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ADAPTIVE PREDICTIVE CONTROL OF NEAR-SPACE VEHICLE USING FUNCTIONAL LINK NETWORK 被引量:3
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作者 都延丽 吴庆宪 姜长生 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2010年第2期148-154,共7页
A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle (NHV) in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predicti... A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle (NHV) in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller (OGPC) and the functional link network (FLN) direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking. 展开更多
关键词 predictive control systems adaptive control systems UNCERTAINTY functional link network near-space vehicle
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Time-stamped predictive functional control for networked control systems with random delays
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作者 张奇智 张卫东 《Journal of Southeast University(English Edition)》 EI CAS 2005年第2期149-152,共4页
The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is... The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is proposed,which generalizes the standard PFC algorithm to networked control systems with random delays.The algorithm uses the time-stamp method to estimate the control delay,predicts the future outputs based on a discrete time delay state space model,and drives the control law that applies to an NCS from the idea of a PFC algorithm.A networked control system was constructed based on TrueTime simulator,with which the time-stamped PFC algorithm was compared with the standard PFC algorithm.The response curves show that the proposed algorithm has better control performance. 展开更多
关键词 networked control systems random delays predictive functional control industrial Ethernet
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Predictive functional control based on fuzzy T-S model for HVAC systems temperature control 被引量:6
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作者 Hongli LU Lei JIA +1 位作者 Shulan KONG Zhaosheng ZHANG 《控制理论与应用(英文版)》 EI 2007年第1期94-98,共5页
In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) f... In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc. 展开更多
关键词 T-S fuzzy model predictive functional control Least squares method HVAC systems
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Incremental multivariable predictive functional control and its application in a gas fractionation unit 被引量:3
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作者 施惠元 苏成利 +3 位作者 曹江涛 李平 宋英莉 李宁波 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第12期4653-4668,共16页
The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the t... The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the traditional PID control has been proven not sufficient and capable for this particular petro-chemical process.In this work,an incremental multivariable predictive functional control(IMPFC) algorithm was proposed with less online computation,great precision and fast response.An incremental transfer function matrix model was set up through the step-response data,and predictive outputs were deduced with the theory of single-value optimization.The results show that the method can optimize the incremental control variable and reject the constraint of the incremental control variable with the positional predictive functional control algorithm,and thereby making the control variable smoother.The predictive output error and future set-point were approximated by a polynomial,which can overcome the problem under the model mismatch and make the predictive outputs track the reference trajectory.Then,the design of incremental multivariable predictive functional control was studied.Simulation and application results show that the proposed control strategy is effective and feasible to improve control performance and robustness of process. 展开更多
关键词 gas fractionation unit multivariable process incremental predictive functional control
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Active disturbance rejected predictive functional control for space vehicles with RCS 被引量:3
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作者 TIAN Jiayi ZHANG Shifeng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第5期1022-1035,共14页
Reaction control system(RCS) is a powerful and efficient actuator for space vehicles attitude control, which is typically characterized as a pulsed unilateral effector only with two states(off/on). Along with inevitab... Reaction control system(RCS) is a powerful and efficient actuator for space vehicles attitude control, which is typically characterized as a pulsed unilateral effector only with two states(off/on). Along with inevitable internal uncertainties and external disturbances in practice, this inherent nonlinear character always hinders space vehicles autopilot from pursuing precise tracking performance. Compared to most of pre-existing methodologies that passively suppress the uncertainties and disturbances, a design based on predictive functional control(PFC) and generalized extended state observer(GESO) is firstly proposed for three-axis RCS control system to actively reject that with no requirement for additional fuel consumption. To obtain a high fidelity predictive model on which the performance of PFC greatly depends, the nonlinear coupling multiple-input multiple-output(MIMO) flight dynamics model is parameterized as a state-dependent coefficient form. And based on that, a MIMO PFC algorithm in state space domain for a plant of arbitrary orders is deduced in this paper.The internal uncertainties and external disturbances are lumped as a total disturbance, which is estimated and cancelled timely to further enhance the robustness. The continuous control command synthesised by above controller-rejector tandem is finally modulated by pulse width pulse frequency modulator(PWPF) to on-off signals to meet RCS requirement. The robustness and feasibility of the proposed design are validated by a series of performance comparison simulations with some prominent methods in the presence of significant perturbations and disturbances, as well as measurement noise. 展开更多
