Control system design of hybrid fuel cell city bus

This paper introduced the design of the hybrid powertrain of the Fuel Cell City Bus demonstrated in 2008 Beijing Olympic Games. The configuration of the hybrid fuel cell powertrain was introduced. The safety of hydrogen storage and delivery system, the hydrogen leakage alarm system were developed. The real-time distributed control and diagnosis system based on the Time Trigger Controller Area Network （TTCAN） with 10 ms basic control period was developed. The concept and implementation of processor （or controller） monitor and process （or task） monitor technique based on the TYCAN were applied in this paper. The fault tolerant control algorithm of the fuel cell engine and the battery man- agement system were considered. The demonstration experience verified that the fault tolerant control was very important for the fuel cell city bus.

Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

The core task of tracking control is to make the controlled plant track a desired trajectory.The traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps increases.In this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control problem.Unlike the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to zero.The discounted iterative scheme under the new cost function for the special case of linear systems is elaborated.Finally,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

A hybrid dynamic programming-rule based algorithm for real-time energy optimization of plug-in hybrid electric bus

The optimization of the control strategy of a plug-in hybrid electric bus(PHEB) for the repeatedly driven bus route is a key technique to improve the fuel economy. The widely used rule-based(RB) control strategy is lacking in the global optimization property, while the global optimization algorithms have an unacceptable computation complexity for real-time application. Therefore, a novel hybrid dynamic programming-rule based(DPRB) algorithm is brought forward to solve the global energy optimization problem in a real-time controller of PHEB. Firstly, a control grid is built up for a given typical city bus route, according to the station locations and discrete levels of battery state of charge(SOC). Moreover, the decision variables for the energy optimization at each point of the control grid might be deduced from an off-line dynamic programming(DP) with the historical running information of the driving cycle. Meanwhile, the genetic algorithm(GA) is adopted to replace the quantization process of DP permissible control set to reduce the computation burden. Secondly, with the optimized decision variables as control parameters according to the position and battery SOC of a PHEB, a RB control is used as an implementable controller for the energy management. Simulation results demonstrate that the proposed DPRB might distribute electric energy more reasonably throughout the bus route, compared with the optimized RB. The proposed hybrid algorithm might give a practicable solution, which is a tradeoff between the applicability of RB and the global optimization property of DP.

Improving schedule adherence based on dynamic signal control and speed guidance in connected bus system

Purpose–The purpose of this paper is to develop a dynamic control method to improve bus schedule adherence under connected bus system.Design/methodology/approach–The authors developed a dynamic programming model that optimally schedules the bus operating speed at road sections and multiple signal timing plans at intersections to improve bus schedule adherence.First,the bus route was partitioned into three types of sections:stop,road and intersection.Then,transit agencies can control buses in real time based on all collected information;i.e.control bus operating speed on road sections and adjust the signal timing plans through signal controllers to improve the schedule adherence in connected bus environment.Finally,bus punctuality at the downstream stop and the saturation degree deviations of intersections were selected as the evaluation criteria in optimizing signal control plans and bus speeds jointly.Findings–An illustrative case study by using a bus rapid transit line in Jinan city was performed to verify the proposed model.It revealed that based on the proposed strategy,the objective value could be reduced by 73.7%,which indicated that the punctuality was highly improved but not to incur excessive congestion for other vehicular traffic.Originality/value–In this paper,the authors applied speed guidance and the adjustment of the signal control plans for multiple cycles in advance to improve the scheduled stability;furthermore,the proposed control strategy can reduce the effect on private traffics to the utmost extend.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

基于介质响应原理的变压器油纸绝缘测试实验平台设计

油纸绝缘作为电力变压器中的主绝缘设备,在工业生产和电力传输应用中尤为重要,为验证油纸绝缘的性能状态,该文研制了基于介质响应原理的现场可编程电力电子控制实验平台。平台以LabVIEW编程环境和三电极测试装置作为载体,采用状态机框架设计了回复电压谱与极化谱测量流程,并嵌入聚类云模型算法实现油纸绝缘状态精准分类。该实验平台可促进理论知识与实践经验相结合的教学模式革新,满足实验探索、科学研究等多层次需求。

Policy Iteration for Optimal Control of Discrete-Time Time-Varying Nonlinear Systems

Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is developed.The iterative control law is designed to update the iterative value function which approximates the index function of optimal performance.The admissibility of the iterative control law is analyzed.The results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal solution.To implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each iteration.Finally,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying parameters.The effectiveness of the developed method is illustrated by numerical results and comparisons.

