输入受限无人帆船自适应航向跟踪控制

针对带有输入受限且存在未知控制系数约束情形下,考虑了具有未知模型和风、浪等外界干扰的无人船航向跟踪控制问题,提出一种受限控制输入约束下的跟踪控制方法。该方法运用RBF神经网络对未知模型进行在线逼近,利用Nussbaum自适应增益技术解决未知控制系数问题。根据滑模控制理论,设计具有指数趋近律的鲁棒控制项,保证所得误差闭环系统快速响应且最终趋向0。为弱化传统滑模控制产生的抖振问题,将符号函数替换成饱和函数使控制输入变得平滑。引入一种误差辅助系统,构建了帮助误差闭环系统输入退出饱和机制。通过李雅普诺夫稳定性理论,给出了跟踪控制方法的稳定性数学分析过程,证明误差闭环跟踪控制系统的所有信号最终一致有界性。最后通过仿真结果验证了所得理论的有效性。     

基于干扰误差补偿的自动化电机自适应滑模反演控制

针对自动化电机受电磁干扰误差较大,导致电机控制效果较差、难以反映真实运行状态的问题,提出基于干扰误差补偿的自动化电机自适应滑模反演控制方法。构建电机的转子动力学模型,设计干扰观测器,将干扰预测输出值传输至增益调整模块,构建非线性干扰预测动态方程,将预测的干扰因素转化为相应控制量。电机的连续控制问题即跟踪控制问题,按照滑模反演控制理论,定义电机的两个子误差,引入滑模切换函数,构建转子动力学惯性逆矩阵获取控制力矩,通过跟踪转子输出轴完成电机自适应滑模反演控制。实验结果表明,所提方法能够较好地跟踪实际干扰信号变化轨迹,对自动化电机的控制性能较好。     

含齿隙伺服系统的反步自适应模糊滑模控制

针对具有齿隙非线性和参数摄动的某机械传动回转位置伺服系统,提出一种基于反演法的自适应模糊滑模控制策略。首先,在两质量系统中,引入近似死区模型,建立含齿隙的系统动力学模型。然后,通过反演法逐步选择Lyapunov函数,结合滑模控制补偿系统中的参数不确定和齿隙非线性。通过模糊推理机制将不连续切换项线性处理,消除传统滑模控制中的抖振现象。对比试验表明,基于反演法的自适应模糊滑模控制较PID控制更能有效削弱大、小齿轮间传递力矩的波动,并具有更高的位置跟踪精度和对系统参数变化的鲁棒性。     

优化的精度控制自适应调节方案

针对非线性不确定系统,研究并优化了基于输入信号参考自适应PID控制方法——在模型参考自适应PID控制的基础上以输入信号为参考代替模型参考对系统进行控制。控制方法是基于李雅普诺夫平衡点稳定定理控制方法的系统稳定性推演的,由于控制方法中引入稳定项后使控制过程带来微分项,控制方法中加入滤波器,通过系统的自适应调节最终使系统趋于稳定状态。同时,在控制中加入PID因子使系统的控制性能趋佳。该方法是基于输入信号为参考的自适应控制,减少了模型参考带来的误差。仿真推演结果显示,被控对象可以有较强的适应能力,趋于实现更优的过程控制效果。文中给出了运用于海洋钻井设备运动补偿装置实例的分析。     

车辆主动悬架自适应模糊滑模控制研究

针对主动悬架系统具有的非线性和不确定性,结合滑模控制的鲁棒性和模糊控制的优势,建立自适应模糊滑模控制策略。确定滑模切换面参数,应用切换控制方法和函数逼近技术改善滑模运动的动态品质,并利用模糊语言达到控制悬架振动的效果。以车辆1/4主动悬架动力学模型为对象进行仿真,结果显示,与传统的模糊控制相比,自适应模糊滑模控制能有效地改善路面变化对悬架的影响。     

下肢康复机器人模糊增益自适应调整的滑模阻抗控制

为了实现下肢康复机器人在康复训练过程中主动模式下的控制,在分析了人机交互作用力与动力学模型的基础上,提出了一种模糊增益自适应调整的滑模阻抗控制。该控制方法,通过阻抗控制器修正期望的下肢运动轨迹,得到新的关节运动轨迹,将新的关节轨迹与实际的关节轨迹误差转化为滑模函数,通过模糊化,将自适应力矩作用于下肢康复机器人。该控制方法减轻了滑模控制中的抖振现象,使其达到期望的力矩控制效果,实现了主动模式下的的柔顺性。     

