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Adaptive nonlinear model predictive control design of a flexible-link manipulator with uncertain parameters 被引量:7
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作者 Fabian Schnelle Peter Eberhard 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2017年第3期529-542,共14页
This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented... This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented Kalman filtering. Reducing the nonlinear system to a linear system by feedback linearization simplifies the optimization problem of the model predictive controller significantly, which, however, is no longer linear in the presence of parameter uncertainties and can potentially lead to an undesired dynamical behaviour. An unscented Kalman filter is used to approximate the dynamics of the prediction model by an online parameter estimation, which leads to an adaptation of the optimization problem in each time step and thus to a better prediction and an improved input action. Finally, a detailed fuzzy-arithmetic analysis is performed in order to quantify the effect of the uncertainties on the control structure and to derive robustness assessments. The control structure is applied to a serial manipulator with two flexible links containing uncertain model parameters and acting in three-dimensional space. 展开更多
关键词 model predictive control Feedback linearization Unscented Kalman filter Flexible-link manipulator Fuzzy-arithmetical analysis
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Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model 被引量:7
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作者 SU Cheng-li WANG Shu-qing 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2006年第10期1723-1732,共10页
An extended robust model predictive control approach for input constrained discrete uncertain nonlinear systems with time-delay based on a class of uncertain T-S fuzzy models that satisfy sector bound condition is pre... An extended robust model predictive control approach for input constrained discrete uncertain nonlinear systems with time-delay based on a class of uncertain T-S fuzzy models that satisfy sector bound condition is presented. In this approach, the minimization problem of the “worst-case” objective function is converted into the linear objective minimization problem in- volving linear matrix inequalities (LMIs) constraints. The state feedback control law is obtained by solving convex optimization of a set of LMIs. Sufficient condition for stability and a new upper bound on robust performance index are given for these kinds of uncertain fuzzy systems with state time-delay. Simulation results of CSTR process show that the proposed robust predictive control approach is effective and feasible. 展开更多
关键词 Uncertain Takagi-Sugeno fuzzy model TIME-DELAY model predictive control (MPC) linear matrix inequalities(LMIs) Robustness
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Model Predictive Control of Nonlinear Systems: Stability Region and Feasible Initial Control 被引量:5
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作者 Xiao-Bing Hu Wen-Hua Chen 《International Journal of Automation and computing》 EI 2007年第2期195-202,共8页
This paper proposes a new method for model predictive control (MPC) of nonlinear systems to calculate stability region and feasible initial control profile/sequence, which are important to the implementations of MPC... This paper proposes a new method for model predictive control (MPC) of nonlinear systems to calculate stability region and feasible initial control profile/sequence, which are important to the implementations of MPC. Different from many existing methods, this paper distinguishes stability region from conservative terminal region. With global linearization, linear differential inclusion (LDI) and linear matrix inequality (LMI) techniques, a nonlinear system is transformed into a convex set of linear systems, and then the vertices of the set are used off-line to design the controller, to estimate stability region, and also to determine a feasible initial control profile/sequence. The advantages of the proposed method are demonstrated by simulation study. 展开更多
关键词 model predictive control (MPC) stability region terminal region linear differential inclusion (LDI) linear matrix inequality (LMI).
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Distributed Model Predictive Control with Actuator Saturation for Markovian Jump Linear System 被引量:2
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作者 Yan Song Haifeng Lou Shuai Liu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI 2015年第4期374-381,共8页
This paper is concerned with the distributed model predictive control (MPC) problem for a class of discrete-time Markovian jump linear systems (MJLSs) subject to actuator saturation and polytopic uncertainty in system... This paper is concerned with the distributed model predictive control (MPC) problem for a class of discrete-time Markovian jump linear systems (MJLSs) subject to actuator saturation and polytopic uncertainty in system matrices. The global system is decomposed into several subsystems which coordinate with each other. A set of distributed controllers is designed by solving a min-max optimization problem in terms of the solutions of linear matrix inequalities (LMIs). An iterative algorithm is developed to achieve the online computation. Finally, a simulation example is employed to show the effectiveness of the proposed algorithm. © 2014 Chinese Association of Automation. 展开更多
关键词 Actuators ALGORITHMS Iterative methods linear matrix inequalities linear systems Markov processes Matrix algebra model predictive control Optimization predictive control systems Robustness (control systems)
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An Improved Robust Model Predictive Control Approach to Systems with Linear Fractional Transformation Perturbations 被引量:2
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作者 Peng-Yuan Zheng Yu-Geng Xi De-Wei Li 《International Journal of Automation and computing》 EI 2011年第1期134-140,共7页
In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws... In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws instead of a single one, the control performance can be improved and the region of attraction can be enlarged compared with the existing model predictive control (MPC) approaches. Moreover, a synthesis approach of MPC is developed to achieve high performance with lower on-line computational burden. The effectiveness of the proposed approach is verified by simulation examples. 展开更多
关键词 Robust model predictive control linear fractional transformation (LFT) perturbations linear matrix inequalities (LMIs) feedback model predictive control (MPC) framework sequence of feedback control laws.
