and the response spectral lines may awfully exceed their tolerances. Most of the major biases between the response spectra and the reference spectra are produced by the amplified noises. However, ordinary control algorithms can hardly reduce the level of noises. The influences of the noises on both the auto- and cross-power spectra are analyzed in this paper. As a conventional frequency domain method on the inverse problem, the Tikhonov filter is adopted in the environment test to suppress the exceeding spectral lines. By altering regularization parameters gradually, the auto-power spectra can be improved in a closed control loop. Instead of using the traditional way of selecting regularization parameters, we observe the coherence change to estimate noise eliminations. Incidentally, the requirement of coherence control can be realized. The errors of the phase are then studied and a phase control algorithm is introduced at the end as a supplement of cross-power spectra control. The Tikhonov filter and the proposed phase control algorithm are tested numerically and experimentally. The results show that the noises in the vicinity of lightly damped resonant peaks are more stubborn. The response spectra are able to be greatly improved by the combination of these two methods.展开更多
A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a su...A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a supervision module for the local controller, ILC can improve the tracking performance of the closed-loop system along the batch direction. In this study, an ILC-based P-type controller is proposed for multi-input multi-output (MIMO) linear batch processes, where a P-type controller is used to design the control signal directly and an ILC module is used to update the set-point for the P-type controller. Under the proposed ILC-based P-type controller, the closed-loop system can be transformed to a 2-dimensional (2D) Roesser s system. Based on the 2D system framework, a sufficient condition for asymptotic stability of the closed-loop system is derived in this paper. In terms of the average tracking error (ATE), the closed-loop control performance under the proposed algorithm can be improved from batch to batch, even though there are repetitive disturbances. A numerical example is used to validate the proposed results.展开更多
In this study, a novel approach for dynamic modeling and closed-loop control of hybrid grid-connected renewable energy system with multi-input multi-output(MIMO) controller is proposed. The studied converter includes ...In this study, a novel approach for dynamic modeling and closed-loop control of hybrid grid-connected renewable energy system with multi-input multi-output(MIMO) controller is proposed. The studied converter includes two parallel DC-DC boost converters, which are connected into the power grid through a single-phase H-bridge inverter. The proposed MIMO controller is developed for maximum power point tracking of photovoltaic(PV)/fuel-cell(FC) input power sources and output power control of the grid-connected DC-AC inverter. Considering circuit topology of the system, a unique MIMO model is proposed for the analysis of the entire system. A unique model of the system includes all of the circuit state variables in DCDC and DC-AC converters. In fact, from the viewpoint of closed-loop controller design, the hybrid grid-connected energy system is an MIMO system. The control inputs of the system are duty cycles of the DC-DC boost converters and the amplitude modulation index of DC-AC inverters. Furthermore, the control outputs are the output power of the PV/FC input power sources as well as AC power injected into the power grid. After the development of the unique model for the entire system, a decoupling network is introduced for system input-output linearization due to inherent connection of the control outputs with all of the system inputs. Considering the decoupled model and small signal linearization, the required linear controllers are designed to adjust the outputs. Finally, to evaluate the accuracy and effectiveness of the designed controllers, the PV/FC based grid-connected system is simulated using the MATLAB/Simulink toolbox.展开更多
This paper presents the design of decentralized repetitive control （RC） for multi-input multi-output （MIMO） systems. An optimization method is used to obtain a RC compensator that ensures system stability and good...This paper presents the design of decentralized repetitive control （RC） for multi-input multi-output （MIMO） systems. An optimization method is used to obtain a RC compensator that ensures system stability and good tracking performance. The designed compensator is in the form of a stable, low order, and causal filter, in which the compensator can be implemented separately without being merged with the RC internal model. This will reduce complexity in the implementation. Simulation results and comparison study are given to demonstrate the effectiveness of the proposed design. The novelty of design is also verified in experiments on a 2 degrees of freedom （DOF） robot.展开更多
The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises i...The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF. The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation. The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF （degree-of-freedom） hydraulic vibration table. The result shows that it is favorable to improve the control precision of the MIMO vibration control system.展开更多
Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotiv...Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.展开更多
