Dead‐Zone Model Based Adaptive Backstepping Control for a Class of Uncertain Saturated Systems

In this paper, a dead‐zone based model of saturation phenomena is proposed. This method is capable of modelling diverse kinds of saturation, including both hard‐limited and soft‐limited. Due to use of a linear parameter approach, the proposed model is consistent with the available adaptive control techniques in the literature. In addition, based on the proposed model, an adaptive controller is designed for a class of nonlinear saturated systems, where, the shape of the saturation phenomenon is assumed to be unknown. The effectiveness of the proposed method and its robustness against initial condition variation and reference signal is evaluated via simulated examples for both spring–mass–damper and ship steering autopilot systems.     

带有未建模动态的船舶减摇鳍的鲁棒自适应控制

针对船舶减摇鳍非线性数学模型,提出一种鲁棒自适应控制器,可以用于存在非线性不确定、未知有界扰动和未建模动态的情况。应用Lyapunov稳定性理论证明,所提出的鲁棒自适应控制器可保证整个非线性系统的稳定性,且通过适当选择设计参数,可使跟踪误差达到任意精度。仿真结果表明了所提方法的有效性。     

Adaptive fuzzy robust tracking controller design via small gain approach and its application

An adaptive fuzzy robust tracking control (AFRTC) algorithm is proposed for a class of nonlinear systems with the uncertain system function and uncertain gain function, which are all the unstructured (or nonrepeatable) state-dependent unknown nonlinear functions arising from modeling errors and external disturbances. The Takagi-Sugeno type fuzzy logic systems are used to approximate unknown uncertain functions and the AFRTC algorithm is designed by use of the input-to-state stability approach and small gain theorem. The algorithm is highlighted by three advantages: 1) the uniform ultimate boundedness of the closed-loop adaptive systems in the presence of nonrepeatable uncertainties can be guaranteed; 2) the possible controller singularity problem in some of the existing adaptive control schemes met with feedback linearization techniques can be removed; and 3) the adaptive mechanism with minimal learning parameterizations can be obtained. The performance and limitations of the proposed method are discussed. The uses of the AFRTC for the tracking control design of a pole-balancing robot system and a ship autopilot system to maintain the ship on a predetermined heading are demonstrated through two numerical examples. Simulation results show the effectiveness of the control scheme.     

船舶自动舵控制技术发展研究

介绍与比较了船舶操纵的各种自动舵控制方法 ,船舶自动舵可分为四个发展阶段 ,即机械舵、PID舵、自适应舵和智能舵 ,其中智能舵为目前最先进的自动舵 ,它又分为专家系统、模糊舵和神经网络舵。     

控制增益未知的船舶航向非线性自适应跟踪控制

针对参数不确定的船舶运动非线性控制系统控制方向未知的困难,将逆推算法与Nussbaum增益方法相结合,提出一种新的自适应非线性控制策略,从而实现船舶运动航向跟踪控制.首先,从理论上证明了所设计的自适应控制器保证最终的控制系数符号未知的参数不确定船舶运动非线性系统中所有信号一致有界,船舶的实际航向全局自适应地渐近跟踪期望的参考航向.对两条船舶数学模型的仿真实验结果表明,所设计的自适应非线性跟踪控制器具有良好的适应性及鲁棒性.     

Adaptive fuzzy ship autopilot for track-keeping

An adaptive fuzzy gain autopilot for ship track-keeping is developed. This autopilot is composed of Sugeno fuzzy type autopilot in an ordinary feedback loop and adjustable scaling factors mechanism in an additional feedback loop. The adjustment mechanism represents a fuzzy controller that changes scaling factors of the base fuzzy autopilot. The control system for the track-keeping is completely described. For the track-keeping problem, the maneuver of way-point turning and ship guiding through a complex path (trajectory) are presented. The influence of sea current and wave disturbances on track-keeping performance was also considered. Simulation results obtained by the Sugeno fuzzy type autopilot are first presented. Then, those results are compared with ones obtained by an adaptive fuzzy autopilot.     

波浪作用下船舶航向自抗扰控制设计及参数配置

针对具有内部参数不确定性和外部扰动的海上船舶设计了航向自抗扰控制器,并解决了舵机模型中舵角的限幅和限速问题,基于滑模控制理论提出了反馈控制带宽的计算方法.采用频域分析的方法,系统地分析了自抗扰控制器对外部波浪扰动的抑制能力、模型参数不确定时的鲁棒性;结合作者实船工作经验以及系统动态特性与控制参数的关系,提出了船舶航向控制器参数的配置规律;最后以一艘57000吨级散货船为控制对象,验证了航向控制器的鲁棒性和本文所述参数配置规律的有效性.为将自抗扰控制算法应用于船舶自动舵设计提供理论依据和实践参考.     

Study on a new and effective fuzzy PID ship autopilot

Ship autopilots are usually designed based on Proportional Differential (PD) and Proportional Integrate Differential (PID) controllers because of their simplicity, reliability, and ease of construction. However, their performance in various environmental conditions is not as good as desired. This disadvantage can be overcome by adjusting works or constructing adaptive controllers, although these methods are complex and not easy. This article presents a new method for constructing a ship autopilot based on the combination of fuzzy logic control (FLC) and linear control theory (PID control). The new ship autopilot has the advantages of both the PID and FLC control methodologies: ease of construction, and optimal control laws can be established based on ship master knowledge. Therefore, the new ship autopilot can be well adapted with parameter variations and strong environment effects. Simulation using MATLAB software for a ship with real parameters showed high effectiveness of the fuzzy PID autopilot in course-keeping and course-changing maneuvers in comparison with the ordinary PID ship autopilots.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

船舶航向模型参考模糊自适应控制器的设计

本文介绍了模型模糊自适应控制器的结构，调节机理。针对船舶航向控制，设计了参考模型模糊自适应控制器，并进行了仿真。与普通模糊控制器控制效果进行了比较，仿真表明参考模型模糊自适应控制有良好的控制性能。     

基于观测器的不确定非线性系统的自适应鲁棒模糊控制

针对单输入单输出不确定非线性系统提出了一种自适应鲁棒模糊控制算法.该算法通过设计观测器来估计系统的状态向量,因此不要求假设系统的状态向量是可测的.在这个算法中,主要的假设为最优逼近参数向量与标称参数向量之差的范数和逼近误差的界限是未知的.通过只对未知界限估计的调节,该算法减轻了在线计算量并且提高了系统的鲁棒性.所设计的自适应鲁棒模糊控制算法保证了闭环系统的所有信号是一致有界的并且跟踪误差估计收敛到一个小的零邻域内.仿真例子证实了所提方法的可行性.