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Model predictive control synthesis algorithm based on polytopic terminal region for Hammerstein-Wiener nonlinear systems 被引量:2
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作者 李妍 陈雪原 毛志忠 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第9期2028-2034,共7页
An improved model predictive control algorithm is proposed for Hammerstein-Wiener nonlinear systems.The proposed synthesis algorithm contains two parts:offline design the polytopic invariant sets,and online solve the ... An improved model predictive control algorithm is proposed for Hammerstein-Wiener nonlinear systems.The proposed synthesis algorithm contains two parts:offline design the polytopic invariant sets,and online solve the min-max optimization problem.The polytopic invariant set is adopted to replace the traditional ellipsoid invariant set.And the parameter-correlation nonlinear control law is designed to replace the traditional linear control law.Consequently,the terminal region is enlarged and the control effect is improved.Simulation and experiment are used to verify the validity of the wind tunnel flow field control algorithm. 展开更多
关键词 Hammerstein-Wiener nonlinear systems model predictive control polytopic terminal constraint set parameter-correlation nonlinear control stability linear matrix inequalities (LMIs)
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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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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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Model⁃Free Predictive Control for a Kind of High Order Nonlinear Systems
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作者 Ye Tian Baili Su 《Journal of Harbin Institute of Technology(New Series)》 CAS 2022年第2期62-69,共8页
For a type of high⁃order discrete⁃time nonlinear systems(HDNS)whose system models are undefined,a model⁃free predictive control(MFPC)algorithm is proposed in this paper.At first,an estimation model is given by the imp... For a type of high⁃order discrete⁃time nonlinear systems(HDNS)whose system models are undefined,a model⁃free predictive control(MFPC)algorithm is proposed in this paper.At first,an estimation model is given by the improved projection algorithm to approach the controlled nonlinear system.Then,on the basis of the estimation model,a predictive controller is designed by solving the finite time domain rolling optimization quadratic function,and the controller’s explicit analytic solution is also obtained.Furthermore,the closed⁃loop system's stability can be ensured.Finally,the results of simulation reveal that the presented control strategy has a faster convergence speed as well as more stable dynamic property compared with the model⁃free sliding mode control(MFSC). 展开更多
关键词 nonlinear system compact dynamic linearization(CDL) model predictive control(MPC) model-free control(MFC) projection algorithm
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Application of Linear Model Predictive Control and Input-Output Linearization to Constrained Control of 3D Cable Robots
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作者 Ali Ghasemi 《Modern Mechanical Engineering》 2011年第2期69-76,共8页
Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging comp... Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation. 展开更多
关键词 CABLE ROBOTS INPUT-OUTPUT linearIZATION linear model predictive control
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A Pragmatic Approach for Assessing the Economic Performance of Model Predictive Control Systems and Its Industrial Application 被引量:12
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作者 赵超 苏宏业 +1 位作者 古勇 褚建 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2009年第2期241-250,共10页
In this article,an approach for economic performance assessment of model predictive control(MPC) system is presented.The method builds on steady-state economic optimization techniques and uses the linear quadratic Gau... In this article,an approach for economic performance assessment of model predictive control(MPC) system is presented.The method builds on steady-state economic optimization techniques and uses the linear quadratic Gaussian(LQG) benchmark other than conventional minimum variance control(MVC) to estimate the potential of reduction in variance.The LQG control is a more practical performance benchmark compared to MVC for performance assessment since it considers input variance and output variance,and it thus provides a desired basis for determining the theoretical maximum economic benefit potential arising from variability reduction.Combining the LQG benchmark directly with benefit potential of MPC control system,both the economic benefit and the optimal operation condition can be obtained by solving the economic optimization problem.The proposed algorithm is illustrated by simulated example as well as application to economic performance assessment of an industrial model predictive control system. 展开更多
关键词 economic performance assessment model predictive control linear quadratic Gaussian benchmark steady-state model based optimization
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Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model 被引量:9
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作者 熊智华 ZHANG Jie 董进 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2008年第2期235-240,共6页