To solve the synchronization and tracking problems,a cooperative control scheme is proposed for a class of higher-order multi-input and multi-output(MIMO)nonlinear multi-agent systems(MASs)subjected to uncertainties a...To solve the synchronization and tracking problems,a cooperative control scheme is proposed for a class of higher-order multi-input and multi-output(MIMO)nonlinear multi-agent systems(MASs)subjected to uncertainties and external disturbances.First,coupled relationships among Laplace matrix,leader-following adjacency matrix and consensus error are analyzed based on undirected graph.Furthermore,nonlinear disturbance observers(NDOs)are designed to estimate compounded disturbances in MASs,and a distributed cooperative anti-disturbance control protocol is proposed for high-order MIMO nonlinear MASs based on the outputs of NDOs and dynamic surface control approach.Finally,the feasibility and effectiveness of the proposed scheme are proven based on Lyapunov stability theory and simulation experiments.展开更多
In this paper,a linear/nonlinear switching active disturbance rejection control(SADRC)based decoupling control approach is proposed to deal with some difficult control problems in a class of multi-input multi-output(M...In this paper,a linear/nonlinear switching active disturbance rejection control(SADRC)based decoupling control approach is proposed to deal with some difficult control problems in a class of multi-input multi-output(MIMO)systems such as multi-variables,disturbances,and coupling,etc.Firstly,the structure and parameter tuning method of SADRC is introduced into this paper.Followed on this,virtual control variables are adopted into the MIMO systems,making the systems decoupled.Then the SADRC controller is designed for every subsystem.After this,a stability analyzed method via the Lyapunov function is proposed for the whole system.Finally,some simulations are presented to demonstrate the anti-disturbance and robustness of SADRC,and results show SADRC has a potential applications in engineering practice.展开更多
An adaptive inverse controller for nonliear discrete-time system is proposed in this paper. A compound neural network is constructed to identify the nonlinear system, which includes a linear part to approximate the no...An adaptive inverse controller for nonliear discrete-time system is proposed in this paper. A compound neural network is constructed to identify the nonlinear system, which includes a linear part to approximate the nonlinear system and a recurrent neural network to minimize the difference between the linear model and the real nonlinear system. Because the current control input is not included in the input vector of recurrent neural network (RNN), the inverse control law can be calculated directly. This scheme can be used in real-time nonlinear single-input single-output (SISO) and multi-input multi-output (MIMO) system control with less computation work. Simulation studies have shown that this scheme is simple and affects good control accuracy and robustness.展开更多
In this paper, a novel real time non-linear model predictive controller(NMPC) for a multi-variable coupled tank system(CTS) is designed. CTSs are highly non-linear and can be found in many industrial process applicati...In this paper, a novel real time non-linear model predictive controller(NMPC) for a multi-variable coupled tank system(CTS) is designed. CTSs are highly non-linear and can be found in many industrial process applications. The involvement of multi-input multi-output(MIMO) system makes the design of an effective controller a challenging task. MIMO systems have inherent couplings,interactions in-between the process input-output variables and generally have an complex internal structure. The aim of this paper is to design, simulate, and implement a novel real time constrained NMPC for a multi-variable CTS with the aid of intelligent system techniques. There are two major formidable challenges hindering the success of the implementation of a NMPC strategy in the MIMO case. The first is the difficulty of obtaining a good non-linear model by training a non-convex complex network to avoid being trapped in a local minimum solution. The second is the online real time optimisation(RTO) of the manipulated variable at every sampling time.A novel wavelet neural network(WNN) with high predicting precision and time-frequency localisation characteristic was selected for an MIMO model and a fast stochastic wavelet gradient algorithm was used for initial training of the network. Furthermore, a genetic algorithm was used to obtain the optimised parameters of the WNN as well as the RTO during the NMPC strategy. The proposed strategy performed well in both simulation and real time on an MIMO CTS. The results indicated that WNN provided better trajectory regulation with less mean-squared-error and average control energy compared to an artificial neural network. It is also shown that the WNN is more robust during abnormal operating conditions.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 overcome the disadvantage that the standard least squares support vector regression(LS-SVR) algorithm is not suitable to multiple-input multiple-output(MIMO) system modelling directly,an improved LS-SVR algorithm w...To overcome the disadvantage that the standard least squares support vector regression(LS-SVR) algorithm is not suitable to multiple-input multiple-output(MIMO) system modelling directly,an improved LS-SVR algorithm which was defined as multi-output least squares support vector regression(MLSSVR) was put forward by adding samples' absolute errors in objective function and applied to flatness intelligent control.To solve the poor-precision problem of the control scheme based on effective matrix in flatness control,the predictive control was introduced into the control system and the effective matrix-predictive flatness control method was proposed by combining the merits of the two methods.Simulation experiment was conducted on 900HC reversible cold roll.The performance of effective matrix method and the effective matrix-predictive control method were compared,and the results demonstrate the validity of the effective matrix-predictive control method.展开更多
