双臂空间机器人姿态、关节协调运动基于RBF神经网络的自适应控制算法

讨论了载体位置无控、姿态受控情况下,双臂空间机器人姿态、关节协调运动的控制问题．由Lagrange第二类方法及系统动量守恒关系,建立了漂浮基双臂空间机器人的系统动力学方程．以此为基础,借助于RBF神经网络技术、GL矩阵及其乘积算子定义,对双臂空间机器人系统进行了神经网络系统建模;之后针对双臂空间机器人所有惯性参数均未知的情况,设计了双臂空间机器人载体姿态与机械臂各关节协调运动基于RBF神经网络的自适应控制算法．提出的控制算法不要求系统动力学方程具有惯常的关于惯性参数的线性性质,且无需预知系统惯性参数的任何信息,也无需对神经网络进行离线训练、学习,因此更适于实时应用．一个平面漂浮基双臂空间机器人系统的数值仿真,证实了该控制算法的有效性．     

考虑执行器特性的机械臂全阶滑模控制

针对动力学模型中带有参数未知特性的机械臂位置和速度跟踪问题,提出一种新型的基于神经网络和全阶滑模的控制策略.该策略考虑了执行器的动力学特性,然后基于跟踪误差,建立了全阶滑模面,并利用径向基网络对模型未知特性进行逼近,进而设计鲁棒自适应控制律使得系统状态到达滑模面并沿滑模面收敛到平衡点.理论分析证明了所设计的控制策略可在克服抖振问题的同时保证闭环系统的渐近稳定性.二连杆机械臂系统的数值仿真结果验证了所提出方法的有效性.     

线性滞后广义系统的二阶滑模控制方法

讨论了时滞广义系统在不同条件下的变结构控制,根据终端滑模控制的特点,提出了一种由线性滑模与终端滑模构成的二阶终端滑模及相应控制策略.研究结果表明,该方法能够有效地清除系统的高频抖振,同时保证闭环系统的渐近稳定,实现滑模运动.举例说明了设计的合理性和有效性.     

基于干扰观测器的异构多智能体自适应滑模容错一致性控制

针对线性一阶和二阶异构多智能体系统,考虑到任意智能体可能发生的执行器故障以及受到外部干扰,研究了系统容错一致性控制设计问题.首先设计变增益扰动观测器,快速估计外部干扰;其次,利用一致性误差变量构造自适应积分滑模面,结合干扰观测器的估计值设计自适应滑模容错控制器.当异构多智能体系统存在执行器故障和外部扰动时,自适应滑模控制器可以保证智能体系统的位置和速度状态趋于一致.最后,利用Matlab仿真验证了所提方法的可行性与有效性.     

基于RBF神经网络的鲁棒因子滑模变结构多自由度机械臂精确跟踪控制研究

针对具有时变干扰的不确定多自由度机械臂,文章设计了基于RBF神经网络的含有鲁棒因子的滑模变结构高精度跟踪控制方法.针对时变干扰,设计鲁棒因子,将其嵌入滑模变结构控制器,克服了时变干扰对系统跟踪性能的影响.将RBF神经网络控制算法结合鲁棒因子滑模变结构控制,估计多自由度机械手臂系统的不确定因素.采用Lyapunov函数方法,证明了系统的稳定性.对比分析了计算力矩法滑模变结构控制方法,仿真结果证明,基于RBF神经网络的鲁棒因子滑模控制,针对具有时变干扰的含有不确定因素的多自由度机械手臂系统,具有较为精确的跟踪性能.     

基于组合智能控制的柔性臂微机控制系统研究

针对难以控制的柔性机械臂，设计了强鲁棒性、强自适应能力的模糊滑模控制策略；并针对控制对象与控制算法的复杂性，设计了基于DSP＋FPGA的控制系统，保证了系统的实时性和精确度。     

广义不确定系统的终端滑模控制

本文研究了线性广义不确定系统在满足匹配条件下的终端滑模控制的综合设计问题.利用变结构控制方法设计切换函数和终端滑模控制器,获得了在终端滑模控制下,闭环系统的模态在有限时间内到达平衡点的重要结果.克服了传统的变结构控制方法只能保证闭环系统的模态在平衡点渐近稳定,不能实现有限时间到达平衡点的缺点.举例说明了设计方法的合理性和有效性.     

