2D Model-Following Servo System

This paper gives, in view of the feature of practical 2D (2-dimensional) systems, a formulation of the 2D model-following servo problem for the case where one of the independent variables of the considered 2D systems is unbounded and the other one is bounded. That is, to determine a control input such that the outputs of a given 2D plant asymptotically track, with tracking error as small as possible, the (step) response of a given 2D model system as the unbounded variable approaches infinite. It is shown that this problem under a specified quadratic performance index can be transformed into a 1D LQR problem, and thus can be solved by the well-known 1D approaches. The relation between the solvability condition obtained for the equivalent 1D LQR problem and the practical stabilizability and detectability of the original 2D plant is clarified. Its application to the design of non-unit memory linear multipass processes is also shown. Finally, a numerical example for metal rolling process is given to verify the effectiveness.     

Active TLCGD control of plane asymmetric buildings under earthquake excitation

The sealed,tuned liquid column gas damper (TLCGD) with gas-spring effect extends the frequency range of application and efficiently increases the modal structural damping.Active tuned liquid column gas damper (ATLCGD) is developed for the vibration control of plane asymmetric buildings subjected to earthquake excitation,improving the performance of the passive control scheme.The active behaviour is obtained by adjusting the pressure at the end of the liquid column using a pressurised reservoir.The classical linear quadratic regulator (LQR) design is presented as a straightforward approach to optimal control.Numerical simulations indicate a significant vibration reduction of plane asymmetric buildings by active control within the strong motion of the dynamic response.     

基于视觉的AGV两轮差速转向最优控制研究

简要地介绍了基于机器视觉导向的AGV两轮差速转向的原理和组成,并对计算机控制系统设计,图像信息识别等AGV控制问题进行了阐述.提出了一种采用最优控制方法对两轮差速转向进行控制.仿真和实验结果表明,采用最优控制方法对两轮差速转向进行控制,样车运行过程稳定,路径跟踪可靠,控制性能良好.     

Non-probabilistic reliability method and reliability-based optimal LQR design for vibration control of structures with uncertain-but-bounded parameters

Uncertainty is inherent and unavoidable in almost all engineering systems. It is of essential significance to deal with uncertainties by means of reliability approach and to achieve a reasonable balance between reliability against uncertainties and system performance in the control design of uncertain systems. Nevertheless, reliability methods which can be used directly for analysis and synthesis of active control of structures in the presence of uncertainties remain to be developed, especially in non-probabilistic uncertainty situations. In the present paper, the issue of vibration con- trol of uncertain structures using linear quadratic regulator （LQR） approach is studied from the viewpoint of reliabil- ity. An efficient non-probabilistic robust reliability method for LQR-based static output feedback robust control of un- certain structures is presented by treating bounded uncertain parameters as interval variables. The optimal vibration con- troller design for uncertain structures is carried out by solv- ing a robust reliability-based optimization problem with the objective to minimize the quadratic performance index. The controller obtained may possess optimum performance un- der the condition that the controlled structure is robustly re- liable with respect to admissible uncertainties. The proposed method provides an essential basis for achieving a balance between robustness and performance in controller design ot uncertain structures. The presented formulations are in the framework of linear matrix inequality and can be carried out conveniently. Two numerical examples are provided to illustrate the effectiveness and feasibility of the present method.     

Study of the open and closed loop characteristics of a tractor and a single axle towed implement system

Accurate automatic guidance of towed implements is important for performing agricultural field operations and for gaining the ultimate benefit from such systems. The study of open and closed loop system responses of a vehicle-implement system can be helpful in the design of practical guidance controllers. Open loop analysis of the kinematic and dynamic models revealed that the higher order dynamics captured by the tractor and implement dynamic model had an impact on simulated responses at higher operating velocities and on higher input frequencies. In addition, a dynamic model with tire relaxation length dynamics was also studied. The various model responses were compared with the experimental responses. Closed loop system characteristics were studied by using a linear quadratic regulator (LQR) controller. The tractor position and heading and implement heading states along with respective rate states were fed back to close the loop. Steering dynamics were also added to the dynamic model closed loop analysis, which helped to achieve a realistic closed loop steering angle history. The closed loop system dynamics became faster as the forward velocity was increased. The open and closed loop response analysis performed in this work provided an understanding about the system at various forward velocities, which will help to design and develop efficient and robust tractor and towed implement guidance controller.     

基于粒子群优化的导弹分数阶控制器设计

针对传统控制方法控制品质易受气动参数变化影响的问题,结合分数阶微积分理论和LQR最优控制技术,设计了改进的导弹分数阶控制器。首先对于导弹动力学模型进行状态重组,应用LQR技术采用输出反馈,得到基于导弹最优跟踪指标的三回路控制结构,进而构建了广义分数阶控制器结构。为优化控制器参数选择,提出一种综合频域和时域性能的适应值函数,通过粒子群(PSO)算法整定控制器参数。仿真结果表明分数阶控制器具有良好的稳态、动态特性性能。     

LQR最优控制器在精馏塔上的应用

本文将ＬＱＲ（Ｌｉｎｅａｒｑｕａｄｒａｔｉｃ　ｒｅｇｕｌａｔｏｒ）最优控制的理论研究成果应用到精馏塔上,设计了精馏塔的线性二次型最优控制器,并针控制结果与常规ＰＩＤ控制器控制结果进行了比较。仿真证明,在动态变化过程中,ＬＱＲ控制器确实能使目标函数得到代化。     

单级倒立摆LQR控制仿真

倒立摆是不稳定,非线性,强耦合系统,本文应用现代控制理论最优控制LQR方法对单级倒立摆系统进行仿真控制研究,仿真结果说明反馈控制理论对倒立摆系统的控制是有效的。     

LQR based improved discrete PID controller design via optimum selection of weighting matrices using fractional order integral performance index

The continuous and discrete time Linear Quadratic Regulator (LQR) theory has been used in this paper for the design of optimal analog and discrete PID controllers respectively. The PID controller gains are formulated as the optimal state-feedback gains, corresponding to the standard quadratic cost function involving the state variables and the controller effort. A real coded Genetic Algorithm (GA) has been used next to optimally find out the weighting matrices, associated with the respective optimal state-feedback regulator design while minimizing another time domain integral performance index, comprising of a weighted sum of Integral of Time multiplied Squared Error (ITSE) and the controller effort. The proposed methodology is extended for a new kind of fractional order (FO) integral performance indices. The impact of fractional order (as any arbitrary real order) cost function on the LQR tuned PID control loops is highlighted in the present work, along with the achievable cost of control. Guidelines for the choice of integral order of the performance index are given depending on the characteristics of the process, to be controlled.