In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear un...In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.展开更多
Sliding mode control(SMC) becomes a common tool in designing robust nonlinear control systems, due to its inherent characteristics such as insensitivity to system uncertainties and fast dynamic response.Two modes are ...Sliding mode control(SMC) becomes a common tool in designing robust nonlinear control systems, due to its inherent characteristics such as insensitivity to system uncertainties and fast dynamic response.Two modes are involved in the SMC operation, namely reaching mode and sliding mode.In the reaching mode, the system state is forced to reach the sliding surface in a finite time.The major drawback of the SMC approach is the occurrence of chattering in the sliding mode, which is undesirable in most applications.Generally, the trade-off between chattering reduction and fast reaching time must be considered in the conventional SMC design.This paper proposes SMC design with a novel reaching law called the exponential rate reaching law(ERRL) to reduce chattering, and the control structure of the converter is designed based on the multiinput SMC that is applied to a three-phase AC/DC power converter.The simulation and experimental results show the effectiveness of the proposed technique.展开更多
基金National Natural Science Foundation of China （10972104） The Fundamental Research Funds for NUAA（NS2010007）
文摘Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output （MIMO） random vibration test. During the control process with the difference control algorithm （DCA）, a lower triangular matrix is derived from Cholesky decomposition of a reference spectrum matrix. The diagonal elements of the lower triangular matrix （DELTM） may become negative. These negative values have no meaning in physical significance and can cause divergence of auto-power spectrum control. A proportional root mean square control algorithm （PRMSCA） provides another method to avoid the divergence caused by negative values of DELTM, but PRMSCA cannot control the cross-power spectrum. A new control algorithm named matrix power control algorithm （MPCA） is proposed in the paper. MPCA can guarantee that DELTM is always positive in the auto-power spectrum control. MPCA can also control the cross-power spectrum. After these three control algorithms are analyzed, three-input three-output random vibration control tests are implemented on a three-axis vibration shaker. The results show the validity of the proposed MPCA.
基金supported by the Priority Academic Program Development of Jiangsu Higher Education Institutionsthe Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. KYCX17_0234)
文摘A control method for Multi-Input Multi-Output（MIMO） non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified references composed of auto spectral densities, cross spectral densities and kurtoses on the test article in the laboratory. It is found that the cross spectral densities will bring intractable coupling problems and induce difficulty for the control of the multioutput kurtoses. Hence, a sequential phase modification method is put forward to solve the coupling problems in multi-input multi-output non-Gaussian random vibration test. To achieve the specified responses, an improved zero memory nonlinear transformation is utilized first to modify the Fourier phases of the signals with sequential phase modification method to obtain one frame reference response signals which satisfy the reference spectra and reference kurtoses. Then, an inverse system method is used in frequency domain to obtain the continuous stationary drive signals. At the same time, the matrix power control algorithm is utilized to control the spectra and kurtoses of the response signals further. At the end of the paper, a simulation example with a cantilever beam and a vibration shaker test are implemented and the results support the proposed method very well.
基金supported by the Fundamental Research Funds for the Central Universities (No. NS2015008)the corresponding work was performed in the State Key Laboratory of Mechanics and Control of Mechanical Structures
文摘Noises always disturb the control effect of an environment test especially in multi-input multi-output(MIMO) systems. If the frequency response function matrices are ill-conditioned, the noises in the driving forces will be amplified and the response spectral lines may awfully exceed their tolerances. Most of the major biases between the response spectra and the reference spectra are produced by the amplified noises. However, ordinary control algorithms can hardly reduce the level of noises. The influences of the noises on both the auto- and cross-power spectra are analyzed in this paper. As a conventional frequency domain method on the inverse problem, the Tikhonov filter is adopted in the environment test to suppress the exceeding spectral lines. By altering regularization parameters gradually, the auto-power spectra can be improved in a closed control loop. Instead of using the traditional way of selecting regularization parameters, we observe the coherence change to estimate noise eliminations. Incidentally, the requirement of coherence control can be realized. The errors of the phase are then studied and a phase control algorithm is introduced at the end as a supplement of cross-power spectra control. The Tikhonov filter and the proposed phase control algorithm are tested numerically and experimentally. The results show that the noises in the vicinity of lightly damped resonant peaks are more stubborn. The response spectra are able to be greatly improved by the combination of these two methods.
