基于非线性H∞状态反馈的机器人鲁棒控制

针对机器人存在参数不确定性以及外界未知干扰的情况,运用反推(backstepping)设计方法 ,通过求解非线性H∞状态反馈控制问题,设计了一种鲁棒控制器,实现了对外界未 知干扰的有效衰减,以及只考虑参数不确定性时系统跟踪误差的渐近收敛性．最后给出了对 两连杆刚性机器人的仿真,验证了控制效果．     

基于NDO的ROV变深自适应终端滑模控制器设计

针对ROV的深度控制问题, 提出基于非线性干扰观测器的自适应终端滑模控制方法. 详细叙述了控制器的设计过程, 并利用Lyapunov 稳定性判据, 验证了存在模型参数不确定性和外干扰时, 系统的全局渐近稳定性和跟踪误差的收敛性. 仿真实验表明, 所提出的控制器不仅能够很好地估计并克服外干扰和模型不确定性等因素, 具有很好的鲁棒性能, 而且还可以实现在任意规定时刻变深运动的快速收敛.

     

基于非线性H_∞状态反馈的机器人鲁棒控制

针对机器人存在参数不确定性以及外界未知干扰的情况 ,运用反推 (backstepping)设计方法 ,通过求解非线性 H∞ 状态反馈控制问题 ,设计了一种鲁棒控制器 ,实现了对外界未知干扰的有效衰减 ,以及只考虑参数不确定性时系统跟踪误差的渐近收敛性 .最后给出了对两连杆刚性机器人的仿真 ,验证了控制效果 .     

挠性飞行器姿态稳定鲁棒变结构控制

针对三轴稳定卫星的模型参数存在不确定性,设计了一种鲁棒变结构控制器,它能确保系统在一定条件下具有全局渐近稳定性,并且系统在一定条件下能在有限的时间内到达滑动平面,具有鲁棒到达条件,同时控制律实现简单,采用积分型滑动平面,能保证系统在到达滑动平面后具有良好的性能,最后根据卫星参数给出了具体的数值算例,数值仿真结果良好,从数值仿真结果来看控制器在存在较大不确定性情况下（考虑系统转动惯量有5％的不确定性）依然保持良好性能,具有很强的鲁棒稳定性,而且,采用边界层改进控制器后,能有效地解决抖振问题,同时控制器的性能基本保持不变,说明鲁棒变结构控制器的设计是有效的。     

不确定性系统的自适应鲁棒跟踪控制

针对存在未知干扰和未建模动态等不确定性的系统的自适应鲁棒跟踪控制问题进行了 探讨.首选将l1优化控制器的有限拍设计方法结合给出了最优鲁棒稳态跟踪控制器的设计方法． 然后利用集员辨识的思想,将名义模型的参数和未建模动态及干扰的大小作为未知参数,提出了 一种递推参数估计方法.最后将上述研究结果结合起来提出了一种自适应鲁棒跟踪控制策略,证 明了自适应算法的全局收敛性并给出了鲁棒跟踪性能指标的一下较紧的上界.与现有的结果相 比,本文提出的自适应控制具有非保守的鲁棒稳定性,具有渐近最优的鲁棒跟踪性能.     

二级倒立摆的鲁棒建模及其鲁棒H∞最优控制

针对倒立摆系统本身存在的大量不确定性因素，建立其不确定数学模型。苦于最优控制的思想，针对二级倒立摆的参数摄动及干扰，设计了鲁棒H∞最优控制器，并在二级倒立摆实验装置上进行控制。实验结果表明；用鲁棒H∞最优控制器的二级倒立摆系统，具有很强的鲁棒稳定性和抗干扰性。     

一类不确定时滞奇异系统的鲁棒非脆弱控制

针对不确定奇异时滞系统，研究了鲁棒非脆弱控制问题。假定不确定性范数有界，设计了基于观测器的控制器，使得闭环系统在不确定性影响下保持鲁棒稳定。仅通过求解相应线性矩阵不等式就可得到鲁棒状态反馈控制器，该控制器不仅对所有容许的系统不确定性使相应的闭环系统渐近稳定，而且满足控制器本身是非脆弱的，达到抑制干扰的效果。     

一类不确定时滞奇异系统的鲁棒非脆弱控制

针对不确定奇异时滞系统,研究了鲁棒非脆弱控制问题.假定不确定性范数有界,设计了基于观测器的控制器,使得闭环系统在不确定性影响下保持鲁棒稳定.仅通过求解相应线性矩阵不等式就可得到鲁棒状态反馈控制器,该控制器不仅对所有容许的系统不确定性使相应的闭环系统渐近稳定,而且满足控制器本身是非脆弱的,达到抑制干扰的效果.     

并联机器人的鲁棒自适应控制

本文针对含有不确定性的液压并联机器人，提出了一种鲁棒自适应控制器，该控制器能够克服参数变化和负载扰动的不良影响，保证系统的鲁棒全局渐近稳定性的良好的踊跃动态性能，计算机仿真结果证明了该控制方案的有效性。     

非线性不确定中立型系统的鲁棒H∞控制

考虑系统外界干扰、系统参数摄动等非线性扰动环节对中立型时滞系统的H∞影响,提出基于Lyapunov稳定性理论的鲁棒H∞控制器的设计思想.利用线性矩阵不等式(LMI)方法,给出了该类具有状态非线性不确定性中立型时滞系统的鲁棒∞控制器的设计实例.在非线性不确定函数满足增益有界的条件下,得到了该类时滞系统满足鲁棒∞性能的一个充分条件.通过求解一个线性矩阵不等式LMI,即可获得鲁棒∞控制器.仿真结果表明了基于Lyapunov稳定性理论,LMI技术设计的控制器克服了系统外界非线性干扰或系统本身非线性参数摄动的影响,实现了闭环系统的H∞性能条件下的渐近稳定,满足了该系统鲁棒H∞控制的要求.     

Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design

Combining sliding mode control method with radial basis function neural network (RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle (NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.      

干扰下的无人直升机自适应反步法鲁棒跟踪控制

针对无人直升机干扰下的鲁棒轨迹跟踪问题,设计了一种自适应反步控制方法.鉴于作用在直升机上的干扰是产生跟踪误差的主要原因,该方法的主要思想是寻求一种方法来补偿这种干扰.首先,将未建模动态如外部阵风干扰、配平误差、机身、垂尾、平尾以及其他可忽略的动态产生的力和力矩看成一种组合干扰,从而建立了一个方便反步法控制器设计的简化模型.当设计好反步法控制器后,设计了一个非线性自适应律来估计这种组合干扰,并通过将干扰估计值整合到反步控制器中,使得闭环跟踪系统的鲁棒稳定性得到了保证,即基于李雅普诺夫稳定性理论证明了所设的控制器对于干扰主动阻隔,特别是低频干扰的主动阻隔是有效的.最后,两个仿真研究验证了该方法是优于常规反步法和积分反步法的.     

A novel adaptive backstepping design of turbine main steam valve control

The problem of transient stability for a single machine infinite bus system with turbine main steam valve control is addressed by means of a novel adaptive backstepping method in this paper. The recursive design procedure of the proposed controller is much simpler than that of the existing controller based on conventional adaptive backstepping method. In the system, the damping coefficient is measured inaccurately, and the reactance of transmission line also contains a few uncertainties. A nonlinear robust controller and parameter updating laws are obtained simultaneously. The system does not need to be linearized, and the closed-loop error system is guaranteed to be asymptotically stable. The design procedure and simulation results demonstrate the effectiveness of the proposed design.     

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.     

A modified direct adaptive robust motion trajectory tracking controller of a pneumatic system

In this study, we developed and tested a high-precision motion trajectory tracking controller of a pneumatic cylinder driven by four costless on/off solenoid valves rather than by a proportional directional control valve. The relationship between the pulse width modulation （PWM） of a signal＇s duty cycle and control law was determined experimentally, and a mathematical model of the whole system established. Owing to unknown disturbances and unmodeled dynamics, there are considerable uncertain nonlinearities and parametric uncertainties in this pneumatic system. A modified direct adaptive robust controller （DARC） was constructed to cope with these issues. The controller employs a gradient type adaptation law based on discontinuous projection mapping to guarantee that estimated unknown model parameters stay within a known bounded region, and uses a deterministic robust control strategy to weaken the effects of unmodeled dynamics, disturbances, and parameter estimation errors. By using discontinuous projection mapping, the parameter adaptation law and the robust control law can be synthesized separately. A recursive backstepping technology is applied to account for unmatched model uncertainties. Kalman filters were designed sepa- rately to estimate the motion states and the derivative of the intermediate control law in synthesizing the deterministic robust control law. Experimental results illustrate the effectiveness of the proposed controller.     

Active Heave Compensation Control of ROVS

To keep the remotely operated vehicles (ROVs) motion unaffected by the ship's motion in the vertical direction, a nonlinear active heave compensation controller is designed in this paper. The compensation system consists mainly of an electro‐hydraulic system driven by a double rod cylinder. Based on the external model principle, an adaptive observer is proposed to asymptotically estimate the ship's heave motion represented by a set of sinusoidal signals. The hybrid control development and stability analysis are based on the Lyapunov's direct method and backstepping technique. The proposed controller forces the tracking error to globally asymptotically converge to a small zone around zero that can be reduced arbitrarily. Simulation results illustrate and validate the effectiveness of the proposed control scheme.     

Robust multivariable control of complex biological processes

This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible.     

Global disturbance rejection of a class of nonlinear systems with unknown exosystems

An asymptotic rejection algorithm is proposed for a class of nonlinear systems that have not only additive nonlinear uncertainties but also unknown disturbances. The disturbances are generated from an unknown exosystem, and are assumed to be sinusoidal disturbances with unknown amplitude and frequency. By using the technique of backstepping and adaptive control, a nonlinear state feedback controller is designed. Under the proposed controller, the system＇s state variables asymptotically converge to zero, and the disturbances are rejected completely. The approach used is an integration of the robust stabilization technique, adaptive technique, and backstepping technique.     

未知不确定非线性系统的直接自校正滑模控制

针对一类具有未知不确定性的非线性系统,提出一种参数直接自校正滑模控制方法.将系统的非线性、参数变化和外部干扰都视作系统不确定性,控制器的设计无需不确定项的上下界等信息:为改善跟踪性能与减小输入抖振,控制器设计中引入可调边界层厚度的双极性sigmoid函数与可变滑模切换增益,推导出控制增益和边界层厚度的直接自校正律,并基于Lyapunov判据给出了闭环系统稳定性证明.仿真实例证明了该方法的有效性和正确性.