深海底采矿机器车运动建模与控制研究
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摘要
深海底蕴藏着丰富的矿产资源,对其开发手段的研究,对我国矿产资源的可持续利用,及深海作业技术的发展,具有重要的战略意义。深海底采矿机器车行走于6000m深海底“极稀软”沉积物底质,作业环境为无自然光、海底高压、未知复杂环境,其控制质量的好坏直接关系我国大洋战略开发的实施质量。为此,在国家大洋专项基金——国际海底区域研究开发“十五”项目(DY105-03-02-06)的资助下,本文重点研究了深海底采矿机器车的建模与控制技术。论文的主要研究成果包括:
1) 深海底采矿机器车运动建模技术
深海底采矿机器车工作于6000m深海“极稀软”沉积物底质,车辆设计的特殊性和作业环境的特殊性决定了其工作特性与普通履带车辆有所不同。针对深海底采矿机器车高尖三角齿、大沉陷、高打滑率、稀软海底低速作业的特点,在特别考虑履齿附加推力、推土阻力、水阻力,并忽略向心力情况下,采用深海底沉积物特殊环境参数,对机器车牵引力和运动阻力综合计算,建立了深海底采矿机器车动力学模型;采用机器人坐标系和地面坐标系,考虑深海底采矿机器车左右履带打滑率对车体姿态的影响,建立了深海底采矿机器车的运动学模型;实现了对深海底采矿机器车极限环境动力学和运动学系统的有效描述。
针对深海底采矿机器车变量液压泵—定量液压马达容积调速系统参数复杂,高非线性的特点,将系统分解为电液比例方向阀、变量泵控制液压缸、柱塞泵和柱塞马达四个子系统分别建模,在此基础上综合建立了深海底采矿机器车液压驱动系统模型,实现了对深海底采矿机器车液压驱动系统的有效描述。
将上述数学模型进行综合,运用MATLAB语言,建立了基于MALTAB的深海底采矿机器车运动系统仿真模型,进行了仿真研究,仿真结果验证了模型的有效性。
2) 深海底采矿机器车关键运动参数在线辨识技术
由于作业环境的未知、深海底沉积物的极稀软且不均匀特性,深海底采矿机器车作业打滑严重,运动状态不确定性变化大,机器车驱动轮有效半径、左右履带打滑率等关键运动参数难以直接测量。针对该问题,提出了深海底采矿机器车关键运动参数在线计算模型,该模型通过对机器车左右液压马达压差及左右履带沉陷的检测,实现对机器车左右履带打滑率及驱动轮半径的在线计算。在此基础上,取适当状态变量,建立了深海底采矿机器车左右履带打滑率和左右履带驱
Deep seabed contains abundant mineral resource. Research on it's explore technique has important significance for our country's mineral resource continual owner and development of deep-sea resource exploitation technology. Deep seabed mining robot vehicle works in 6000m-depth seabed unknown complex environment. The control quality has direct influence on our countries ocean exploitation strategy. So, in the support of project named as Internal seabed area research and exploitation, the thesis proposes a movement modeling and control strategy for deep seabed mining robot vehicle. The main research achievements include:(1)Deep seabed mining robot vehicle movement modeling techniqueDeep seabed mining robot vehicle works in 6000m-depth extra-soft seabed, the special design and special working environment decides it's special working property. Aiming at the properties of high-sharp triangle teeth, large sink, high slip rate and low speed., after special consideration on track teeth thrust, bulldozer resistance, hydraulic resistance, and omitting centrifugal force, the dynamic model of deep seabed robot vehicle is build. After that, the kinematical model is built in Cartesian coordinate system with consideration of track slip rates.Aiming at properties of complex parameters and high nonlinearity for the vehicle's variable-hydraulic pump to fix-hydraulic motor volume velocity modulation system, the system is composed as electric-hydraulic proportional directional valve, variable-pump-controlled cylinder, piston pump and piston motor module to build model separately. On the basis of the four sub modules, deep seabed mining robot vehicle hydraulic drive model is built.Combining the dynamic model, the kinematics' model and the hydraulic model, and realized in Matlab language, he deep seabed mining robot vehicle movement system simulation model is finished. Some simulations are done to verify the validity of the model.(2) Deep seabed mining robot vehicle key moving parameters identification techniqueBecause of the unknown mining environment, uneven and extra soft seabed sediment, the vehicle works with high slip and big uncertain moving state change. However, the key moving parameters such as effective radius of driving wheel and track slips are difficult to measure. A new approach identify these parameters is presented. First, based on moving analysis, the parameters identification model is