基金supported by National Natural Science Foundation of China (No. 60874116)Natural Science Foundation of Hebei Province (No. F2009000857)
文摘A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a supervision module for the local controller, ILC can improve the tracking performance of the closed-loop system along the batch direction. In this study, an ILC-based P-type controller is proposed for multi-input multi-output (MIMO) linear batch processes, where a P-type controller is used to design the control signal directly and an ILC module is used to update the set-point for the P-type controller. Under the proposed ILC-based P-type controller, the closed-loop system can be transformed to a 2-dimensional (2D) Roesser s system. Based on the 2D system framework, a sufficient condition for asymptotic stability of the closed-loop system is derived in this paper. In terms of the average tracking error (ATE), the closed-loop control performance under the proposed algorithm can be improved from batch to batch, even though there are repetitive disturbances. A numerical example is used to validate the proposed results.
基金supported by Islamic Azad University–Ardabil Branch。
文摘In this study, a novel approach for dynamic modeling and closed-loop control of hybrid grid-connected renewable energy system with multi-input multi-output(MIMO) controller is proposed. The studied converter includes two parallel DC-DC boost converters, which are connected into the power grid through a single-phase H-bridge inverter. The proposed MIMO controller is developed for maximum power point tracking of photovoltaic(PV)/fuel-cell(FC) input power sources and output power control of the grid-connected DC-AC inverter. Considering circuit topology of the system, a unique MIMO model is proposed for the analysis of the entire system. A unique model of the system includes all of the circuit state variables in DCDC and DC-AC converters. In fact, from the viewpoint of closed-loop controller design, the hybrid grid-connected energy system is an MIMO system. The control inputs of the system are duty cycles of the DC-DC boost converters and the amplitude modulation index of DC-AC inverters. Furthermore, the control outputs are the output power of the PV/FC input power sources as well as AC power injected into the power grid. After the development of the unique model for the entire system, a decoupling network is introduced for system input-output linearization due to inherent connection of the control outputs with all of the system inputs. Considering the decoupled model and small signal linearization, the required linear controllers are designed to adjust the outputs. Finally, to evaluate the accuracy and effectiveness of the designed controllers, the PV/FC based grid-connected system is simulated using the MATLAB/Simulink toolbox.
文摘This paper presents the design of decentralized repetitive control （RC） for multi-input multi-output （MIMO） systems. An optimization method is used to obtain a RC compensator that ensures system stability and good tracking performance. The designed compensator is in the form of a stable, low order, and causal filter, in which the compensator can be implemented separately without being merged with the RC internal model. This will reduce complexity in the implementation. Simulation results and comparison study are given to demonstrate the effectiveness of the proposed design. The novelty of design is also verified in experiments on a 2 degrees of freedom （DOF） robot.
基金This project is supported by Program for New Century Excellent Talents in University,China(No.NCET-04-0325).
文摘The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF. The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation. The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF （degree-of-freedom） hydraulic vibration table. The result shows that it is favorable to improve the control precision of the MIMO vibration control system.
基金Project supported by the Centre for Smart Grid and Information Convergence(CeSGIC)at Xi’an Jiaotong-Liverpool University,China
文摘Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.
基金National Natural Science Foundation of China(No.61963029)Jiangxi Provincial Natural Science Foundation(Nos.20224BAB202027 and 20232ACB202007)。
文摘To solve the synchronization and tracking problems,a cooperative control scheme is proposed for a class of higher-order multi-input and multi-output(MIMO)nonlinear multi-agent systems(MASs)subjected to uncertainties and external disturbances.First,coupled relationships among Laplace matrix,leader-following adjacency matrix and consensus error are analyzed based on undirected graph.Furthermore,nonlinear disturbance observers(NDOs)are designed to estimate compounded disturbances in MASs,and a distributed cooperative anti-disturbance control protocol is proposed for high-order MIMO nonlinear MASs based on the outputs of NDOs and dynamic surface control approach.Finally,the feasibility and effectiveness of the proposed scheme are proven based on Lyapunov stability theory and simulation experiments.
基金supported by the Scientific Research Innovation Development Foundation of Army Engineering University((2019)71).
