基于参数解耦陷波滤波器的工业机器人末端振动抑制

六自由度工业机器人关节因传动装置刚度不足而引发末端振动,通常采用传统陷波滤波器解决该问题;但滤波器参数之间存在耦合,导致滤波器参数难以快速整定。为此,基于所建立的工业机器人双惯量负载模型设计出具有参数解耦的陷波滤波器。分析传统陷波滤波器传递函数,采用极点零点抵消法对陷波器参数进行解耦设计;将陷波器中心频率、宽度以及深度作为陷波滤波器的参数;最后,利用傅里叶变换和对数衰减法快速整定改进后的陷波器参数,以此来抑制工业机器人末端振动。搭建六自由度工业机器人实验平台进行实验。结果表明:参数解耦陷波滤波器不存在参数耦合,参数整定方便;使用参数解耦滤波器比未使用滤波器相比可降低78.5%的工业机器人定位振动,证明改进的参数解耦陷波滤波器对定位振动抑制的可行性与有效性。     

气辅成型中成型工艺对制品翘曲的影响

对气辅成型制品翘曲缺陷采用正交实验方法和数值模拟方法进行了研究。研究了气体注射延迟时间与气体注射压力及气体注射时间与气体注射压力两对工艺参数的交互作用对制品翘曲缺陷的影响。结果表明,对制品翘曲影响最为严重的是气体注射时间与气体注射压力的交互作用。较长的延时可以减轻制品翘曲的程度,但气体无法穿透或穿透不足等问题也是延时过长会造成的,因此选择合适的气体注射时间与气体注射压力以及气体延时组合非常重要。     

基于Root MUSIC法的轧辊偏心参数估计

针对轧辊偏心信号是混杂在各种随机干扰中的复杂高频周期信号,因FFT法对信号分析的局限性,提出了一种Root MUSIC(Multiple Signal Classification)法和Prony法相结合的轧辊偏心信号估计新方法。利用Root MUSIC法准确估计出偏心谐波的频率及谐波的个数,同时使用Prony方法估计出偏心信号的各次谐波幅值和相位。仿真结果验证了可行性和有效性,在信噪比较低的情况下仍能准确地同时估计出偏心谐波的频率、幅值及相位,尤其在频率分辨率和抗噪声上比FFT法具有优越性     

State-led technological innovation of domestic firms in Shenzhen,China: Evidence from liquid crystal display (LCD) industry

Since 2000, particularly in the aftermath of the global financial crisis, there has emerged revisit of the role of the state in technological upgrading of latecomer cities and regions in developing countries, including China. The effectiveness of a technological innovation strategy driven by transnational corporations (TNCs) has been questioned, despite its significant contribution to rapid industrialization via strategic coupling in the global production networks (GPNs). There has been a paradigm shift of innovation policy towards indigenous innovation through state-led explicit coupling of designated domestic firms and lead firms in the GPNs. The practice of this remains understudied, however. By examining the development of the liquid crystal display (LCD) industry, one of the strategic emerging industries (SEIs) in Shenzhen, this paper sheds light on the collective roles of various state authorities ranging from the central to provincial and municipal governments in fostering technological innovation of domestic firms (e.g. CSOT) through explicit coupling with global lead firms (e.g. Samsung). The empirical experience in Shenzhen indicates that indigenous innovation focused on domestic firms may unnecessarily exclude the participation of TNCs. This study urges more research to examine the changing dynamics of technological catch-up of domestic firms in an increasingly globalized and uncertain world economy.     

Robust numerical approach to steady-state calibration of mean-value models

A numerically robust approach to steady-state calibration of nonlinear dynamic models is presented. The approach is based on explicit formulation of the constraints on validity of internal model signals by set of inequalities. The constrained optimization with feasible iterates guarantees that the model will never be evaluated with invalid internal signals. This overcomes numerical difficulties often encountered when dealing with highly nonlinear models. Because the approach uses a large number of slack variables, distributed least squares algorithm is proposed. The robustness of this approach is demonstrated on a steady-state calibration of turbocharged diesel engine model starting from grossly inaccurate initial estimates.     

