Neural network based expectation learning in perception control: learning and control with unreliable sensory system

In this article, we investigate the viability of our proposed neural network-based extension of the perception control concept introduced by Randløv and Alstrøm. In their work, each of the expectation elements is linearly acquired such that the expectation gives only the dominant information of the recent past. This handicap could become a serious problem when the perception process is applied to real physical systems. Such an approach has no capability to sense the trend or the dynamics in the information. Here, we introduce an extension of the perception control process by using a radial basis function feedforward neural network to learn the trend and the dynamics in the information queue. Through our simulations, we show that our neural network-based method is better than the conventional method.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

模糊控制及其在开关磁阻电动机控制中的应用

对常规的模糊控制器的设计进行了分析研究。以提高系统精度为目的,简单实用为原则,设计了模糊PID控制器。仿真结果表明,所设计的模糊PID控制器大大提高了系统的控制精度,加快了系统的响应特性,可以做到理论上无静差,明显优于常规的模糊控制器。最后把设计的模糊PID控制器应用到开关磁阻电动机调速系统中,经过反复实际调整,确定了一组合适的量化因子的数值,这对量化因子使用理论值来说是个突破。同时实验结果表明,文中设计模糊PID控制算法不但可行,且效果很好,已在实际中得到成功的应用。     

永磁同步电机中混沌现象的滑模变结构控制

研究了具光滑气隙永磁同步电动机的数学建模问题,对永磁同步电机的动态模型分析表明,在某种条件下,系统存在混沌行为。为了消除这种不期望的混沌振荡,设计滑模变结构控制器将系统混沌状态调整到吸引子域中平衡点。仿真实验结果证实所设计的控制策略极为有效。     

Asynchronous measurement and control: a case study on motor synchronization

The synchronization between two electrical motors (master and slave) is studied. To reduce the costs of the master–slave combination, the slave motor is mounted with a very low-resolution encoder (one pulse per revolution). Since the position measurements are asynchronous in time, standard control and analysis techniques are not applicable. Two methods are proposed to deal with these cheap, low-resolution encoders: the hybrid and the asynchronous control scheme. The presented controllers are successfully tested on a real industrial master-multi-slave system as is used for mailing machines.     

Planning,scheduling and dispatching tasks in production control

"What is the difference between planning and scheduling?" Production control encompasses many tasks performed by humans, three of which are planning, scheduling, and dispatching. In the past, the only criterion that could distinguish between the tasks was that planning is usually on a higher level than scheduling and scheduling is on a higher level than dispatching. Hence, the tasks are often ambiguous, unclear, and subject to speculation. There are few formal studies on the actual tasks of planning, scheduling, and dispatching, and there are no known studies that compare or discuss all three. In this paper it is argued that it is important to understand the differences between the tasks. An action science and ethnographic case study is presented as the empirical basis for the discussion, and the implications for decision support systems in production control tasks are presented.     

Towards models of tasks and task complexity in supervisory control applications

Dynamic task environments in supervisory control situations differ from those traditionally investigated in problem-solving research in that (1) several task goals exist in parallel, (2) task goals change dynamically as die behaviour of the technical process changes, and (3) information required to accomplish task goals changes across time. In the present work, it is suggested that such dynamic task environments can be described using two types of task goal networks, namely a control task goal (CTG) network and an information processing goal (IPG) network. CTG networks are generated by analysis of the operational states required to produce the commodity for which a technical system has been designed. For example, such analyses can be performed using approaches such as Mitchell's operator function model or canonical means-end analyses. IPG networks are generated by using the recenUy proposed functional information and knowledge acquisition (FIKA) modelling technique. Two examples from different domains illustrate how these task goal networks can be used to describe dynamic task environments. Finally, two different ways of using the task modelling approach are briefly discussed.     

机器人辅助椎板切除的骨铣削状态感知与运动控制

本文旨在提高机器人辅助椎板切除时的骨铣削操作安全性.首先,提出一种基于激光信号和线性自抗扰控制器的铣削深度监测与控制方法,辨识了机器人的位置控制传递函数,并通过分析椎板的铣削力、受迫振动和铣削过程,给出基于骨铣削声信号的铣削进给速度优化原理.然后使用基于带通滤波器和普罗尼算法的声信号处理方法,用于手术动力装置主轴旋转频...     