文摘In this paper,a linear/nonlinear switching active disturbance rejection control(SADRC)based decoupling control approach is proposed to deal with some difficult control problems in a class of multi-input multi-output(MIMO)systems such as multi-variables,disturbances,and coupling,etc.Firstly,the structure and parameter tuning method of SADRC is introduced into this paper.Followed on this,virtual control variables are adopted into the MIMO systems,making the systems decoupled.Then the SADRC controller is designed for every subsystem.After this,a stability analyzed method via the Lyapunov function is proposed for the whole system.Finally,some simulations are presented to demonstrate the anti-disturbance and robustness of SADRC,and results show SADRC has a potential applications in engineering practice.
基金Supported by the National Natural Science Foundation of China (60575009, 60574036)
文摘An adaptive inverse controller for nonliear discrete-time system is proposed in this paper. A compound neural network is constructed to identify the nonlinear system, which includes a linear part to approximate the nonlinear system and a recurrent neural network to minimize the difference between the linear model and the real nonlinear system. Because the current control input is not included in the input vector of recurrent neural network (RNN), the inverse control law can be calculated directly. This scheme can be used in real-time nonlinear single-input single-output (SISO) and multi-input multi-output (MIMO) system control with less computation work. Simulation studies have shown that this scheme is simple and affects good control accuracy and robustness.
基金supported by Petroleum Training Development Fund,Nigeria
文摘In this paper, a novel real time non-linear model predictive controller(NMPC) for a multi-variable coupled tank system(CTS) is designed. CTSs are highly non-linear and can be found in many industrial process applications. The involvement of multi-input multi-output(MIMO) system makes the design of an effective controller a challenging task. MIMO systems have inherent couplings,interactions in-between the process input-output variables and generally have an complex internal structure. The aim of this paper is to design, simulate, and implement a novel real time constrained NMPC for a multi-variable CTS with the aid of intelligent system techniques. There are two major formidable challenges hindering the success of the implementation of a NMPC strategy in the MIMO case. The first is the difficulty of obtaining a good non-linear model by training a non-convex complex network to avoid being trapped in a local minimum solution. The second is the online real time optimisation(RTO) of the manipulated variable at every sampling time.A novel wavelet neural network(WNN) with high predicting precision and time-frequency localisation characteristic was selected for an MIMO model and a fast stochastic wavelet gradient algorithm was used for initial training of the network. Furthermore, a genetic algorithm was used to obtain the optimised parameters of the WNN as well as the RTO during the NMPC strategy. The proposed strategy performed well in both simulation and real time on an MIMO CTS. The results indicated that WNN provided better trajectory regulation with less mean-squared-error and average control energy compared to an artificial neural network. It is also shown that the WNN is more robust during abnormal operating conditions.
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Project(50675186) supported by the National Natural Science Foundation of China
文摘To overcome the disadvantage that the standard least squares support vector regression(LS-SVR) algorithm is not suitable to multiple-input multiple-output(MIMO) system modelling directly,an improved LS-SVR algorithm which was defined as multi-output least squares support vector regression(MLSSVR) was put forward by adding samples' absolute errors in objective function and applied to flatness intelligent control.To solve the poor-precision problem of the control scheme based on effective matrix in flatness control,the predictive control was introduced into the control system and the effective matrix-predictive flatness control method was proposed by combining the merits of the two methods.Simulation experiment was conducted on 900HC reversible cold roll.The performance of effective matrix method and the effective matrix-predictive control method were compared,and the results demonstrate the validity of the effective matrix-predictive control method.
文摘In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.
文摘Sliding mode control(SMC) becomes a common tool in designing robust nonlinear control systems, due to its inherent characteristics such as insensitivity to system uncertainties and fast dynamic response.Two modes are involved in the SMC operation, namely reaching mode and sliding mode.In the reaching mode, the system state is forced to reach the sliding surface in a finite time.The major drawback of the SMC approach is the occurrence of chattering in the sliding mode, which is undesirable in most applications.Generally, the trade-off between chattering reduction and fast reaching time must be considered in the conventional SMC design.This paper proposes SMC design with a novel reaching law called the exponential rate reaching law(ERRL) to reduce chattering, and the control structure of the converter is designed based on the multiinput SMC that is applied to a three-phase AC/DC power converter.The simulation and experimental results show the effectiveness of the proposed technique.
