Optimal Control of Nonlinear Inverted Pendulum System Using PID Controller and LQR: Performance Analysis Without and With Disturbance Input

Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical system. LQR is one of the optimal control techniques, which takes into account the states of the dynamical system and control input to make the optimal control decisions.The nonlinear system states are fed to LQR which is designed using a linear state-space model. This is simple as well as robust. The inverted pendulum, a highly nonlinear unstable system, is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches a desired position and the inverted pendulum stabilizes in the upright position. In this paper, the modeling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using PID controller and LQR have been presented for both cases of without and with disturbance input. The Matlab-Simulink models have been developed for simulation and performance analysis of the control schemes. The simulation results justify the comparative advantage of LQR control method.     

二级倒立摆系统的实时稳定控制实验研究

为实现二级倒立摆系统的实时稳定控制,以深圳固高直线二级倒立摆装置作为控制对象,在MATLAB环境下,利用基于二次型最优控制理论的线性二次型(Linear Quadratic Regulator,LQR)最优控制器,成功实现了该装置的实时稳定控制。为引入新的控制策略,采集二级倒立摆实时控制过程中的LQR控制器数据作为样本,经过自适应神经模糊推理系统(Adaptive Neuro-Fuzzy Inference System,ANFIS)工具箱训练并生成出一种新型模糊神经网络控制器,应用到装置上同样实现了实时平衡。结果表明,新型控制器较LQR控制器控制效果更优,也为成功实现装置的实时平衡提供了一种新的思路和解决方法。     

平面倒立摆建模与最优控制算法的研究

倒立摆系统是一个多变量、非线性、高阶次、强耦合、欠驱动的自然不稳定系统,是自动控制理论教学和研究中典型的物理模型。本文以平面倒立摆系统为研究对象,使用拉格朗日方程建立了多级平面倒立摆的数学模型。采用线性二次最优控制算法,分别设计了LQR及LQR-模糊控制器,实现平面多级倒立摆的平衡控制,结论证明了本文设计的LQR控制器有很好的稳定性、鲁棒性和适应性。     

三级倒立摆的自动摆起与稳定控制

采用非线性逆系统轨迹控制实现三级倒立摆的自动摆起,并设计了变增益LQR控制器将其稳定在竖直倒立位置.首先,三级倒立摆从静止下垂状态摆起到竖直倒立位置的过程,从数学角度看是一个两点边值问题,通过求解该两点边值问题获得摆起的标称轨迹,利用逆系统方法设计前馈控制,同时结合增益调度反馈控制使摆起过程稳定;其次,在稳定控制阶段,...     

基于无迹卡尔曼滤波的旋转倒立摆LQR控制

LQR控制器在含有系统噪声与量测噪声的旋转倒立摆系统应用中,难以获得精确的状态向量实现对系统的最优控制.为了提高LQR的控制精度,引入了无迹卡尔曼滤波(UKF)状态观测器,以获得系统的最优状态估计量,实现基于动态规划的自抗扰二次型最优反馈控策略.与卡尔曼滤波(KF)相比,UKF用于非线性系统的状态估计的主要优势是不需要线性化去计算状态转移矩阵,避免了系统线性化带来的模型误差.在含有系统噪声与量测噪声的旋转倒立摆仿真模型下,对基于KF和UKF的LQR控制器进行了仿真对比分析.仿真结果表明,UKF对系统响应时间、控制精度、鲁棒性的优化效果更好.     

Design of optimized fuzzy cascade controllers by means of Hierarchical Fair Competition-based Genetic Algorithms

In this study, we present a design of an optimized fuzzy cascade controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for a rotary inverted pendulum system. In this system, one controls the movement of a pendulum through the adjustment of a rotating arm. The objective is to control the position of the rotating arm and to make the pendulum maintain the unstable equilibrium point at vertical position. To control the system, we design a fuzzy cascade controller scheme which consists of two fuzzy controllers arrange in a cascaded topology. The parameters of the controller are optimized by means of the HFCGA algorithm. The fuzzy cascade scheme comprises two controllers located in two loops. An inner loop controller governs the position of the rotating arm while an outer controller modifies a set point of the inner controller implied by the changes of the angle of pendulum. The HFCGA being a computationally effective scheme of the Parallel Genetic Algorithm (PGA) has been developed to eliminate an effect of premature convergence encountered in Serial Genetic Algorithms (SGA). It has emerged as an effective optimization vehicle to deal with very large search spaces. A comparative analysis involving computing simulations and practical experiment demonstrates that the proposed HFCGA based fuzzy cascade controller comes with superb performance in comparison with the conventional Linear Quadratic Regulator (LQR) controller as well as HFCGA-based PD cascade controller.     

