由于船体表面形状不规则及海浪激励引起船舶运动,因此船舶清洗作业成为难点.为实现船舶高效、自动化清洗作业,该文提出一种变结构空间绳驱动清洗机器人.首先,采用Newton-Euler法建立包含船舶运动及多种外部扰动的动力学模型.通过流体仿真试验验证了水射流可喷射至作业面,并得到水枪反作用力.其次,考虑到海风对清洗作业的影响,采用风压投影法计算得到风扰力,并将风扰力与水枪反作用力共同作为扰动输入.再次,在动力学模型的基础上,为实现动基座激励下的高精度轨迹跟踪控制,提出了 一种模糊自适应比例-积分(proportional-integral,PI)滑模控制器(fuzzy adaptive PI sliding mode controller,FAPI-SMC).最后,采用Lyapunov理论证明了控制系统稳定,并通过仿真试验验证了 FAPI-SMC有效.结果表明:在不同形式的波浪激励和作业场景下,FAPI-SMC的位置稳态误差为±0.02 m,角度稳态误差为±0.02°.与传统的比例-积分-微分(proportional-integral-derivative,PID)控制器相比,FAPI-SMC的最大误差减少6％,响应速度提升57％,稳态性能提升3％.该研究成果可为绳驱动机构的实船应用提供理论依据.
Dynamic modeling and robust control of cable-driven cleaning robot for marine multi-curvature bulkhead
[Objective]Cleaning operations for ships become challenging due to the irregular hull surface and ship motion.Thus,to achieve efficient and automated cleaning operations,this study proposes a variable-structure spatial cable-driven cleaning robot.Existing research is mainly based on fixed-base conditions and has not considered the influence of base motion on modeling accuracy.The cleaning robot is mounted on ships,and the 6 degrees of freedom ship motion will inevitably affect the tracking accuracy of the motion platform,eventually causing closed-loop instability of the system.Moreover,most research simplifies the external disturbances acting on the motion platform,which cannot accurately comprehend the influence of external disturbances on tracking accuracy.The cleaning robot is affected by external disturbances such as wind,waves,and currents during operation,and existing dynamic models are inapplicable.[Methods]To address the aforementioned issues,this study proposes the use of the Newton-Euler method to establish a dynamic model including ship motion and external disturbances.Fluid simulation is used to verify that water flow can be sprayed onto the operating surface,and to determine the reaction force acting on the motion platform.Furthermore,given the influence of sea wind on cleaning operations,the wind pressure projection method is used to calculate the wind's disturbing force and combine it with the reaction force of water flow as an external disturbance.Furthermore,given the uncertainty of the dynamic model,it is decomposed into the modeled part and model error,and separate control laws are designed for these two parts.A proportional-integral sliding mode controller(PI-SMC)is further proposed.To improve the response speed and tracking accuracy of the control system,a fuzzy adaptive PI sliding mode controller(FAPI-SMC)is proposed based on the PI-SMC with an adaptive law and a fuzzy control strategy.Finally,the stability of the control system is proven by the Lyapunov theory,and the effectiveness of the controller is verified through simulations.[Results]The numerical analysis results showed that:(1)Under the set operating conditions,water flow could be sprayed onto the operating surface,and the mean value of the reaction force was approximately 9 N.(2)Under different forms of wave excitations and operating conditions,the position steady-state error of the motion platform under FAPI-SMC was maintained at±0.02 m,and the angle steady-state error was maintained at±0.02°.(3)When the operating conditions change,the steady-state error under proportional-integral-differential controller(PID)changed by approximately 0.16 m,the steady-state error under PI-SMC changed by approximately 0.19 m,and a smaller steady-state error under FAPI-SMC changed by approximately 0.01 m.(4)Compared with PI-SMC and PID,the maximum error of FAPI-SMC was reduced by 8％and 6％,respectively,the response speed was improved by 18％and 57％,respectively,and the steady-state performance was improved by 2％and 3％,respectively.[Conclusions]The proposed control strategy has high precision and rapid response under ship motion and external disturbances.Moreover,the cleaning robot has excellent operating stability for different wave excitations and operating conditions.Thus,the dynamic model and control strategy proposed in this study can provide theoretical guidance for applying cable-driven mechanisms in ships.
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