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基于级联式控制策略的农业机械自动导航控制方法研究
其他题名Research on Automatic Navigation Control Method Based on Cascaded Control Strategy for Agricultural Machinery
李逃昌1,2
导师胡静涛
分类号TP273
关键词农机导航 自适应滑模控制 鲁棒自适应控制 非线性最优控制 模糊自适应纯追踪
索取号TP273/L34/2014
页数126页
学位专业机械电子工程
学位名称博士
2014-05-16
学位授予单位中国科学院沈阳自动化研究所
学位授予地点沈阳
作者部门信息服务与智能控制技术研究室
摘要随着农业现代化进程的加快,具有自动导航能力的轮式农业机械(以下简称农机)具有广阔的发展前景。目前,农机的自动导航控制主要是对农机进行横向控制,即控制农机跟踪事先规划好的作业路径,使其与路径之间的横向位置偏差保持在一定的精度范围之内。由于导航控制方法对农机自动导航系统控制性能的优劣起着决定性的作用,因此有必要对农机自动导航控制方法进行深入的研究。 本文以实际应用为导向、以级联式控制策略为方案,深入地研究了农机转向控制方法、基于位姿偏差的路径跟踪控制方法和基于期望横摆角速度的路径跟踪控制方法,并以这些方法为基础,提出了基于级联式控制策略的农机导航控制方法,实现了农机自动导航控制。为了验证所研究方法的有效性和可行性,本文在不同的农机自动导航控制平台上进行了方法的验证实验和应用实验。本文的主要研究工作和贡献如下: (1)针对农机转向控制问题提出了一种基于非线性积分滑模面的自适应滑模控制方法。当农机转向控制子系统遭受不确定因素和外部干扰的影响时,该方法能够保证农机的转向轮快速而准确地跟踪期望的转向角指令。在方法的研究中,首先研究了农机转向系统的数学模型,将电控机械式和电控液压式驱动的农机转向系统建模成由一阶惯性和纯积分环节组成的二阶模型。然后根据转向系统的执行能力和控制目标设计期望转向角的暂态过程,并在此基础上提出了一种非线性积分滑模面,进而设计出相应的滑模控制律,保证了系统快速而无超调的响应特性;同时,本文采用模糊控制方法实时估计系统等效干扰,实现了滑模切换增益的在线自适应调整,从而减弱了滑模控制量的抖振现象。 (2)针对农机路径跟踪控制问题提出了三种基于位姿偏差的农机路径跟踪控制方法,即最优PD路径跟踪控制方法、模糊自适应纯追踪路径跟踪控制方法和非线性最优路径跟踪控制方法。在第一种方法的研究中,首先推导出以位置误差及其导数为状态变量的状态方程。然后基于此状态方程利用LQR方法确定PD控制器的比例和微分参数,得到符合某一性能指标的最优参数,从而保证农机最优地跟踪期望路径行驶。在第二种方法的研究中,首先讨论了农机的纯追踪模型,并详细分析了纯追踪模型中的前视距离参数对路径跟踪控制效果的影响。然后基于该分析结果提出一种模糊控制规则可在线调整的模糊控制器,进而采用这种模糊控制器来在线自适应地确定前视距离参数。该方法克服了最优PD方法或者其他传统控制方法设计过程中对农机模型进行小角度近似线性化的缺点,而且也解决了纯追踪模型中前视距离的实时自适应确定问题,增强了纯追踪路径跟踪方法对不同初始误差状态的适应性和鲁棒性。在第三种方法的研究中,首先建立了基于空间参数(即路径弧长参数)驱动的非线性农机相对运动学模型。然后研究了基于空间参数驱动的模型进行控制设计的合理性和基于该模型进行反馈线性化的可行性问题。最后,针对该非线性模型进行内环的反馈线性化设计和外环的最优化设计,得到在某一性能指标下最优的且与行驶速度无关的农机路径跟踪控制律。该方法在设计过程中不需要对非线性模型进行常速假设和小角度线性近似处理,且对农机行驶速度的变化具有鲁棒性。 (3)针对农机受到大的扰动时横向位置响应的一致性问题,本文将横摆角速度控制引进到路径跟踪控制中,提出一种基于期望横摆角速度的农机路径跟踪控制方法,重点研究了农机横摆角速度鲁棒自适应控制方法。在方法的研究中,首先建立了农机牵引或者悬挂机具时的农机-机具横摆角速度动力学模型,并分析了农机牵引或悬挂机具时的动力学特性。然后基于所建的动力学模型提出一种鲁棒自适应控制律,并以定理的形式证明了基于所提出的鲁棒自适应控制律的闭环系统的稳定性和鲁棒自适应性。该方法消除了干扰对农机横摆角速度动力学产生的影响,使农机的横摆角速度始终按照期望的横摆角速度变化,保证了在大的机具负载或外部扰动下农机横向位置响应的一致性。 (4)基于上述研究的成果,本文开展了级联式导航控制方法在农机导航系统中的应用研究,阐述了农机导航系统实现上的相关问题的求解方法,并将级联式导航控制方法应用到农机导航控制平台上进行多条连续路径的自动导航控制实验研究,实验结果进一步验证了本文研究成果的可行性和有效性。
其他摘要With the accelerated process of agriculture modernization, wheeled agricultural machinery with automatic navigation capability has broad development prospect. At present, automatic navigation control for agricultural machinery mainly refers to the lateral control that controls agricultural machinery to track predefined paths and keeps the lateral position error between agricultural machinery and the path within a certain range of accuracy. Since navigation control methods play a decisive role in an automatic navigation control system for agricultural machinery, it is necessary to conduct intensive research on agricultural machinery navigation control methods. Being application-oriented, this dissertation specializes in the agricultural machinery steering control method, the path tracking control methods based on the position and heading deviation as well as the path tracking control method based on the desired yaw rate directed by cascaded control strategy. Subsequently, based on these methods, the dissertation proposes agricultural machinery navigation control methods based on cascaded control strategy and achieves automatic navigation control of agricultural machinery. In order to verify the effectiveness and the feasibility of the proposed methods, the dissertation also carries out the experimental studies of the agricultural machinery automatic navigation control system.The main research works and contributions of the dissertation are summarized as follows: (1) For agricultural machinery steering control problem, an adaptive sliding mode control method based on a nonlinear integral sliding surface is proposed for agricultural machinery steering control. The steering control method can guarantee that the steering wheels of agricultural machinery track desired steering