鲁棒自适应仿生模糊滑模控制

针对一类非线性系统,将生物个体对外界环境的适应对策弓J入滑模控制中,在模糊滑模控制的基础上提出了仿生模糊滑模控制方法.该法利用生物随外界环境变化的主动适应性来设计控制器.在实际问题中往往出现建模误差、外界干扰等不确定因素,为了补偿模糊控制器与理想控制器的误差,增加了一个鲁棒控制器.这样使系统具有更强的鲁棒性和抗扰动性,有效避免抖振和消除误差,达到理想状态.同时,利用Lyapunov稳定性理论,证明了闭环系统的全局稳定性.最后对线性系统和倒立摆系统进行了仿真,结果表明了方法的有效性和可行性.     

鲁棒自适应仿生模糊滑模控制北大核心

针对一类非线性系统,将生物个体对外界环境的适应对策弓J入滑模控制中,在模糊滑模控制的基础上提出了仿生模糊滑模控制方法.该法利用生物随外界环境变化的主动适应性来设计控制器.在实际问题中往往出现建模误差、外界干扰等不确定因素,为了补偿模糊控制器与理想控制器的误差,增加了一个鲁棒控制器.这样使系统具有更强的鲁棒性和抗扰动性,有效避免抖振和消除误差,达到理想状态.同时,利用Lyapunov稳定性理论,证明了闭环系统的全局稳定性.最后对线性系统和倒立摆系统进行了仿真,结果表明了方法的有效性和可行性.     

基于小波分析的空间机械臂运动规划的最优控制

讨论了空间机械臂系统非完整运动规划的最优控制问题.利用小波分析方法,将离散正交小波函数引入最优控制,由小波级数展开式逼近替代传统的Fourier基函数,提出基于小波分析的最优控制数值算法.仿真结果表明,该方法对求解空间机械臂非完整运动规划问题是有效的.     

Fuzzy fractional order sliding mode controller for nonlinear systems

In this paper, an intelligent robust fractional surface sliding mode control for a nonlinear system is studied. At first a sliding PD surface is designed and then, a fractional form of these networks PD^α, is proposed. Fast reaching velocity into the switching hyperplane in the hitting phase and little chattering phenomena in the sliding phase is desired. To reduce the chattering phenomenon in sliding mode control (SMC), a fuzzy logic controller is used to replace the discontinuity in the signum function at the reaching phase in the sliding mode control. For the problem of determining and optimizing the parameters of fuzzy sliding mode controller (FSMC), genetic algorithm (GA) is used. Finally, the performance and the significance of the controlled system two case studies (robot manipulator and coupled tanks) are investigated under variation in system parameters and also in presence of an external disturbance. The simulation results signify performance of genetic-based fuzzy fractional sliding mode controller.     

Nonlinear and chaos control of a micro-electro-mechanical system by using second-order fast terminal sliding mode control

In this paper, a novel second-order fast terminal sliding mode control (SFTSMC) scheme is proposed to suppress the chaotic motion of a micro-mechanical resonator with system uncertainty and external disturbance. To obtain a better disturbance rejection property, a fuzzy logic system is introduced to estimate the upper boundary of the sum of system uncertainty and external disturbance. Moreover, we employ the finite-time technique to obtain the properties of fast response and high precision. Finally, numerical simulations demonstrate the effectiveness of the proposed control scheme.     

Disturbance-observer-based fuzzy terminal sliding mode control for MIMO uncertain nonlinear systems

