氨法脱硫系统存在滞后大、非线性和实时负荷跟踪性差等问题。针对该问题设计的Smith预估控制器通过补偿延迟时间提高了系统的实时性。但通常采用试凑法来设定系统中的PID(Proportion Integral Differential)参数,导致系统稳定性较差。...氨法脱硫系统存在滞后大、非线性和实时负荷跟踪性差等问题。针对该问题设计的Smith预估控制器通过补偿延迟时间提高了系统的实时性。但通常采用试凑法来设定系统中的PID(Proportion Integral Differential)参数,导致系统稳定性较差。文中提出模糊PID参数自适应整定控制方法,通过模糊控制器求得PID的3个参数的调整值,自适应地调整PID参数,将SNO_(x)的浓度控制在预设值附近。与传统阶跃信号判断控制效果不同,文中所提方法以实时的负荷数据来进行模型仿真,数据仿真结果也证明了Smith预估模糊PID控制器的可行性。系统稳定时SNO_(x)浓度与预设值的误差在0.5 ppm以内,缩短了调节时间,表明所提方法改善了氨法脱硫控制系统的实时跟踪性,实现了快准稳的脱硫控制性能。展开更多
To address the nonlinearities and external disturbances in unstructured and complex agricultural environments,this paper investigates an autonomous trajectory tracking control method for agricultural ground vehicles.F...To address the nonlinearities and external disturbances in unstructured and complex agricultural environments,this paper investigates an autonomous trajectory tracking control method for agricultural ground vehicles.Firstly,this paper presents the design and implementation of a lightweight,modular two-wheeled differential drive vehicle equipped with two drive wheels and two caster wheels.The vehicle comprises drive wheel modules,passive wheel modules,battery modules,a vehicle frame,a sensor system,and a control system.Secondly,a novel robust trajectory tracking method was proposed,utilizing an improved pure pursuit algorithm.Additionally,an Online Particle Swarm Optimization Continuously Tuned PID(OPSO-CTPID)controller was introduced to dynamically search for optimal control gains for the PID controller.Simulation results demonstrate the superiority of the improved pure pursuit algorithm and the OPSO-CTPID control strategy.To validate the performance,the vehicle was integrated with a seeding and fertilizing machine to realize autonomous wheat seeding in an agricultural environment.Experimental outcomes reveal that the vehicle of this study completed a seeding operation exceeding 1 km in distance.The proposed method can robustly and smoothly track the desired trajectory with an accuracy of less than 10 cm for the root mean square error(RMSE)of the curve and straight lines,given a suitable set of parameters,meeting the requirements of agricultural applications.The findings of this study hold significant reference value for subsequent research on trajectory tracking algorithms for ground-based agricultural robots.展开更多
文摘氨法脱硫系统存在滞后大、非线性和实时负荷跟踪性差等问题。针对该问题设计的Smith预估控制器通过补偿延迟时间提高了系统的实时性。但通常采用试凑法来设定系统中的PID(Proportion Integral Differential)参数,导致系统稳定性较差。文中提出模糊PID参数自适应整定控制方法,通过模糊控制器求得PID的3个参数的调整值,自适应地调整PID参数,将SNO_(x)的浓度控制在预设值附近。与传统阶跃信号判断控制效果不同,文中所提方法以实时的负荷数据来进行模型仿真,数据仿真结果也证明了Smith预估模糊PID控制器的可行性。系统稳定时SNO_(x)浓度与预设值的误差在0.5 ppm以内,缩短了调节时间,表明所提方法改善了氨法脱硫控制系统的实时跟踪性,实现了快准稳的脱硫控制性能。
基金Jiangsu Provincial Key Research and Development Program(Grant No.BE2017301)Jiangsu Provincial Key Research and Development Program(Grant No.BE2022363)+2 种基金Project of Jiangsu Modern Agricultural Machinery Equipment&Technology Demonstration and Promotion(Grant No.NJ2022-03)National Natural Science Fund of China(Grant No.61473155)Six Talent Peaks Project in Jiangsu Province of China(Grant No.GDZB-039).
文摘To address the nonlinearities and external disturbances in unstructured and complex agricultural environments,this paper investigates an autonomous trajectory tracking control method for agricultural ground vehicles.Firstly,this paper presents the design and implementation of a lightweight,modular two-wheeled differential drive vehicle equipped with two drive wheels and two caster wheels.The vehicle comprises drive wheel modules,passive wheel modules,battery modules,a vehicle frame,a sensor system,and a control system.Secondly,a novel robust trajectory tracking method was proposed,utilizing an improved pure pursuit algorithm.Additionally,an Online Particle Swarm Optimization Continuously Tuned PID(OPSO-CTPID)controller was introduced to dynamically search for optimal control gains for the PID controller.Simulation results demonstrate the superiority of the improved pure pursuit algorithm and the OPSO-CTPID control strategy.To validate the performance,the vehicle was integrated with a seeding and fertilizing machine to realize autonomous wheat seeding in an agricultural environment.Experimental outcomes reveal that the vehicle of this study completed a seeding operation exceeding 1 km in distance.The proposed method can robustly and smoothly track the desired trajectory with an accuracy of less than 10 cm for the root mean square error(RMSE)of the curve and straight lines,given a suitable set of parameters,meeting the requirements of agricultural applications.The findings of this study hold significant reference value for subsequent research on trajectory tracking algorithms for ground-based agricultural robots.