关键词 reaction control system(RCS) predictive functional control(PFC) generalized extended state observer(GESO) pulse width pulse frequency(PWPF) multiple-input multiple-output(MIMO)
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Predictive functional control of integrating process based on impulse response 被引量:2
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作者 BinZHANG PingLI WeidongZHANG 《控制理论与应用(英文版)》 EI 2004年第2期196-200,共5页
The predictive model is built according to the characteristics of the impulse response of integrating process. In order to eliminate the permanent offset between the setpoint and the process output in the presence of ... The predictive model is built according to the characteristics of the impulse response of integrating process. In order to eliminate the permanent offset between the setpoint and the process output in the presence of the load disturbance, a novel error compensation method is proposed. Then predictive functional control of integrating process is designed. The method given generates a simple control structure, which can significandy reduce online computation. Furthermore, the tuning of the controller is fairly straightforward. Simulation results indicate that the designed control system is relatively robust to the parameters variation of the process. 展开更多
关键词 Integrating process Time delay Impulse response predictive functional control (PFC)
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Adaptive predictive functional control based on Takagi-Sugeno model and its application to pH process 被引量:5
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作者 苏成利 李平 《Journal of Central South University》 SCIE EI CAS 2010年第2期363-371,共9页
In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive fun... In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC. 展开更多
关键词 Takagi-Sugeno (T-S) model adaptive fuzzy predictive functional control (AFPFC) weighted recursive least square (WRLS) pH process
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Predictive Functional Controller with a Similar Proportional Integral Optimal Regulator Structure:Comparison with Traditional Predic-tive Functional Controller and Application to Heavy Oil Coking Equipment 被引量:1
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作者 张日东 王树青 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2007年第2期247-253,共7页
By extending the system's state variables,a novel predictive functional controller has been developed.The structure of this controller is similar to that of classical proportional integral(PI)optimal controller an... By extending the system's state variables,a novel predictive functional controller has been developed.The structure of this controller is similar to that of classical proportional integral(PI)optimal controller and in-cludes a control block that can perform a feed-forward control of future P-step set points.It considers both the state variables and the output errors in its cost function,which results in enhanced control performance compared with traditional state space predictive functional control(TSSPFC)methods that consider only the predictive output er-rors.The predictive functional controller(PFC)has been compared with TSSPFC in terms of tracking ability,dis-turbance rejection,and also based on its application to heavy oil coking equipment.The results obtained show the effectiveness of the controller. 展开更多
关键词 state space model PI optimal regulator predictive functional control
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Predictive functional control (PFC) and its application in chlorinated polyethylene process
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作者 李鸿亮 苏宏业 +1 位作者 刘军 褚健 《Journal of Zhejiang University Science》 CSCD 2003年第3期300-304,共5页
The main principle and the characteristic of Predictive Functional Control (PFC) strategy are presented in this paper and the corresponding control system aid design software APC-PFC is also introduced. For a chlorina... The main principle and the characteristic of Predictive Functional Control (PFC) strategy are presented in this paper and the corresponding control system aid design software APC-PFC is also introduced. For a chlorinated polyethylene (CPE) process, a design scheme of cascade predictive functional control system is described and the control performance is improved obviously. 展开更多
关键词 predictive control predictive functional control (PFC) Base functions Chlorinated Polyethylene (CPE)
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Enhanced Water Quality Control Based on Predictive Optimization for Smart Fish Farming
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作者 Azimbek Khudoyberdiev Mohammed Abdul Jaleel +1 位作者 Israr Ullah DoHyeun Kim 《Computers, Materials & Continua》 SCIE EI 2023年第6期5471-5499,共29页