虚拟轴机床伺服系统的模糊滑模自适应控制

提出了一种将模糊控制、滑模控制与自适应控制三者有机的整合的模糊滑模自适应控制的算法,并以虚拟轴机床的单通道的阀控非对称液压缸作为研究的对象。仿真实验表明,该算法可以使得系统输出渐进地收敛于参考的输入信号,且可以很快地对变化的信号进行有效地跟踪,对参数的摄动与有界的干扰具有不变性。提出的方法与传统的PID控制比较,更加的适用于较强的干扰的复杂系统、高阶的非线性,将方法应用于虚拟轴机床的液压的控制系统可以获得较高的控制精度、较好的机床动态性能与较小的稳态误差。     

复合式高速直升机过渡模式控制器设计

以复合式高速直升机为研究对象,建立整机气动模型.针对复合式高速直升机过渡模式中存在强非线性、控制输入转移的问题,提出一种基于操稳性和推进功率最优的控制分配方法,设计过渡模式自适应PID控制器,进行仿真验证.仿真结果表明:该控制器可以有效保证复合式高速直升机过渡模式的安全性和平稳性.     

3-UPS/PU并联机构动力学建模及自适应滑模控制

为减少动力学模型不确定性(包括参数不确定和未知的负载干扰)对3-UPS/PU并联机构控制精度的影响,提出一种自适应滑模控制。首先在运动学反解基础上采用虚功原理建立该机构关于动平台工作空间的动力学模型。控制器结合了动力学名义模型和滑模控制理论,利用滑模面设计的自适应律可以对不确定性进行在线估计并补偿,从而提高系统鲁棒性。通过Lyapunov函数分析了系统稳定性。该控制器优点是:无需依赖不确定性上界,结构简单,易于工程应用,适用于并联机构这类复杂不确定系统。仿真结果显示,所采取的控制器能有效克服时变的模型不确定性,使动平台各自由度的平均跟踪误差相比传统滑模控制明显减少。     

汽车主动悬架自适应模糊PID控制研究

为改善汽车行驶平顺性,建立了简化的1/4车二自由度汽车主动悬架模型,提出了主动悬架自适应模糊PID控制方法。该方法中PID控制器以车身垂直速度的误差为控制参量,将车身垂直速度误差及误差变化率作为模糊控制器的输入变量,对PID控制器参数进行在线自调整。以C级路面白噪声随机信号为输入,利用MATLAB/Simulink对自适应模糊PID控制器进行了仿真,结果表明:自适应模糊PID在车身垂直速度、加速度及轮胎动载荷等控制方面明显优于被动悬架及传统PID控制,说明该法具有较好的控制效果和鲁棒性。     

Sliding mode control with PID sliding surface and experimental application to an electromechanical plant

In this study, a sliding mode control system with a proportional+integral+derivative (PID) sliding surface is adopted to control the speed of an electromechanical plant. A robust sliding mode controller is derived so that the actual trajectory tracks the desired trajectory despite uncertainty, nonlinear dynamics, and external disturbances. The proposed sliding mode controller is chosen to ensure the stability of overall dynamics during the reaching phase and sliding phase. The stability of the system is guaranteed in the sense of the Lyapunov stability theorem. The chattering problem is overcome using a hyperbolic function for the sliding surface. Experimental results that are compared with the results of conventional PID verify that the proposed sliding mode controller can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances.     

A novel adaptive sliding mode control with application to MEMS gyroscope

This paper presents a new adaptive sliding mode controller for MEMS gyroscope; an adaptive tracking controller with a proportional and integral sliding surface is proposed. The adaptive sliding mode control algorithm can estimate the angular velocity and the damping and stiffness coefficients in real time. A proportional and integral sliding surface, instead of a conventional sliding surface is adopted. An adaptive sliding mode controller that incorporates both matched and unmatched uncertainties and disturbances is derived and the stability of the closed-loop system is established. The numerical simulation is presented to verify the effectiveness of the proposed control scheme. It is shown that the proposed adaptive sliding mode control scheme offers several advantages such as the consistent estimation of gyroscope parameters including angular velocity and large robustness to parameter variations and external disturbances.     