Zero dynamics stabilisation and adaptive trajectory tracking for WIP vehicles through feedback linearisation and LQR technique

This paper presents a composite control strategy integrating adaptive sliding-mode control and the linear quadratic regulator (LQR) technology for a wheeled inverted pendulum (WIP) vehicle system. The system can be partitioned into an actuated rotational subsystem and an underactuated longitudinal subsystem based on the different control input in the mathematical model. In particular, the instability analysis of zero dynamic for the underactuated longitudinal subsystem is investigated in detail using the feedback linearisation technology. Then, an adaptive sliding-mode control is designed for the trajectory tracking, where an adaptive algorithm is developed to handle with the parameter uncertainties. In addition, the LQR technique is employed to guarantee zero dynamics stability so as to achieve simultaneously the vehicle body stabilisation at the upright position. Simulation results show the good performance and strong robustness of the proposed control schemes.     

A Robotic Walker Based on a Two-Wheeled Inverted Pendulum

This paper presents the design and control of a robotic walker based on a two-wheeled inverted pendulum (TWIP) developed to assist mobility-impaired users with balance and stability. Traditional walkers use three or more contact points to create a solid base to augment a user’s balance. A TWIP walker can support a user’s balance through balance control. A robotic walker prototype has been developed to illustrate its ability to assist human gait and exploit the maneuverability of a two-wheeled mobile platform compared to multi-wheeled system. Presented is a linearized mathematical model of the two-wheeled system using Newtonian mechanics. A control strategy consisting of a decoupled linear quadratic regulator (LQR) controller and two state variable controllers is developed to stabilize the platform and regulate its behavior with robust disturbance rejection performance. Results are shown using a physical prototype to demonstrate the ability of the decoupled LQR controller to robustly balance the platform while the state variable controllers regulate the platform’s position with smooth, minimum jerk, control when used by a person during standing and walking.     

基于LQR的直线一阶单倒立摆最优控制器的设计

对已有的LQR最优控制中系统的动态响应与加权矩阵Q和R之间遵循的基本规律进行分析,并根据这一基本规律对给定的直线一阶单倒立摆采用线性二次型最优控制的方法设计控制器。仿真结果表明,基于LQR的最优控制系统对直线一阶单倒立摆具有很好的控制效果。     

环型二级倒立摆的控制研究与实现

通过分析环型二级倒立摆系统的动力学特性,将系统的状态空间方程在“倒立”的 平衡点附近进行线性化处理,应用线性二次型最优控制策略,对环型二级倒立摆进行控制器 的设计与仿真实验,并成功地将所设计的控制器应用到实际的环型二级倒立摆系统上,使其 稳定地平衡在“倒立”状态．所做应用与实际实验在国内尚未见到报道．     

环形一级倒立摆摆起及稳定控制研究

本文通过拉格朗日方程推导出环形一级倒立摆系统的数学模型,用能量方法对该模型进行摆起控制;在倒立摆成功摆起后,在倒立平衡点对系统模型进行线性化,并用线性二次型最优控制(LQR)算法对倒立摆线性化模型进行稳定控制。仿真结果表明本文给出的控制方法是有效的。     

单级旋转倒立摆的控制系统设计

介绍单级旋转倒立摆的控制系统设计.系统采用LQR算法控制旋转臂和摆杆位置,验证了小角度内平衡点附近线性化的合理性,结构简单且控制快速,具有良好的稳定性和鲁棒性.     