The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations.Internet of Things(IoT)based Modern fish farming systems can significantly optimi... The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations.Internet of Things(IoT)based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish production.This objective requires intensive monitoring,prediction,and control by optimizing leading factors that impact fish growth,including temperature,the potential of hydrogen(pH),water level,and feeding rate.This paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish farming.The proposed fish farm control mechanism has a predictive optimization to deal with water quality control and efficient energy consumption problems.Fish farm indoor and outdoor values are applied to predict the water quality parameters,whereas a novel objective function is proposed to achieve an optimal fish growth environment based on predicted parameters.Fuzzy logic control is utilized to calculate control parameters for IoT actuators based on predictive optimal water quality parameters by minimizing energy consumption.To evaluate the efficiency of the proposed system,the overall approach has been deployed to the fish tank as a case study,and a number of experiments have been carried out.The results show that the predictive optimization module allowed the water quality parameters to be maintained at the optimal level with nearly 30%of energy efficiency at the maximum actuator control rate compared with other control levels. 展开更多
关键词 Smart fish farming internet of things(IoT) predictive optimization objective function fuzzy logic control(FLC)
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SVM with Quadratic Polynomial Kernel Function Based Nonlinear Model One-step-ahead Predictive Control 被引量:12
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作者 钟伟民 何国龙 +1 位作者 皮道映 孙优贤 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2005年第3期373-379,共7页
A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identifica... A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identification method. By solving a cubic equation in the feature space, an explicit predictive control law is obtained through the predictive control mechanism. The effect of controller is demonstrated on a recognized benchmark problem and on the control of continuous-stirred tank reactor (CSTR). Simulation results show that SVM with quadratic polynomial kernel function based predictive controller can be well applied to nonlinear systems, with good performance in following reference trajectory as well as in disturbance-rejection. 展开更多
关键词 nonlinear model predictive control support vector machine nonlinear system identification kernel function
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Hybrid Predictive Control Based on High-Order Differential State Observers and Lyapunov Functions for Switched Nonlinear Systems 被引量:1
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作者 Baili Su Guoyuan Qi Barend J. van Wyk 《Applied Mathematics》 2013年第9期32-42,共11页
In this paper, a hybrid predictive controller is proposed for a class of uncertain switched nonlinear systems based on high-order differential state observers and Lyapunov functions. The main idea is to design an outp... In this paper, a hybrid predictive controller is proposed for a class of uncertain switched nonlinear systems based on high-order differential state observers and Lyapunov functions. The main idea is to design an output feedback bounded controller and a predictive controller for each subsystem using high-order differential state observers and Lyapunov functions, to derive a suitable switched law to stabilize the closed-loop subsystem, and to provide an explicitly characterized set of initial conditions. For the whole switched system, based on the high-order differentiator, a suitable switched law is designed to ensure the whole closed-loop’s stability. The simulation results for a chemical process show the validity of the controller proposed in this paper. 展开更多
关键词 SWITCHED System LYAPUNOV function High Order DIFFERENTIATOR control Constraint Output Feedback Model predictive control Stable Region
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Performance Monitoring of the Data-driven Subspace Predictive Control Systems Based on Historical Objective Function Benchmark 被引量:3
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作者 王陆 李柠 李少远 《自动化学报》 EI CSCD 北大核心 2013年第5期542-547,共6页
关键词 预测控制系统 性能监控 数据驱动 子空间 历史 基准 监视控制器 目标函数
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Kautz Function Based Continuous-Time Model Predictive Controller for Load Frequency Control in a Multi-Area Power System
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作者 A.Parassuram P.Somasundaram 《Computer Modeling in Engineering & Sciences》 SCIE EI 2018年第11期169-187,共19页
A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control(LFC).A dynamic model of an interconnected power system was used for Model P... A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control(LFC).A dynamic model of an interconnected power system was used for Model Predictive Controller(MPC)design.MPC predicts the future trajectory of the dynamic model by calculating the optimal closed loop feedback gain matrix.In this paper,the optimal closed loop feedback gain matrix was calculated using Kautz function.Being an Orthonormal Basis Function(OBF),Kautz function has an advantage of solving complex pole-based nonlinear system.Genetic Algorithm(GA)was applied to optimally tune the Kautz function-based MPC.A constraint based on phase plane analysis was implemented with the cost function in order to improve the robustness of the Kautz function-based MPC.The proposed method was simulated with three area interconnected power system and the efficiency of the proposed method was measured and exhibited by comparing with conventional Proportional and Integral(PI)controller and Linear Quadratic Regulation(LQR). 展开更多
关键词 Load frequency control model predictive controlLER orthonormal basis function kautz function phase plane analysis linear QUADRATIC REGULATOR proportional and integral controlLER genetic algorithm.