A batch-to-batch optimal iterative learning control (ILC) strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation (LTVP) model is built for produc... A batch-to-batch optimal iterative learning control (ILC) strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation (LTVP) model is built for product quality around the nominal trajectories. To address problems of model-plant mismatches, model prediction errors in the previous batch run are added to the model predictions for the current batch run. Then tracking error transition models can be built, and the ILC law with direct error feedback is explicitly obtained, A rigorous theorem is proposed, to prove the convergence of tracking error under ILC, The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC. 展开更多
关键词 iterative learning control linear time-varying perturbation model batch process
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Robust model predictive control with randomly occurred networked packet loss in industrial cyber physical systems 被引量:8
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作者 CAI Hong-bin LI Ping +1 位作者 SU Cheng-li CAO Jiang-tao 《Journal of Central South University》 SCIE EI CAS CSCD 2019年第7期1921-1933,共13页
For a class of linear discrete-time systems that is subject to randomly occurred networked packet loss in industrial cyber physical systems, a novel robust model predictive control method with active compensation mech... For a class of linear discrete-time systems that is subject to randomly occurred networked packet loss in industrial cyber physical systems, a novel robust model predictive control method with active compensation mechanism was proposed. The probability distribution of packet loss is described as the Bernoulli distributed white sequences. By using the Lyapunov stability theory, the existing sufficient conditions of the controller are derived from solving a group of linear matrix inequalities. Moreover, dropout-rate with uncertainty and unknown dropout-rate are also considered, which can greatly reduce the conservativeness of the controller. The designed robust model predictive control method not only efficiently eliminates the negative effects of the networked data loss in industrial cyber physical systems but also ensures the stability of closed-loop system. Two examples were provided to illustrate the superiority and effectiveness of the proposed method. 展开更多
关键词 robust model predictive control networked control system packet loss linear matrix inequalities (LMIs)
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Robust model predictive control for continuous uncertain systems with state delay 被引量:4
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作者 Chunyan HAN Xiaohua LIU Huanshui ZHANG 《控制理论与应用(英文版)》 EI 2008年第2期189-194,共6页
This paper is concerned with robust model predictive control for linear continuous uncertain systems with state delay and control constraints, A piecewise constant control sequence is calculated by minimizing the uppe... This paper is concerned with robust model predictive control for linear continuous uncertain systems with state delay and control constraints, A piecewise constant control sequence is calculated by minimizing the upper-bound of the infinite horizon quadratic cost function, At each sampling time, the sufficient conditions for the existence of the model predictive control are derived, and expressed as a set of linear matrix inequalities. The robust stability of the closed-loop svstems is guaranteed bv the proposed design method. A numerical example is given to illustrate the main results. 展开更多
关键词 model predictive control (MPC) Robust control linear matrix inequality (LMI) Time-delay systems
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A Modified Model Predictive Control Scheme 被引量:1
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作者 Xiao-Bing Hu Wen-Hua Chen 《International Journal of Automation and computing》 EI 2005年第1期101-106,共6页
In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computation... In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach. Keywords Model predictive control - linear matrix inequality - stability region - terminal region - feasibility Xiao-Bing Hu received the B.S. degree in Aviation Electronic Engineering at Civil Aviation Institute of China, Tianjin, China, in 1998, the M.S. degree in Automatic Control Engineering at Nanjing University of Aeronautics & Astronautics, Nanjing, China, in 2001, and the Ph.D. degree in Aeronautical and Automotive Engineering at Loughborough University, UK, in 2005.He is currently a Research Fellow in Department of Informatics at Sussex University, UK. His major field of research includes predictive control, artificial intelligence, air traffic management, and flight control. Wen-Hua Chen received his MSc and Ph.D. degrees from Department of Automatic Control at Northeast University, China, in 1989 and 1991, respectively.From 1991 to 1996, he was a Lecturer in Department of Automatic Control at Nanjing University of Aeronautics & Astronautics, China. He held a research position and then a Lectureship in Control Engineering in Center for Systems and Control at University of Glasgow, UK, from 1997 to 2000. He holds a Lectureship in Flight Control Systems in Department of Aeronautical and Automotive Engineering at Loughborough University, UK. He has published one book and more than 60 papers on journals and conferences. His research interests are the development of advanced control strategies and their applications in aerospace engineering. 展开更多
关键词 model predictive control linear matrix inequality stability region terminal region FEASIBILITY
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Min-max fuzzy model predictive tracking control of boiler-turbine system for ultra-supercritical units 被引量:1