This study is concerned with the design of a disturbance-observer-based fuzzy terminal sliding mode controller (FTSMC) for multi-input multi-output (MIMO) uncertain nonlinear systems by considering unknown non-symmetric input saturation and control singularity. The disturbance observer is proposed for the unmeasured external disturbance and guarantees the convergence of the disturbance estimation error to zero in a finite time. The terminal sliding mode controller (TSMC) is designed for MIMO uncertain nonlinear systems by utilizing the output of the proposed disturbance observer. This control scheme combines the disturbance-observer-based TSMC with a fuzzy logic system in the presence of unknown non-symmetric input saturation and control singularity in order to reduce chattering phenomena. Finite time asymptotic stability, convergence of the disturbance observer, and convergence of the closed-loop system are proved via Lyapunov stability theorem. In addition, a five-rotor unmanned aerial vehicle (UAV) is employed in the numerical simulations to demonstrate the effectiveness and performance of the proposed control scheme. Disturbance observer estimates the payload and flight endurance of the five-rotor UAV. Genetic algorithm (GA) optimization is used to specify the parameters of the disturbance-observer-based TSMC (GATSMC) to decrease chattering. Finally, the superior performance of FTSMC is investigated over TSMC and GATSMC.     

Chaos control of uncertain time‐delay chaotic systems with input dead‐zone nonlinearity

This article presents an adaptive sliding mode control (SMC) scheme for the stabilization problem of uncertain time‐delay chaotic systems with input dead‐zone nonlinearity. The algorithm is based on SMC, adaptive control, and linear matrix inequality technique. Using Lyapunov stability theorem, the proposed control scheme guarantees the stability of overall closed‐loop uncertain time‐delay chaotic system with input dead‐zone nonlinearity. It is shown that the state trajectories converge to zero asymptotically in the presence of input dead‐zone nonlinearity, time‐delays, nonlinear real‐valued functions, parameter uncertainties, and external disturbances simultaneously. The selection of sliding surface and the design of control law are two important issues, which have been addressed. Moreover, the knowledge of upper bound of uncertainties is not required. The reaching phase and chattering phenomenon are eliminated. Simulation results demonstrate the effectiveness and robustness of the proposed scheme. © 2014 Wiley Periodicals, Inc. Complexity 21: 13–20, 2016     

Anti-synchronization of uncertain unified chaotic systems with dead-zone nonlinearity

This paper addresses chaos anti-synchronization of uncertain unified chaotic systems with dead-zone input nonlinearity. Using the sliding mode control technique and Lyapunov stability theory, a proportional–integral (PI) switching surface is proposed to ensure the stability of the closed-loop error system in sliding mode. Then a sliding mode controller (SMC) is proposed to guarantee the hitting of the switching surface even with uncertainties and the control input containing dead-zone nonlinearity. Some simulation results are included to demonstrate the effectiveness and feasibility of the proposed synchronization scheme.     

Design of LMI‐based sliding mode controller with an exponential policy for a class of underactuated systems

In this article, a novel sliding mode control (SMC) approach is proposed for the control of a class of underactuated systems which are featured as in cascaded form with external disturbances. The asymptotic stability conditions on the error dynamical system are expressed in the form of linear matrix inequalities. The control objective is to construct a controller such that would force the state trajectories to approach the sliding surface with an exponential policy. The proposed SMC has a simple structure because it is derived from the associated first‐order differential equation and is capable of handling system disturbances and nonlinearities. The effectiveness of the proposed control method is validated using intensive simulations. © 2014 Wiley Periodicals, Inc. Complexity 21: 117–124, 2016     

Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua’s chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system.     

Optimal sliding mode control for nonlinear systems with time-delay

This paper is concerned with the sliding mode control (SMC) for a class of nonlinear systems with time-delay. A novel optimal sliding mode is proposed by using the successive approximation approach (SAA). The stability of the nonlinear sliding mode is analyzed. The switching manifold ensures that the state trajectories of the closed-loop system converge to zero in an optimal fashion on the ideal sliding surface. Furthermore, the convergence velocity of every state trajectory on the ideal sliding surface can be adjusted through choosing the parameters of the quadratic performance index. A numerical simulation is given to show the effectiveness of the proposed design approach.     

Design of adaptive sliding mode control for synchronization Genesio–Tesi chaotic system

In this paper two adaptive sliding mode controls for synchronizing the state trajectories of the Genesio–Tesi system with unknown parameters and external disturbance are proposed. A switching surface is introduced and based on this switching surface, two adaptive sliding mode control schemes are presented to guarantee the occurrence of the sliding motion. The stability and robustness of the two proposed schemes are proved using Lyapunov stability theory. The effectiveness of our introduced schemes is provided by numerical simulations.