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Nonlinear Model Predictive Control Based on Support Vector Machine with Multi-kernel 被引量:22
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作者 包哲静 皮道映 孙优贤 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2007年第5期691-697,共7页
Multi-kernel-based support vector machine (SVM) model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a... Multi-kernel-based support vector machine (SVM) model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a SVM with spline kernel function. With the help of this model, nonlinear model predictive control can be transformed to linear model predictive control, and consequently a unified analytical solution of optimal input of multi-step-ahead predictive control is possible to derive. This algorithm does not require online iterative optimization in order to be suitable for real-time control with less calculation. The simulation results of pH neutralization process and CSTR reactor show the effectiveness and advantages of the presented algorithm. 展开更多
关键词 nonlinear model predictive control support vector machine with multi-kernel nonlinear system identification kernel function
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Support vector machine based nonlinear model multi-step-ahead optimizing predictive control 被引量:9
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作者 钟伟民 皮道映 孙优贤 《Journal of Central South University of Technology》 EI 2005年第5期591-595,共5页
A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established... A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established by black-box identification. And a quadratic objective function with receding horizon was selected to obtain the controller output. By solving a nonlinear optimization problem with equality constraint of model output and boundary constraint of controller output using Nelder-Mead simplex direct search method, a sub-optimal control law was achieved in feature space. The effect of the controller was demonstrated on a recognized benchmark problem and a continuous-stirred tank reactor. The simulation results show that the multi-step-ahead predictive controller can be well applied to nonlinear system, with better performance in following reference trajectory and disturbance-rejection. 展开更多
关键词 nonlinear model predictive control support vector machine nonlinear system identification kernel function nonlinear optimization
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New predictive control algorithms based on Least Squares Support Vector Machines 被引量:3
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作者 刘斌 苏宏业 褚健 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2005年第5期440-446,共7页
Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on Least Squares Support Vector Machines (LS-SVM) model. For the weakly nonlin... Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on Least Squares Support Vector Machines (LS-SVM) model. For the weakly nonlinear system, the system model is built by using LS-SVM with linear kernel function, and then the obtained linear LS-SVM model is transformed into linear input-output relation of the controlled system. However, for the strongly nonlinear system, the off-line model of the controlled system is built by using LS-SVM with Radial Basis Function (RBF) kernel. The obtained nonlinear LS-SVM model is linearized at each sampling instant of system running, after which the on-line linear input-output model of the system is built. Based on the obtained linear input-output model, the Generalized Predictive Control (GPC) algorithm is employed to implement predictive control for the controlled plant in both algorithms. The simulation results after the presented algorithms were implemented in two different industrial processes model; respectively revealed the effectiveness and merit of both algorithms. 展开更多
关键词 Least Squares Support Vector Machines Linear kernel function RBF kernel function Generalized predictive control
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An improved constrained model predictive control approach for Hammerstein-Wiener nonlinear systems 被引量:1
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作者 李妍 陈雪原 +1 位作者 毛志忠 袁平 《Journal of Central South University》 SCIE EI CAS 2014年第3期926-932,共7页
Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approa... Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approach, the maximum and minimum of partial derivative for input and output nonlinearities are solved in the neighbourhood of the equilibrium. And several parameter-dependent Lyapunov functions, each one corresponding to a different vertex of polytopic descriptions models, are introduced to analyze the stability of Hammerstein-Wiener systems, but only one Lyapunov function is utilized to analyze system stability like the traditional method. Consequently, the conservation of the traditional quadratic stability is removed, and the terminal regions are enlarged. Simulation and field trial results show that the proposed algorithm is valid. It has higher control precision and shorter blowing time than the traditional approach. 展开更多
关键词 Hammerstein-Wiener nonlinear systems model predictive control parameter-dependent Lyapunov functions stability linear matrix inequalities (LMIs)
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Predictive control for greenhouse temperature and humidity and energy optimization by improved NMPC objective function algorithm
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作者 Lina Wang Ying Zhang +2 位作者 Mengjie Xu Qiuhui Liu Binrui Wang 《International Journal of Agricultural and Biological Engineering》 SCIE 2024年第5期128-136,共9页
Persistent low temperatures in autumn and winter have a huge impact on crops,and greenhouses rely on solar radiation and heating equipment to meet the required indoor temperature.But the energy cost of frequent operat... Persistent low temperatures in autumn and winter have a huge impact on crops,and greenhouses rely on solar radiation and heating equipment to meet the required indoor temperature.But the energy cost of frequent operation of the actuators is exceptionally high.The relationship between greenhouse environmental control accuracy and energy consumption is one of the key issues faced in greenhouse research.In this study,a non-linear model predictive control method with an improved objective function was proposed.The improved objective function used tolerance intervals and boundary constraints to optimize the objective evaluation.The nonlinear model predictive control(NMPC)controller design was based on the wavelet neural network(WNN)data-driven model and applied the interior point method to solve the optimal solution of the objective function control,thus balancing the contradiction between energy consumption and control precision.The simulation results showed that the improved NMPC method reduced energy consumption by 21.02%and 9.54%compared with the model predictive control and regular NMPC,which proved the method achieved good results in a low-temperature environment.This research can provide an important reference for the field as it offers a more efficient approach to managing greenhouse climates,potentially leading to substantial energy savings and enhanced sustainability in agricultural practices. 展开更多
关键词 greenhouse environmental control greenhouse energy optimization nonlinear model predictive control objective function improvement
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Max-plus-linear model-based predictive control for constrained hybrid systems: linear programming solution
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作者 Yuanyuan ZOU Shaoyuan LI 《控制理论与应用(英文版)》 EI 2007年第1期71-76,共6页
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
关键词 Hybrid systems Max-plus-linear systems Model predictive control Canonical form Max-min-plus- scaling function Linear programming
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