angle commands promptly and accurately when the agricultural machinery steering subsystem suffers from uncertainty factors and external disturbances. First, the dissertation researches the model of the agricultural machinery steering system and models it as the second-order dynamical model which consists of the first-order inertial model and the pure integrator. Second, the dissertation designs a transition process of the system control response according to the executing capacity of the steering system and the control objective, and proposes a nonlinear integral sliding surface based on the process. Further, the corresponding sliding mode control law is designed and the prompt and non-overshoot response characteristic of the steering control system is obtained. Meanwhile, the dissertation also adopts the fuzzy control method to estimate the uncertain bounds of system equivalent disturbances and realize the self-adjustment of the switching gain of sliding mode control. Thereby, the control input chattering is weakened. (2) For agricultural machinery path tracking control problem, the dissertation proposes three kinds of agricultural machinery path tracking control methods based on the position and heading deviation, namely, an optimal PD path tracking method, a path tracking method based on fuzzy adaptive pure pursuit model and a nonlinear optimal path tracking method. In the study of the first path tracking method, the dissertation deduces the system’s state equation whose state variables are the lateral position error and its derivative, and utilizes the LQR method based on the state equation to determine the proportional parameter and the differential parameter of the PD controller. The optimal parameters which meet a certain performance index are obtained. Consequently, agricultural machinery can optimally track desired paths. In the study of the second path tracking method, the dissertation discusses the pure pursuit model and analyzes the look-ahead distance parameter’s influence on path tracking control accuracy in detail. Then the dissertation proposes a fuzzy controller whose fuzzy control rules can be adjusted in real time and uses the fuzzy controller to determine the real-time look-ahead distance parameter. The path tracking control method based on fuzzy adaptive pure pursuit model overcomes the shortcoming of the small angle proximate linearization of agricultural machinery model in the design process of the optimal PD control method or other traditional control methods; it also solves the real-time adaptive determination problem of the look-ahead distance parameter of the pure pursuit model. Therefore, the robustness of the pure pursuit method for different initial error status gets enhanced. In the study of the third path tracking method, the dissertation deduces the space parameter-driven nonlinear relative kinematics model between the agricultural machinery and the tracked path, and proves the rationality and feasibility of designing control method based on the model. Then the dissertation deals with the model by input-state linearization and uses the optimal control method to stabilize the linear model obtained by feedback linearization, and then attains an agricultural machinery path tracking control law which is irrelevant to travel speeds and optimal under a certain performance index. The nonlinear optimal path tracking control method does not need small angle approximate linearization and constant speed hypothesis on nonlinear agricultural machinery model. It is robust to change of travel speed of agricultural machinery.
语种中文
产权排序1
文献类型学位论文
条目标识符http://ir.sia.cn/handle/173321/14805
专题信息服务与智能控制技术研究室
作者单位1.中国科学院沈阳自动化研究所
2.中国科学院大学
推荐引用方式
GB/T 7714
李逃昌. 基于级联式控制策略的农业机械自动导航控制方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2014.
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