built. The model is used to online calculate slip rate and effective radiuses of driving wheels by measurement on the motors' pressure and the sediments. After that, selecting several state variables, the nonlinear parameters estimation model of deep seabed mining robot vehicle's left and right track slip rates and effective radiuses of driving wheels is built. It builds basis for optimal unbiased estimation of deep seabed mining robot vehicle's key moving parameters.Then, an improved SUKF algorithm-FSUKF is presented: fuzzy algorithm is used to regulate sigma set operator, which makes ideal model be more identify to real model. The Mackey -Glass time series model is used to verify the validity of the algorithm.In the end, the proposed model and algorithm are used to estimate the key parameters; the simulation result verifies the validity of the method.(3)Deep seabed mining robot vehicle motion control techniqueBased on deep seabed mining robot vehicle control hardware structure and working rule, a motion control system of the vehicle is presented. The system is consisted of modules such as movement planning, parameter estimation, trajectory tracking error computation and tracking control etc. Functions of the Modules are designed separately.Usual sampling approach for trajectory planning is equal interval sampling. In order to improve control precision, a sample approach based on fuzzy rule is presented. This approach has the function of on-line tuning distance between vehicle's real place and target, according to the distance and angle errors.After analysis of tracked vehicle's tracking errors, an expert-fuzzy based cross coupling controller is designed. The internal error is deal with cross-coupling controller; an expert-fuzzy controller eliminates the external error. Simulation results are provided to verify the proposed scheme.(4) Deep seabed mining robot vehicle simulation system developmentDeep seabed mining robot vehicle is voluminous and needs high driving power. It's too expensive for usual motion control exercise. So, a small deep seabed mining robot vehicle model and a simulation system is developed to solve the problem. Some exercise is done based on vehicle model, the result is provided also.
1) 深海底采矿机器车运动建模技术
深海底采矿机器车工作于6000m深海“极稀软”沉积物底质,车辆设计的特殊性和作业环境的特殊性决定了其工作特性与普通履带车辆有所不同。针对深海底采矿机器车高尖三角齿、大沉陷、高打滑率、稀软海底低速作业的特点,在特别考虑履齿附加推力、推土阻力、水阻力,并忽略向心力情况下,采用深海底沉积物特殊环境参数,对机器车牵引力和运动阻力综合计算,建立了深海底采矿机器车动力学模型;采用机器人坐标系和地面坐标系,考虑深海底采矿机器车左右履带打滑率对车体姿态的影响,建立了深海底采矿机器车的运动学模型;实现了对深海底采矿机器车极限环境动力学和运动学系统的有效描述。
针对深海底采矿机器车变量液压泵—定量液压马达容积调速系统参数复杂,高非线性的特点,将系统分解为电液比例方向阀、变量泵控制液压缸、柱塞泵和柱塞马达四个子系统分别建模,在此基础上综合建立了深海底采矿机器车液压驱动系统模型,实现了对深海底采矿机器车液压驱动系统的有效描述。
将上述数学模型进行综合,运用MATLAB语言,建立了基于MALTAB的深海底采矿机器车运动系统仿真模型,进行了仿真研究,仿真结果验证了模型的有效性。
2) 深海底采矿机器车关键运动参数在线辨识技术
由于作业环境的未知、深海底沉积物的极稀软且不均匀特性,深海底采矿机器车作业打滑严重,运动状态不确定性变化大,机器车驱动轮有效半径、左右履带打滑率等关键运动参数难以直接测量。针对该问题,提出了深海底采矿机器车关键运动参数在线计算模型,该模型通过对机器车左右液压马达压差及左右履带沉陷的检测,实现对机器车左右履带打滑率及驱动轮半径的在线计算。在此基础上,取适当状态变量,建立了深海底采矿机器车左右履带打滑率和左右履带驱
Deep seabed contains abundant mineral resource. Research on it's explore technique has important significance for our country's mineral resource continual owner and development of deep-sea resource exploitation technology. Deep seabed mining robot vehicle works in 6000m-depth seabed unknown complex environment. The control quality has direct influence on our countries ocean exploitation strategy. So, in the support of project named as Internal seabed area research and exploitation, the thesis proposes a movement modeling and control strategy for deep seabed mining robot vehicle. The main research achievements include:(1)Deep seabed mining robot vehicle movement modeling techniqueDeep seabed mining robot vehicle works in 6000m-depth extra-soft seabed, the special design and special working environment decides it's special working property. Aiming at the properties of high-sharp triangle teeth, large sink, high slip rate and low speed., after special consideration on track teeth thrust, bulldozer