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作者 Chen Chen Pan Lei Kwang Y.Lee 《Journal of Southeast University(English Edition)》 EI CAS 2021年第1期42-51,共10页
To improve the control performance of nonlinear ultra-supercritical(USC)thermal power units,an improved min-max fuzzy model predictive tracking control(FMPTC)strategy is proposed.First,a T-S fuzzy model is established... To improve the control performance of nonlinear ultra-supercritical(USC)thermal power units,an improved min-max fuzzy model predictive tracking control(FMPTC)strategy is proposed.First,a T-S fuzzy model is established to approximate the dynamics of the nonlinear boiler-turbine system.Then,based on an extended fuzzy model containing state variables and output variables,a min-max FMPTC is derived for output regulation while ensuring the closed-loop system stability and the inputs in their given constraints.For greater controller design freedom,the developed controller adopts a new state-and output-based objective function.In addition,the observer estimation error is regarded as a bounded disturbance,ensuring the stability of the entire closed-loop control system.Simulation results on a 1000 MW USC boiler-turbine model illustrate the effectiveness of the proposed approach. 展开更多
关键词 ultra-supercritical boiler-turbine system T-S model min-max model predictive control output tracking linear matrix inequality
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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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Predictive current control system of PMSM based on LADRC 被引量:2
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作者 Wang Xiaopeng Zhao Jun +1 位作者 Wang Bohui Li Baomin 《Journal of Southeast University(English Edition)》 EI CAS 2022年第3期227-234,共8页
For a permanent magnet synchronous motor(PMSM)model predictive current control(MPCC)system,when the speed loop adopts proportional-integral(PI)control,speed regulation is easily affected by motor parameters,resulting ... For a permanent magnet synchronous motor(PMSM)model predictive current control(MPCC)system,when the speed loop adopts proportional-integral(PI)control,speed regulation is easily affected by motor parameters,resulting in the inability to balance the system robustness and dynamic performance.A PMSM optimal control strategy combining linear active disturbance rejection control(LADRC)and two-vector MPCC(TV-MPCC)is proposed.Firstly,a mathematical model of a PMSM is presented,and the PMSM TV-MPCC model is developed in the synchronous rotation coordinate system.Secondly,a first-order LADRC controller composed of a linear extended state observer and linear state error feedback is designed to reduce the complexity of parameter tuning while linearly simplifying the traditional active disturbance rejection control(ADRC)structure.Finally,the conventional PI speed regulator in the motor speed control system is replaced by the designed LADRC controller.The simulation results show that the speed control system using LADRC can effectively deal with the changes in motor parameters and has better robustness and dynamic performance than PI control and similar methods.The system has a fast motor speed response,small overshoot,strong anti-interference,and no steady-state error,and the total harmonic distortion is reduced. 展开更多
关键词 permanent magnet synchronous motor(PMSM) two-vector model predictive current control linear active disturbance rejection control speed control system
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MODELING OF NONLINEAR SYSTEMS BY MULTIPLE LINEARIZED MODELS
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作者 袁向阳 施颂椒 《Journal of Shanghai Jiaotong university(Science)》 EI 1999年第2期26-31,共6页
In order to design linear controller for nonlinear systems,a simple but efficient method of modeling a nonlinear system was proposed by means of multiple linearized models at different operating points in the entire r... In order to design linear controller for nonlinear systems,a simple but efficient method of modeling a nonlinear system was proposed by means of multiple linearized models at different operating points in the entire range of the expected changes of the operating points.The original nonlinear system was described by linear combination of these multiple linearized models,with the linear combination parameters being identified on line based on least squares method.Model Predictive Control,an optimization based technique,was used to design the linear controller.A sufficient condition for ensuring the existence of a linear controller for the original nonlinear system was also given.Good performance indicated by two simulated examples confirms the usefulness of the proposed method. 展开更多
关键词 NONlinear system MULTIPLE linearized modelS least SQUARES method model predictive control
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无人驾驶车辆路径跟踪混合控制策略研究 被引量:1
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作者 李兆凯 刘新宁 +2 位作者 彭国轩 孙雪 陈涛 《汽车技术》 CSCD 北大核心 2024年第3期37-46,共10页
针对单一控制算法无法同时满足无人驾驶车辆对路径跟踪精度和控制器求解速度需求的问题,提出一种基于线性二次型调节器(LQR)和模型预测控制(MPC)的混合控制策略。该策略在低速工况下使用线性二次型调节器、在高速工况下使用模型预测控... 针对单一控制算法无法同时满足无人驾驶车辆对路径跟踪精度和控制器求解速度需求的问题,提出一种基于线性二次型调节器(LQR)和模型预测控制(MPC)的混合控制策略。该策略在低速工况下使用线性二次型调节器、在高速工况下使用模型预测控制算法进行路径跟踪控制,在此基础上设计基于有限状态机(FSM)的控制算法切换机制,并通过遗传算法(GA)对控制参数进行优化,基于CarSim和MATLAB/Simulink仿真平台对混合控制策略进行仿真验证,并进一步完成了实车试验。试验结果表明,所设计的混合控制策略能够在提高跟踪精度的基础上缩短计算时间,与单一控制算法相比,平均横向误差和平均航向误差分别减小了26.3%和39.6%,平均计算时间缩短了10.9%。 展开更多
关键词 路径跟踪 线性二次型调节器 模型预测控制 有限状态机 遗传算法
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