Extracting DC bus current information for optimal phase correction and current ripple in sensorless brushless DC motor drive

Brushless DC motor （BLDCM） sensorless driving technology is becoming increasingly established. However, op- timal phase correction still relies on complex calculations or algorithms. In finding the correct commutation point, the problem of phase lag is introduced. In this paper, we extract DC bus current information for auto-calibrating the phase shift to obtain the correct commutation point and optimize the control ofBLDC sensorless driving. As we capture only DC bus current information, the original shunt resistor is used in the BLDCM driver and there is no need to add further current sensor components. Software processing using only simple arithmetic operations successfully accomplishes the phase correction. Experimental results show that the proposed method can operate accurately and stably at low or high speed, with light or heavy load, and is suitable for practical applications. This approach will not increase cost but will achieve the best performance/cost ratio and meet market expectations.     

Adaptation and learning in control of voluntary movement by the central nervous system

In order to control voluntary movements, the central nervous system must solve the following three computational problems at different levels: (1) the determination of a desired trajectory in visual coordinates; (2) the transformation of its coordinates into body coordinates; and (3) the generation of motor command. Concerning these problems, relevant experimental observations obtained in the field of neuroscience are briefly reviewed. On the basis of physiological information and previous models, we propose computational theories and a neural network model which account for these three problems. (1) A minimum torque-change model which predicts a wide range of trajectories in human multi-joint arm movements is proposed as a computational model for trajectory formation. (2) An iterative learning scheme is presented as an algorithm which solves the coordinate transformation and the control problem simultaneously. This algorithm can be regarded as a Newton-like method in function spaces. (3) A neural network model for generation of motor command is proposed. This model contains internal neural models of the motor system and its inverse system. The inverse-dynamics model is acquired by heterosynaptic plasticity using a feedback motor command (torque) as an error signal. The hierarchical arrangement of these neural networks and their global control are discussed. Their applications to robotics are also discussed.     

On low frequency and long-run effects in self-tuning control

Long-term performance of self-tuning controllers is analysed for low frequency disturbance corrupted single input-single output systems described by five variants of the linear difference equation model. Having the drifts classified, the appropriate models to allow for drift effects are specified and standard recursive least squares parameter estimation schemes are applied. Optimal single-stage control strategies are comparatively analysed both from the steady-state accuracy and stability points of view. As a result, an ‘extended self-tuning controller’ is developed and its superiority over classical ones is demonstrated. The related problem of ‘blow-up’ protection for self-tuning controllers is also investigated and some effective measures are proposed.     

Novel approaches to control multiple tasks in redundant manipulators: stability analysis and performance evaluation

In this paper, two new approaches for handling multiple tasks in redundant manipulators based on predefined allocated priorities are proposed. The first approach is an integrated scheme which employs null-space base vector for handling prioritized tasks. Clear task and null-space representation, better execution of the lower priority tasks, and intuitive formulation are its basic features. The second approach aims to improve the performance of all the prioritized tasks, especially during algorithmic singularities beside clear null-space dynamics representation. This approach can be considered as a modification and extension of the Reverse Priority (RP) algorithm in acceleration level. The commands related to each tasks are added to each other following reverse order of priorities and by suitable projectors. The projector definition is given using minimal representation of the null-space. Clear null-space dynamics in the proposed methods facilitate the stability analysis. A detailed evaluation by means of computer simulation in various cases is reported. Tasks accomplishment using the proposed approaches is compared with the classic method. The results, in general, show higher performance and accuracy of the tasks by the proposed approaches.     

Extraction and implementation of muscle synergies in neuro-mechanical control of upper limb movement

This work faces the redundancy problem, a central concern in robotics, in a particular force-producing task by using muscle synergies to simplify the control. We extracted muscle synergies from human electromyograph signals and interpreted the physical meaning of the identified muscle synergies. Based on the human analysis results, we hypothesized a novel control framework that can explain the mechanism of the human motor control. The framework was tested in controlling a pneumatic-driven robotic arm to perform a reaching task. This control method, which uses only two synergies as manipulated variables for driving antagonistic pneumatic artificial muscles to generate desired movements, would be useful to deal with the redundancy problem; thus, suggesting a simple but efficient control for human-like robots to work safely and compliantly with humans.     