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

We develop an online adaptive dynamic programming （ADP） based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

基于PROFIBUS总线的陶瓷压砖机控制系统

本文介绍了基于PROFIBUS.DP总线的陶瓷压砖机控制系统的拓扑结构。详细讨论了PROFIBUS网的通讯机理,分析了系统的程序设计和控制技术。

Optimal Constrained Self-learning Battery Sequential Management in Microgrid Via Adaptive Dynamic Programming

This paper concerns a novel optimal self-learning battery sequential control scheme for smart home energy systems. The main idea is to use the adaptive dynamic programming U+0028 ADP U+0029 technique to obtain the optimal battery sequential control iteratively. First, the battery energy management system model is established, where the power efficiency of the battery is considered. Next, considering the power constraints of the battery, a new non-quadratic form performance index function is established, which guarantees that the value of the iterative control law cannot exceed the maximum charging/discharging power of the battery to extend the service life of the battery. Then, the convergence properties of the iterative ADP algorithm are analyzed, which guarantees that the iterative value function and the iterative control law both reach the optimums. Finally, simulation and comparison results are given to illustrate the performance of the presented method. © 2017 Chinese Association of Automation.

基于SQP算法的厢舱类产品快速设计技术研究

针对大规模定制背景下产品设计制造过程中遇到的轻量化和强度校核等需求,提出了一种基于序列二次规划(SQP)算法的结构优化与快速设计方法。以方舱为实例对象,按照最优控制理论构建产品关键参数设计数学计算模型,并运用SQP算法实现参数的最优求解,同时通过产品族模块化划分和参数化变型配置技术实现产品结构的快速设计。最后通过二次开发构建了相应的数字化设计平台,验证了该方法的可行性。结果表明:该方法能有效提高产品结构设计的效率和合理性。

基于国产SOPC的多通道控制模块设计

针对某火炮对击发控制的高可靠性和准确性需求,设计了一种基于国产SOPC的多路信号采集和控制模块,应用于其击发控制。设计了以SOPC为核心控制器的信号采集和控制电路,其中SOPC微内核与内部FPGA之间为双向实时通信机制,硬件采用Verilog HDL对SOPC进行了逻辑设计和外设电路构架,实现了多信号采集和控制,利用内部微处理器完成与外部设备的通信和数据交互,依托仿真测试平台完成了SOPC的通信时序和功能验证,并利用示波器和上位机进行了测试。测试结果表明,从输入信号满足条件到输出相关信号的时延低至250μs,多次测试的时延误差不超过±10μs,而采用PLC控制器进行击发控制则需要3~8 ms,较好地满足了击发控制的准确性和可靠性要求。

电动汽车有序充电智能管控软件平台设计

为了打造便捷生活,实现对用户充电信息的精确采集、充电状态的实时监测,该文基于电动汽车立体车库智能管控系统,设计并开发电动汽车有序充电智能管控软件平台。该软件由电动汽车有序充电后台管理软件和微信小程序两部分构成,旨在实现全面、高效的充电管理。电动汽车有序充电后台管理软件作为整个系统的核心,主要包括基础数据管理模块、有序充电管理模块、充电数据管理模块。微信小程序作为前端工具,主要服务于电车用户。用户可以通过小程序录入电车用户的充电需求信息、车辆信息等,还能随时查询电车充电过程状态信息等,从而实现对多网数据的统一调度、统一监控和统一管理,实现智能立体车库高效、安全运营。

过程装备与控制工程专业学生企业实习新探索——以卓越工程师班“低碳智慧换热站”实训为例

针对当前卓越工程师培养计划中实习环节存在的不足,教学团队基于高新企业与高校之间的密切合作,面向产教融合的综合实践课程,探索了一种新型的综合企业实习模式。该模式借助企业提供的真实生产环境,通过递进式的两步实训,让学生能够围绕一个具体的设备系统,巩固其所延伸的多学科知识体系,并落实到实际生产中,取得了显著效果。以“低碳智慧换热站”设计实训为例,阐述了此类综合设计实训的教学方案和思路,剖析了其在落实理论联系实际、贯通多门学科等方面的优点。

