Robust control of variable speed autonomous underwater vehicle

Set point tracking control of autonomous underwater vehicle (AUV) via robust model predictive control (RMPC) is considered. Input-constrained RMPC with integral action, which has been developed in our previous work, is used to control the AUV in this study. In order to derive a RMPC control rule, non-linear dynamics of AUV with six degree of freedom is linearized at certain operating points. So, horizontal and vertical plane dynamics of system are represented by linear models which have polytopic uncertainties. Since the derived control rule will be used in real time, the computation time should be reduced. To overcome this computational time problem and get rid of trial–error step of Algorithm 1, a new algorithm is proposed here. The simulations are carried out using the control rule based on this algorithm and these results are presented.     

Human tracking system based on adaptive multi-feature mean-shift for robot under the double-layer locating mechanism

Human tracking has been a challenging task for robot in the past decades. In this paper, to realize the human following in a cluttered environment, a human tracking system based on adaptive multi-feature mean-shift (AMF-MS) under the double-layer locating mechanism (DLLM) is proposed to solve the problem of distinguishing target, occlusion, and quick turning. The DLLM, considering the course location processing and fine location processing, is designed to estimate the person’s position using the fusion of heterogeneous data. As an ID tag attached on target can be detected by RF antennas, the course locating method can track the target easily and quickly. The Bayes rule is introduced to calculate the probability where the tag exists due to the instability of RF signals. In the fine locating step, the AMF-MS is proposed because it can reduce computational load and represent target by multi-feature histogram function. Meanwhile, we combine extended Kalman filter and AMF-MS to overcome MS’s inability of occlusion. To control the robot following the target person precisely, an intelligent gear shift strategy based on fuzzy control is implemented by analyzing the robot structure. Experiments demonstrate that the proposed approach is robust to handle complex tracking conditions, and show the system has an optimum performance.     

Model reference adaptive impedance control in Cartesian coordinates for physical human–robot interaction

In this paper, a nonlinear model reference adaptive impedance controller is proposed and tested. The controller provides asymptotic tracking of a reference impedance model for the robot end-effector in Cartesian coordinates applicable to rehabilitation robotics or any other human–robot interactions such as haptic systems. The controller uses the parameters of a desired stable reference model which is the target impedance for the robot’s end-effector. It also considers uncertainties in the model parameters of the robot. The asymptotic tracking is proven using Lyapunov stability theorem. Moreover, the adaptation law is proposed in joint space for reducing the complexity of its calculations; however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations and experiments on a two DOFs robot, the effectiveness of the proposed controller is investigated.     

Noncertainty equivalent adaptive control of robot manipulators without velocity measurements

This paper presents a noncertainty equivalent adaptive motion control scheme for robot manipulators in the absence of link velocity measurements. A new output feedback adaptation algorithm, based on the attractive manifold design approach, is developed. A proportional-integral adaptation is selected for the adaptive parameter estimator to strengthen the passivity of the system. In order to relieve velocity measurements, an observer is designed to estimate the velocities. The controller guarantees semiglobal asymptotic motion tracking and velocity estimation, as well as L_∞ and L₂ bounded parameter estimation error. The effectiveness of the proposed controller is verified by simulations for a two-link robot manipulator and a four-bar linkage. The results are further compared with the earlier certainty-equivalent adaptive partial and full state feedback controller to highlight potential closed-loop performance improvements.     

Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control

Introduction

Hyperglycaemia is a common complication of stress and prematurity in extremely low-birth-weight infants. Model-based insulin therapy protocols have the ability to safely improve glycaemic control for this group. Estimating non-insulin-mediated brain glucose uptake by the central nervous system in these models is typically done using population-based body weight models, which may not be ideal.

Method

A head circumference-based model that separately treats small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) infants is compared to a body weight model in a retrospective analysis of 48 patients with a median birth weight of 750 g and median gestational age of 25 weeks. Estimated brain mass, model-based insulin sensitivity (S_I) profiles, and projected glycaemic control outcomes are investigated. SGA infants (5) are also analyzed as a separate cohort.

Results

Across the entire cohort, estimated brain mass deviated by a median 10% between models, with a per-patient median difference in S_I of 3.5%. For the SGA group, brain mass deviation was 42%, and per-patient S_I deviation 13.7%. In virtual trials, 87–93% of recommended insulin rates were equal or slightly reduced (Δ < 0.16 mU/h) under the head circumference method, while glycaemic control outcomes showed little change.

Conclusion

The results suggest that body weight methods are not as accurate as head circumference methods. Head circumference-based estimates may offer improved modelling accuracy and a small reduction in insulin administration, particularly for SGA infants.     

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.     

基于磁流变阻尼器的车辆悬架系统模糊半主动控制

在对磁流变液和磁流变阻尼器的研究基础上 ,以磁流变阻尼器作为半主动控制元件组成模糊半主动悬架系统。运用数值仿真和试验研究等方法对基于磁流变阻尼器的模糊半主动悬架进行了研究。数值仿真和试验结果表明 ,设计的模糊半主动控制算法可对基于磁流变阻尼器的半主动控制悬架实现有效的控制     

Evaluation of hydraulic excavator Human–Machine Interface concepts using NASA TLX

This study evaluated newly proposed Human–Machine Interface (HMI) design concepts for improving the ergonomics of hydraulic excavators. The design concepts were based on an augmented interaction technique which involved the use of heads-up display (HUD) and coordinated control as HMI elements. Two alternative HMI designs were elaborated in order to separately evaluate the ergonomic impacts of the head-up display and the coordinated control by comparing them to the standard HMI design. The effectiveness of these three HMI designs in terms of the reduction of the operators' mental and physical workload were assessed by conducting experiments utilizing human subjects, ages 23–35 years. The National Aeronautics and Space Administration's Task Load Index (NASA TLX) method was used for collecting subjective workload scores based on a weighted average of ratings of six factors: Mental Demand, Physical Demand, Temporal Demand, Own Performance, Effort, and Frustration Level. The results showed that the type of HMI design affects different aspects of the operator's workload. Indeed, it showed how the proposed augmented interaction is an effective solution for reducing the ergonomic gaps in terms of mental workload, and to a lesser extent the physical workload, subjected by the standard HMI design.     

THE EFFECT OF OPERATING VARIABLES ON THE DYNAMICS OF CATALYTIC CRACKING PROCESSES

The dynamic Characteristics of a Fluidized Catalytic Cracking Process are examined over a wide range of operating conditions. A novel Order of Magnitude Approach is introduced to successfully provide physical insight into the cause and effect relationship between operating conditions and dynamic characteristics. It is shown that the original five-dimensional dynamic model is characterized by three fast time constants and two slow ones that dominate the dynamic responses. The two most important time constants are expressed as explicit functions of the operating conditions. These formulas correctly indicate in which parameter regions the open loop response is oscillatory (underdamped) or nonoscillatory (overdamped). Extensive process variables, that are either flow or capacity, related are defined in order to provide an approximate physical meaning for the dynamic modes of the system. It is shown that the two slow modes of the process are related to the enthalpy content of the regenerator and the sensible heat content of the catalyst phase in both the reactor and regenerator.     

格灵化工基于SmartPro的DCS系统设计与应用

介绍北京和利时公司开发的SmartPro MACS Ⅲ型DCS系统在格灵化工硫酸装置中的应用.DCS系统包括硬件组成、软件设计及控制功能实现.该控制系统稳定可靠、控制精度高.在提高生产装置自动化水平的同时,使硫酸产品质量提高,生产成本大幅度降低.