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微操作机器人的视觉伺服控制 总被引:10,自引:1,他引:9
视觉伺服控制是微操作机器人实现精确运动,完成自动操作的必要手段.本文介绍
了实现微操作机器人视觉伺服控制的方法.首先论述了微操作机器人的视觉伺服结构,并以
建立的面向生物工程的双手微操作机器人系统为例,介绍了基于二维显微视觉信息的三自由
度柔性铰链微操作机器人的运动学建模方法,针对压电驱动器控制器的特点提出了基本的PI
D视觉伺服控制规律实现方法,并进行了点到点运动和圆轨迹跟踪实验.实验结果表明,视
觉伺服控制克服了由于标定以及环境等因素导致的运动模型不准确而引入的误差. 相似文献
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一种适用于微型PLC的嵌入式操作系统设计 总被引:1,自引:0,他引:1
为了解决通用嵌入式操作系统在微型PLC设计上的不足,提出一种适用于微型PLC的面向对象嵌入式操作系统设计方案。该系统由内核、PLC解释器、I/O存储空间映射、驱动程序等部分组成,其中内核又由工厂、事件管理、用户接口以及任务管理等模块组成。其特点是采用面向对象、模板以及设计模式的方式编程,从底层提供对微型PLC设计的优化,提供动态内存分配与自动回收功能和内存与I/O口的映射功能,且内嵌PLC解释器。经过测试表明该嵌入式操作系统可满足微型PLC的设计要求。 相似文献
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This paper addresses the following supervisory problem: a continuous plant (P) is to be supervised via symbolic (or quantised) actions. These symbolic actions suggest the set points for the lower level control loops. The system dynamic is analysed on the supervisory level (K) by a qualitative approach. The relationships between variables and the steady-state references are known. These problems are especially common in chemical process control. The supervisor handles start-up and shut-down procedures and takes appropriate action to solve the sequential or parallel tasks of a basic procedure. The object of this paper is to introduce an approach to solving the problem of how to derive a set of rules from a physical process.The solutions for supervising start-up and shut-down operations in close loop are suitable for large industrial systems, as are as the batch and semi-continuous processes used in order to maintain operations in a dynamic mode. This paper considers the qualitative event-based expert supervision approach to distillation column problems. The development of a general supervision in this work is based on an events generator and a corrective actions generator. The qualitative symbols are based on fuzzy sets. In particular, there are mechanisms for processing the changes in the system variables from qualitative symbols. 相似文献
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Traditional manufacturing systems are built on the principle of economies of scale. Here, the large fixed costs of production are depreciation-intensive because of huge capital investments made in high-volume operations. These fixed costs are spread over large production batch sizes in an effort to minimize the total unit costs of owning and operating the manufacturing system. As an alternative to “batch-and-queue,” high-volume, and inflexible operations, the principles of the Toyota Production System (TPS) and lean manufacturing have been widely adopted in recent years in the US [1, 2, 3 and 4]. In this paper, we illustrate an equipment replacement decision problem within the context of lean manufacturing implementation. In particular, we demonstrate how the value stream mapping (VSM) suite of tools can be used to map the current state of a production line and design a desired future state. Further, we provide a roadmap for how VSM can provide necessary information for analysis of equipment replacement decision problems encountered in lean manufacturing implementation. 相似文献
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随着微电子机械系统(MEMS)的迅猛发展,自主式微直升机的研究也已成为这一领域内的研究热点之一.由于微直升机尺寸的限制,不能安装功能很强的传感器和处理器,难以获得完全的环境信息,所以传统的基于模型的控制方法不适用于环境是动态的自主微直升机控制.基于行为的控制方法采用累次逼近的方法,不需要环境的精确模型,因此系统的稳定性较好.本文采用基于替代传导径迹的增强式学习,结合即时差分方法,提高其学习效率,仿真实验验证了该学习算法的有效性.最后,本文介绍了微直升机控制中存在的一些问题和
我们以后的改进方向. 相似文献
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针对间歇过程控制策略优化问题,提出一种基于递推非线性部分最小二乘(NLPLS)模型的批到批优化方法:首先采用非线性部分最小二乘方法建立软测量模型,根据过程的控制操作变量对最后的产品质量进行预测。然后基于该模型,计算出最优控制策略并在实际装置上实施。为了解决模型和对象失配并且存在未知扰动的问题,采用递推算法,在每个批次结束后根据新得到的数据和旧模型参数对原模型进行更新。然后,重新求解最优控制策略并在对象上实施。通常经过几个批次,控制策略将收敛到一个满意解。在一个间歇过程上进行仿真研究,同时与基于PLS模型的批到批优化算法进行对比,结果表明采用NLPLS模型取得了优于采用PLS模型的结果。 相似文献
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A new method is developed to estimate the minimum variance bounds and the achievable variance bounds for the assessment of the batch control system when the iterative learning control is applied. Unlike continuous processes, the performance assessment of batch processes requires particular attention to both disturbance changes and setpoint changes. Because of the intrinsically dynamic operations and the non-linear behavior of batch processes, the conventional approach of controller assessment cannot be directly applied. In this paper, a linear time-variant system for batch processes is used to derive the performance bounds from the routine operating batch data. The bounds at each time point computed from the deterministic setpoint and the stochastic disturbance for the controlled output variance can help create simple monitoring charts. They are used to track the progress easily in each batch run, to monitor the occurrence of the observable upsets, and to accordingly improve the current performance. The applications are discussed through simulation cases to demonstrate the advantages of the proposed strategies. 相似文献