基于微信开发者工具的天窗开启控制与试验研究

为了提高车辆天窗控制的灵活性,文章提出一种基于微信开发者工具和HC-42蓝牙模块的天窗控制系统。利用JavaScript开发语言设计微信小程序,实现手机与车载蓝牙的自动连接,用户通过操作界面完成天窗的开合控制,使其达到在轨道任意位置启停的效果。通过实车天窗测试,结果表明,该系统对天窗的控制效果较好,很大程度上提升了天窗移动的灵活性,同时对物联网,尤其是汽车智能化的发展具有一定实用价值。

泥化顶板影响下巷道支护方案及数值模拟

木瓜煤矿9-207工作面切巷宽度达9.2 m,跨度较大且其顶板为泥化顶板,文章重点考虑锚杆预应力对大跨度泥化顶板支护效果的影响。首先设计了9-207工作面切巷的支护方案,采用数值模拟分析支护参数,最后对比泥化顶板与非泥化顶板的支护效果。采用FLAC数值模拟方法,分析了锚杆的预应力及锚索对于巷道围岩稳定性的影响。结果表明:预应力是锚杆支护系统的关键参数,锚索具有预紧力大、作用范围大的优点。在数值结果分析基础上,优化了9-207工作面切巷的支护方案,从对比模拟结果也能看出泥化顶板的支护效果要比非泥化顶板差。在解决巷道支护受泥化顶板影响的难题时,需要加强监测和优化支护,以确保工程的安全性,为今后类似条件的巷道支护提供了参考。

嵌入式实验室门禁人脸识别系统设计

为加强对实验室门禁系统的控制,降低门禁程序的误检率,对嵌入式实验室门禁人脸识别系统进行设计与验证。简述系统的构建需求,有针对性地进行嵌入式系统总体结构设计。基础电路中接入0K6410核心板,关联前后识别端口的同时,植入图像采集装置,完成系统硬件的设计;建立嵌入式交叉识别编译环境,对所识别的图像预处理并设计定位指令,关联ORL嵌入式人脸数据库,完成系统软件的设计。系统测试结果表明:针对于静态检测识别环境和动态检测识别环境下的测试,在50名用户的识别测验后,得出的误检率均控制在15%以下,表明在实际嵌入式人脸识别过程中,识别误差小、可控、识别速度快、更易调整,具有实际的应用价值。

燃气发电厂主厂房屋顶风机控制的优化设计分析

主厂房屋顶风机是燃气发电厂的重要设备,在保证厂房通风、提高主辅设备散热效果、保障可燃气体不聚集等方面发挥着重要作用。以某燃气发电厂主厂房屋顶风机控制优化改造项目为例,分别从系统设计、程序编写、远程通信等方面优化燃气-蒸汽联合循环发电机组主厂房屋顶风机的控制,实现风机温度调节、远程控制、优先级控制等功能,保障机组运行效率和安全。

基于PLC的农业机械自动化控制系统设计与应用

该文研究了基于PLC的农业机械自动化控制系统设计与应用。首先介绍了农业机械自动化控制的背景和意义,分析了目前国内外农业机械控制技术的研究现状和发展趋势。其次,介绍了PLC技术的特点和应用优势,并详细阐述了PLC在农业机械控制中的应用方法和实现步骤。然后,设计了基于PLC的农业机械自动化控制系统,包括硬件电路设计和软件程序设计两个部分。最后,进行了田间试验验证,结果表明该系统具有较高的自动化控制精度和可靠性,可以提高农业机械的工作效率和生产质量,降低生产成本,具有较好的应用价值和推广前景。

程控阀的设计与加工

程控阀在工业自动化控制、变压吸附装置(PSA)气体分离等系统中起着重要作用,然而设计和加工过程中存在一些问题与挑战。本文针对这些问题,进行了深入分析研究。首先,分析了程控阀的设计需求和加工工艺,明确了研究的重要性和意义。接着,采用了先进的设计、计算、模型试验、最优的加工工艺以及前沿的精加工设备,对程控阀设计和加工的全过程进行优化。通过实验和仿真验证,得到了一系列令人满意的结果和发现。最后,总结了本研究的主要结论和意义,为程控阀的设计和加工提供了有价值的参考。