模型参考自适应滑模控制方法在前向像移补偿中的应用

为了提高航空相机的飞行分辨率,提出了一种基于模型参考自适应的滑模控制方法。用模型参考自适应算法对时变系统参数进行在线辨识,并改变滑模控制器的控制参数。采用基于衰减控制的变速趋近律作切换函数,加快系统收敛速度,减小切换过程中的抖动。实验结果表明,同PID控制方法相比较,模型参考自适应滑模控制方法将速度补偿误差降低了60%,相应地将航空相机的飞行分辨率提高了2倍。因此,基于此方法的前向像移补偿系统可提高速度跟踪精度和鲁棒性,对时变干扰力矩具有较强的抑制能力。     

随机振动机械臂的自适应鲁棒滑模控制

为了解决存在外部不确定随机干扰情况下机械臂的高精度轨迹跟踪问题,提出了一种自适应鲁棒滑模控制方法,并用Lyapunov稳定性定理证明了其闭环系统的稳定性。采用饱和函数取代控制器中的符号函数,有效消除了控制器的抖振现象。仿真结果证明：与传统的PID控制器相比,提出的自适应鲁棒滑模控制器具有更高的鲁棒性、稳定性和精度。     

An adaptive sliding mode control technology for weld seam tracking

A novel adaptive sliding mode control algorithm is derived to deal with seam tracking control problem of welding robotic manipulator, during the process of large-scale structure component welding. The proposed algorithm does not require the precise dynamic model, and is more practical. Its robustness is verified by the Lyapunov stability theory. The analytical results show that the proposed algorithm enables better high-precision tracking performance with chattering-free than traditional sliding mode control algorithm under various disturbances.     

一种微操作平台的自适应运动跟踪控制

针对微操作平台的迟滞非线性和时变性,提出单神经元PID控制策略来对其进行运动跟踪控制,从而提高平台的运动精确性和响应快速性。采用RBF神经网络辨识器对微操作平台的梯度信息进行在线辨识,利用单神经元网络学习算法完成PID参数的在线自整定,实现微操作平台的自适应运动跟踪控制。为说明所提出控制方法的可行性,将其与普通PID控制方法进行了比较分析,实验结果表明,单神经元PID与普通PID控制的位移误差范围分别为-0.5~0.5μm、-2.5~2.5μm,调整时间分别为0.1s、0.4s,所提出控制方法具有更好的控制精度和响应快速性,并具有较强的自适应性。     

基于神经网络PID控制的系统非线性校正的研究

在对BP神经网络PID控制器系统研究的基础上，提出了单神经元的自适应PSD算法。该算法兼有单神经元和自适应PSD算法的特点，简单、实时性好、自适应能力强，可用于控制过程时变、有大滞后的较复杂的对象，是一种实用价值较高的自适应控制算法。文中采用BP神经网络PID控制与单神经元PSD自适应控制两种方法对压电式微位移系统进行非线性控制，并取得了良好的效果。     

Second-order sliding mode control with experimental application

In this article, a second-order sliding mode control (2-SMC) is proposed for second-order uncertain plants using equivalent control approach to improve the performance of control systems. A Proportional + Integral + Derivative (PID) sliding surface is used for the sliding mode. The sliding mode control law is derived using direct Lyapunov stability approach and asymptotic stability is proved theoretically. The performance of the closed-loop system is analysed through an experimental application to an electromechanical plant to show the feasibility and effectiveness of the proposed second-order sliding mode control and factors involved in the design. The second-order plant parameters are experimentally determined using input-output measured data. The results of the experimental application are presented to make a quantitative comparison with the traditional (first-order) sliding mode control (SMC) and PID control. It is demonstrated that the proposed 2-SMC system improves the performance of the closed-loop system with better tracking specifications in the case of external disturbances, better behavior of the output and faster convergence of the sliding surface while maintaining the stability.     

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller     

Robust tracking control of triaxial angular velocity sensors using adaptive sliding mode approach

This paper presents a robust tracking control strategy using an adaptive sliding mode approach for MEMS triaxial angular sensor device that is able to detect rotation in three orthogonal axes, using a single vibrating mass. An adaptive sliding mode controller with proportional and integral sliding surface is developed and the stability of the closed-loop system can be guaranteed with the proposed adaptive sliding mode control strategy. The proposed adaptive sliding mode controller updates estimates of all stiffness errors, damping, and input rotation parameters in real time, removing the need for any offline calibration stages. To enable all unknown parameter estimates to converge to their true values, the necessary model trajectory is shown to be a three-dimensional Lissajous pattern. The numerical simulation for a MEMS triaxial angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive sliding mode control scheme.