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分流模型PID与鲁棒补偿的复合控制策略 被引量:1

Composite Control Strategy Based on Shunting Model PID and Robust Compensative Controller
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摘要 提出了一种基于分流模型PID与鲁棒补偿的复合控制策略,这种控制器具有非线性滤波、增益自调整、鲁棒性好等优良特性。由于分流模型的输出是稳定、光滑且有界,可以构造一类具有输出光滑、有界并且增益自调整的PID控制器,其可设计一类安全控制系统。将分流模型PID与鲁棒补偿控制相结合,有效地解决了参数不确定情况下的一类非线性系统的鲁棒控制问题。通过倒立摆控制系统的仿真研究,验证了控制策略的有效性。 A novel composite control strategy based on a shunting model PID and a compensative controller was developed for a class of nonlinear systems. The proposed controller has some excellent characteristics, such as nonlinear filtering, gain auto-regulation and robustness, Because the output of shunting model is stable, bounded and smooth, it is used to construct the PID controller with bounded and smoothed output and gain auto-regulation, This kind of controller can be employed in designing a class of safe control systems, The shunting model based PID controller is integrated with a robust compensative controller so that it could effectively solve the robust control problem for a class of nonlinear systems with parametric uncertainty, By the simulation study of an inverted pendulum control, the effectiveness of the proposed control strategy is demonstrated.
出处 《系统仿真学报》 EI CAS CSCD 北大核心 2006年第3期706-709,721,共5页 Journal of System Simulation
基金 浙江省自然科学基金资助项目(Y104560) 浙江省留学回国基金资助项目
关键词 分流模型 PID控制器 鲁棒补偿 复合控制 倒立摆 shunting model PID controller robust compensation composite control strategy inverted pendulum,
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参考文献10

  • 1W.-D. Chang, R.-C. Hwang, J.-G. Hsieh. A self-tuning PID control for a class of nonlinear systems based on the Lyapunov approach[J].Journal of Process Control(S0959-1524), 2002, 12(2): 233-242.
  • 2J. Carvajal, G. Chen, H. Ogmen. Fuzzy PID controller: Design,evaluation, and stability analysis[J]. Information Sciences(S0020-0255), 2000, 123(3-4): 249-270.
  • 3A. L. Hodgkin, A. F. Huxley. A quantitative description of membrane current and its application to conduction and excitation in nerve[J]. J.Phys. Lond(S0022-3751)., 1952, 117: 500-544.
  • 4S. Grossberg. Nonlinear neural networks: Principles, mechanism, and architectures[J]. Neural Networks(S0893-6080), 1988, 1(1): 17-61.
  • 5S. Grossberg. Absolute stability of global pattern formation and parallel memory storage by compective neural networks[J]. IEEE Trans. Syst., Man, Cybem. (S0018-9472), 1983, 13: 815-926.
  • 6S. X. Yang, M. Meng. An efficinet neural network approach to dynamic robot motion planning[J]. Neural Networks(S0893-6080),2000, 13(2): 143-148.
  • 7S. X. Yang, M. Meng. Neural network approches to dynamic collision-free trajectory generation[J]. IEEE Transactions on Systems,Man, and Cybernetics, Part B(S 1083-4419), 2001,31 (3): 302-318.
  • 8S. X. Yang, C. Luo. A Neural Network Approach to Complete Coverage Path Planning[J]. IEEE Transactions on Systems, Man and Cybernetics, part B(S 1083-4419), 2004, 34(1):718-724.
  • 9X. Yuan, S. X. Yang. Virtual assembly with biologically inspired intelligence[J]. IEEE Transactions on Systems, Man, and Cybernetics,Part C(S 1094-6977). 2003, 33(2): 159-167.
  • 10S. X. Yang, M. Meng. An efficinet neural network method for real-time motion planning with safety consideration[J]. Robotics and Autonomous Systems(S0921-8890), 2000,32(23): 115-128.

同被引文献11

  • 1陈龙,陈建军,张雪峰.不确定结构振动的保成本鲁棒PID控制[J].振动与冲击,2007,26(6):79-81. 被引量:6
  • 2Balas M J. Direct velocity feedback control of large space structures [ J ]. Journal of Guidance and Control, 1979,2 (5) : 252 - 253.
  • 3Goh C, Caughey T K. On the stability problem caused by itffinite actuator dynamics in the collocated control of large space structure [ J]. International Journal of Control, 1985, 41(3) :787 -802.
  • 4Han J H Rew K H, Lee I. An experimental study of active vibration control of composite structures with a piezoce-ramic actuator and a piezofilm sensor [ J ]. Smart Materials and Structures, 1998, 6(5) : 549 -558.
  • 5Trajkov T N, Koppe H, Gabbert U. Direct model reference adaptive control (MRAC) design and simulation for the vibration suppression of piezoelectric smart structures [ J ]. Communications in Nonlinear Science and Numerical Simulation, 2008,13 : 1896 - 1909.
  • 6Yang K J, Hong K S, Matsuno F. Robust adaptive control of a cantilevered flexible structure with spatiotemporally varing coefficients and bounded disturbance [ J ]. JSME International Journal,2003,47 (3) : 812 - 821.
  • 7Duanl G R , Liu W Q, Liu G P. Robust model reference control for multivariable linear systems subject to parameter uncertainties [ J ]. Journal of Systems and Control Engineering, 2001,215 (16) :599 - 610.
  • 8Jha R S, He C L. Neural-network-based adaptive predictive control for vibration suppression of smart structures [ J ]. Smart Materials and Structures, 2002,11 (6) :909 - 916.
  • 9Guyomar D, Badel A, Lefeuvre E, et al. Toward energy harvesting using active materials and conversion improvement by nonlinear processing [ J ]. IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2005, 52(4) : 584 -595.
  • 10Gu H C, Song G B. Active vibration suppre-ssion of a flexible beam with piezoceramic patches using robust model reference control[ J ]. Smart Materials and Structures, 2007, 16 (4) : 1453 - 1459.

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