Identifying technology innovations for marginalized smallholders-A conceptual approach

This paper adds a contribution in the existing literature in terms of theoretical and conceptual background for the identification of idle potentials of marginal rural areas and people by means of technological and institutional innovations. The approach follows ex-ante assessment for identifying suitable technology and institutional innovations for marginalized smallholders in marginal areas-divided into three main parts (mapping, surveying and evaluating) and several steps. Finally, it contributes to the inclusion of marginalized smallholders by an improved way of understanding the interactions between technology needs, farming systems, ecological resources and poverty characteristics in the different segments of the poor, and to link these insights with productivity enhancing technologies.     

Strengthening the resilience of small-scale fisheries: A modeling approach to explore the use of in-shore pelagic resources in Melanesia

Small-scale fisheries play a critical role in both poverty alleviation and food security. A large proportion of the world fish stocks are, however, getting fully or over-exploited. In this article we address these issues in the context of the small-scale fisheries of the Solomon Islands. The paper explores the extent to which in-shore Fish Aggregating Devices (FADs) can help increasing the resilience of the small scale fishery system and reconciling social, economic and ecological priorities. Based on the concept of ‘time of crisis’ developed recently in the viability literature, we propose to calculate a resilience index through a dynamic stochastic model calibrated by ethnological observations. The resilience index calculation reveals two major findings: (i) the resilience of the small scale fishery system is currently nonexistent and (ii) the introduction of FADs can improve it. The effects of the FADs' implementation are then discussed in the light of a socio-economic perspective. Such results bring new insights into the question of the future of the small scale fishery sector, especially in relation to the local economy evolution from a barter dominance to a cash oriented economy. At the same time, the current subsistence fisheries seems more resilient in general due to a distributive effects which ease the ‘race for fish behaviors’. Finally, our analysis reveals that while the FADs implementation stands as a short and mid-term answer, demographic drivers are important and other alternatives will need to be considered if the overall viability of the system is to be maintained in the longer-term.     

Adaptive backstepping control for an n-degree of freedom robotic manipulator based on combined state augmentation

The aim of this paper is to improve the tracking performance of a robotic manipulator by designing an adaptive controller and implementing it on the system. The proposed controller guarantees the system stability as well as good tracking performance in existence of nonlinearity and parameter uncertainties. The requirement to decrease the system response overshoot and steady state error as well as increasing speed of tracking for manipulators is essential to many manufacturers. To this mean, in this paper, the tracking error equations for an n-DOF manipulator are derived and the response characteristics are improved by augmenting a new state to the system equations. The stability of the closed-loop system is guaranteed based on the Lyapunov theory via backstepping control approach. The robotic manipulator model contains parametric uncertainties and many of the parameter values are unknown. To solve the problem, an adaption law is proposed via adaptive backstepping mechanism. Different experiments are carried out for a 2-DOF manipulator to show the effectiveness of the proposed approach and the results are compared with four of the recently revealed researches on control. Experimental results present the superiority of the state augmented adaptive backstepping in tracking the desired joint angles. Moreover, in order to present the industrial application of the proposed control method, it is simulated for a large industrial Scara manipulator.     

Parameter estimation for a morphochemical reaction-diffusion model of electrochemical pattern formation

The process of electrodeposition can be described in terms of a reaction-diffusion partial differential equation (PDE) system that models the dynamics of the morphology profile and the chemical composition. Here we fit such a model to the different patterns present in a range of electrodeposited and electrochemically modified alloys using PDE constrained optimization. Experiments with simulated data show how the parameter space of the model can be divided into zones corresponding to the different physical patterns by examining the structure of an appropriate cost function. We then use real data to demonstrate how numerical optimization of the cost function can allow the model to fit the rich variety of patterns arising in experiments. The computational technique developed provides a potential tool for tuning experimental parameters to produce desired patterns.     

Backtracking search optimization heuristics for nonlinear Hammerstein controlled auto regressive auto regressive systems

In this work, novel application of evolutionary computational heuristics is presented for parameter identification problem of nonlinear Hammerstein controlled auto regressive auto regressive (NHCARAR) systems through global search competency of backtracking search algorithm (BSA), differential evolution (DE) and genetic algorithms (GAs). The mean squared error metric is used for the fitness function of NHCARAR system based on difference between actual and approximated design variables. Optimization of the cost function is conducted with BSA for NHCARAR model by varying degrees of freedom and noise variances. To verify and validate the worth of the presented scheme, comparative studies are carried out with its counterparts DE and GAs through statistical observations by means of weight deviation factor, root of mean squared error, and Thiel’s inequality coefficient as well as complexity measures.