resistance, hydraulic resistance, and omitting centrifugal force, the dynamic model of deep seabed robot vehicle is build. After that, the kinematical model is built in Cartesian coordinate system with consideration of track slip rates.Aiming at properties of complex parameters and high nonlinearity for the vehicle's variable-hydraulic pump to fix-hydraulic motor volume velocity modulation system, the system is composed as electric-hydraulic proportional directional valve, variable-pump-controlled cylinder, piston pump and piston motor module to build model separately. On the basis of the four sub modules, deep seabed mining robot vehicle hydraulic drive model is built.Combining the dynamic model, the kinematics' model and the hydraulic model, and realized in Matlab language, he deep seabed mining robot vehicle movement system simulation model is finished. Some simulations are done to verify the validity of the model.(2) Deep seabed mining robot vehicle key moving parameters identification techniqueBecause of the unknown mining environment, uneven and extra soft seabed sediment, the vehicle works with high slip and big uncertain moving state change. However, the key moving parameters such as effective radius of driving wheel and track slips are difficult to measure. A new approach identify these parameters is presented. First, based on moving analysis, the parameters identification model is
built. The model is used to online calculate slip rate and effective radiuses of driving wheels by measurement on the motors' pressure and the sediments. After that, selecting several state variables, the nonlinear parameters estimation model of deep seabed mining robot vehicle's left and right track slip rates and effective radiuses of driving wheels is built. It builds basis for optimal unbiased estimation of deep seabed mining robot vehicle's key moving parameters.Then, an improved SUKF algorithm-FSUKF is presented: fuzzy algorithm is used to regulate sigma set operator, which makes ideal model be more identify to real model. The Mackey -Glass time series model is used to verify the validity of the algorithm.In the end, the proposed model and algorithm are used to estimate the key parameters; the simulation result verifies the validity of the method.(3)Deep seabed mining robot vehicle motion control techniqueBased on deep seabed mining robot vehicle control hardware structure and working rule, a motion control system of the vehicle is presented. The system is consisted of modules such as movement planning, parameter estimation, trajectory tracking error computation and tracking control etc. Functions of the Modules are designed separately.Usual sampling approach for trajectory planning is equal interval sampling. In order to improve control precision, a sample approach based on fuzzy rule is presented. This approach has the function of on-line tuning distance between vehicle's real place and target, according to the distance and angle errors.After analysis of tracked vehicle's tracking errors, an expert-fuzzy based cross coupling controller is designed. The internal error is deal with cross-coupling controller; an expert-fuzzy controller eliminates the external error. Simulation results are provided to verify the proposed scheme.(4) Deep seabed mining robot vehicle simulation system developmentDeep seabed mining robot vehicle is voluminous and needs high driving power. It's too expensive for usual motion control exercise. So, a small deep seabed mining robot vehicle model and a simulation system is developed to solve the problem. Some exercise is done based on vehicle model, the result is provided also.
引文
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