李群平均方法在单轮姿态和运动控制中的应用

针对一个单轮系统,采用欧拉群描述其位形空间,对于Wei-Norman方程中不能精确求解的参数,采用平均方法对其进行近似计算,从而使被控系统在满足李代数可控性秩条件下,在李群上的平均轨迹能以一定的精度逼近真实轨迹.通过对单轮系统的仿真实验与结果分析,证明了所用方法的有效性,并指出该方法更适合驱动一类量子力学系统的状态.     

分布式运动控制系统HSSL通信设计与实现

为了满足强实时性分布式运动控制系统中多处理器高速互连的要求,设计了一种使用光纤作为通信介质的高速串行链路(HSSL)通信解决方案,详细描述了HSSL的物理层结构、传输层和应用层协议以及FPGA编程实现的方法。该通信方案已经在步进扫描光刻机研制项目中得到成功应用,实践证明其具有可靠性高、协议开销小、抗电磁干扰能力强、编程容易等优点。     

Dual adaptive control and uncertainty effects in macroeconomic systems optimization

A method is presented for the quantitative assessment of the effects of uncertainty in macroeconomic policy optimization problems. Both parameter and measurement uncertainties are considered. The method derives from an application of adaptive dual control theory which decomposes the optimal loss function into three components: deterministic, cautionary, and probing. This characterizes the welfare loss due to uncertainty and permits the study of the relative importance of caution and probing in selecting the optimal policy instruments. An interesting illustration of the method is given for two macroeconometric models derived from the same data, but each with a different level of uncertainty.     

Altitude control in simulated flight using 3‐D objects and terrain texture

Abstract— In this study, the effects of manipulating the properties of 3‐D objects and terrain texture on the control of altitude in simulated flight has been investigated. 3‐D objects were found to be as effective as terrain texture for controlling altitude, and this result was interpreted as suggesting that both terrain texture and 3‐D objects can serve as effective carriers of information about motion parallax and optical expansion and contraction. The present results, which were obtained using a vertically defined flight task, are inconsistent with the findings of Patterson et al., who reported that 3‐D objects were more effective than terrain texture for controlling a horizontally defined heading task. The present results indicate that, when terrain texture is present, the motion parallax or optical expansion associated with the presence of 3‐D objects does not improve altitude control.     

变频调速控制系统中电机功率参数的实时测量

对单极性三相PWM逆变器供电的交流异步电机的基波功率参数的测量问题进行了探讨。通过先检测瞬时功率．再用数值积分的方法得到平均功率，据此求出PWM逆变器供电方式下电机的实时功率参数。     

Design and evaluation of an actuated exoskeleton for examining motor control in stroke thumb

Chronic hand impairment is common following stroke. This paper presents an actuated thumb exoskeleton (ATX) to facilitate research in examining motor control and hand rehabilitation. The ATX presented in this work aims to provide independent bi-directional actuation in each of the 5 degrees of freedom (DOF) of the thumb using a novel flexible shaft-based mechanism that has 5 active DOF and 3 passive DOF. A prototype has been built and experiments have been conducted to measure the allowable workspace at the thumb and evaluate the kinematic and kinetic performance of the ATX. The experimental results show that the ATX is able to provide individual actuation at all five thumb joints with high joint velocity and torque capacities. Further improvement and future work are discussed.     

Cooperative control of multiple surface vessels in the presence of ocean currents and parametric model uncertainty

This paper addresses the problem of cooperative path‐following of multiple autonomous vehicles. Stated briefly, the problem consists of steering a group of vehicles along specified paths while keeping a desired spatial formation. For a given class of autonomous surface vessels, it is shown how Lyapunov‐based techniques and graph theory can be brought together to design a decentralized control structure, where the vehicle dynamics and the constraints imposed by the topology of the inter‐vehicle communication network are explicitly taken into account. To achieve path‐following for each vehicle, a nonlinear adaptive controller is designed that yields convergence of the trajectories of the closed‐loop system to the path in the presence of constant unknown ocean currents and parametric model uncertainty. The controller derived implicitly compensates for the effect of the ocean current without the need for direct measurements of its velocity. Vehicle cooperation is achieved by adjusting the speed of each vehicle along its path according to information exchanged on the positions of a subset of the other vehicles, as determined by the communication topology adopted. Global stability and convergence of the closed‐loop system are guaranteed. Illustrative examples are presented and discussed. Copyright © 2009 John Wiley & Sons, Ltd.