Robust Control Design of Wheeled Inverted Pendulum Assistant Robot

This paper examines the design concept and mobile control strategy of the human assistant robot I-PENTAR (inverted pendulum type assistant robot). The motion equation is derived considering the non-holonomic constraint of the twowheeled mobile robot. Different optimal control approaches are applied to a linearized model of I-PENTAR. These include linear quadratic regulator (LQR), linear quadratic Gaussian control (LQG), H₂ control and H_∞ control. Simulation is performed for all the approaches yielding good performance results.      

平面两级倒立摆的分析、控制器设计与实现

对基于XY平台的平面两级倒立摆进行了运动学和动力学分析，由于系统具有很强的非线性以及耦合等特性，需要在其平衡点附近线性化，以得到系统的近似线性状态方程。然后分析了系统的可控性，并根据状态方程采用线性二次最优控制LQR方法设计控制器。仿真结果说明，倒立摆系统可以得到很好的稳定效果。最后进行了多次实验，倒立摆都可以稳定很长时间，而且可以施加一定的干扰，具有较好的鲁棒性。实验结果说明，此方法是有效可行的。     

Exponential stabilization of discrete-time switched linear systems

This article studies the exponential stabilization problem for discrete-time switched linear systems based on a control-Lyapunov function approach. It is proved that a switched linear system is exponentially stabilizable if and only if there exists a piecewise quadratic control-Lyapunov function. Such a converse control-Lyapunov function theorem justifies many of the earlier synthesis methods that have adopted piecewise quadratic Lyapunov functions for convenience or heuristic reasons. In addition, it is also proved that if a switched linear system is exponentially stabilizable, then it must be stabilizable by a stationary suboptimal policy of a related switched linear-quadratic regulator (LQR) problem. Motivated by some recent results of the switched LQR problem, an efficient algorithm is proposed, which is guaranteed to yield a control-Lyapunov function and a stabilizing policy whenever the system is exponentially stabilizable.     

二级倒立摆的半物理仿真模型研究与实现

本文在MATLAB环境下建立了二级倒立摆的半物理实时仿真模型，并应用线性二次型最优控制策略．设计了一个二级倒立摆LQR控制器。在实验中，运行该半实物仿真模型，成功的使倒立摆稳定地平衡在“倒立”状态。     

基于能量反馈的圆轨倒立摆摆起控制

基于拉格朗日方程建立圆轨倒立摆单摆模型,根据能量反馈控制理论,设计圆轨倒立摆摆起控制器,从而使摆杆从稳定平衡点摆起到不稳定平衡点并稳定不倒。采用具有流水线指令结构CIP-51控制器内核的C8051单片机实现控制算法。实验结果表明,采用能量反馈控制器可以对具有复杂非线性、强耦合、自然不稳定特性的倒立摆系统实现摆起控制,摆起效果良好。同时也为其他非线性多变量系统的控制提供了有效方法。     

基于Lagrange方程建模的旋转倒立摆的分析与控制

本文通过对旋转倒立摆的动力学特性分析建立了基于Lagrange方程的数学模型，然后应用线性二次型最优控制策略设计控制器，最后在Windows2000平台下控制旋转倒立摆稳定在倒立状态。     

旋转二级倒立摆的二次型最优控制研究

针对多变量、非线性和强耦合的旋转二级倒立摆系统,采用分析力学理论分析旋转二级倒立摆系统的结构,建立了旋转二级倒立摆系统的数学模型状态空间方程,分析了系统的稳定性和可控性.将系统的状态空间方程在平衡点附近进行线性化处理,分别采用线性二次型最优控制策略LQR及LQY方法对旋转二级倒立摆系统进行控制系统设计,并借助Matlab平台进行了仿真实验研究.对控制结果进行了详细分析研究,对于实现其他不稳定系统的控制,有着一定的借鉴价值.     

非线性倒立摆系统的起摆和稳摆控制

介绍了基于数字信号处理器(DSP)控制直线型倒立摆系统的总体结构和工作原理,通过智能控制算法实现倒立摆的起摆控制。当摆杆的角度进入稳定区域时,通过线性二次型调节器(LQR)控制算法使摆杆稳定,并建立了电机电压与输出力矩之间的简单对应关系。实验表明,系统的稳定性好,抗干扰力强,而且采用DSP控制,有利于系统的小型化。