Robust controller with disturbance rejection for hydraulic servosystems

A controller is presented that improves the performance and reduces the sensitivity of hydraulic servo systems in the presence of parameter variations, nonlinear effects, and other disturbances. The control system has enhanced closed-loop stability and can recover from steady-state and transient error quickly and completely. It consists of a servo controller, an auxiliary controller, and a robust controller. Simulation and experimental results demonstrate the validity of the controller     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

A conditional classification recurrent RBM for improved series mid-term forecasting

In the context of human-robot and robot-robot interactions, the better cooperation can be achieved by predicting the other party’s subsequent actions based on the current action of the other party. The time duration for adjustment is not sufficient provided by short term forecasting models to robots. A longer duration can by achieved by mid-term forecasting. But the mid-term forecasting models introduce the previous errors into the follow-up forecasting and amplified gradually, eventually invalidating the forecasting. A new mid-term forecasting with error suppression based on restricted Boltzmann machine(RBM) is proposed in this paper. The proposed model can suppress the error amplification by replacing the previous inputs with their features, which are retrieved by a deep belief network(DBN). Furthermore, a new mechanism is proposed to decide whether the forecasting result is accepted or not. The model is evaluated with several datasets. The reported experiments demonstrate the superior performance of the proposed model compared to the state-of-the-art approaches.

     

Incorporating Actor-Critic in Monte Carlo tree search for symbolic regression

Neural Computing and Applications - Most traditional genetic programming methods that handle symbolic regression are random algorithms without memory and direction. They repeatedly search for the...     

A steel surface defect inspection approach towards smart industrial monitoring

Journal of Intelligent Manufacturing - With the advance in Industry 4.0, smart industrial monitoring has been proposed to timely discover faults and defects in industrial processes. Steel is widely...     

混沌信号的主要测量特性分析

初步分析了混沌信号(以Logistic为例)应用于测量中的主要特性。仿真分析了Logistic信号的频谱特性、相关特性、模糊函数。说明了混沌信号在具有较高的距离速度分辨力,同时具备强抗干扰性。对比分析了混沌码和伪随机码的多普勒容限能力。初步分析Logistic信号的抗干扰特性。     

Effect of supports on the redox performance of pyrite cinder in chemical looping combustion

Chemical looping combustion (CLC) is a clean and efficient flame-free combustion technology,which combust the fuels by lattice oxygen from a solid oxygen carrier with inherent CO2 capture.The develop-ment of oxygen carriers with low cost and high redox performance is crucial to the whole efficiency of CLC process.As the solid by-product from the sulfuric acid production,pyrite cinder presented excellent redox performance as an oxygen carrier in CLC process.The main components in pyrite cinder are Fe2O3,CaSO4,Al2O3 and SiO2 in which Fe2O3 is the active component to provide lattice oxygen.In order to sys-tematic investigate the functions of supports (CaSO4,Al2O3 and SiO2) in pyrite cinder,three oxygen car-riers (Fe2O3-CaSO4,Fe2O3-Al2O3 and Fe2O3-SiO2) were prepared and evaluated in this study.The results showed that Fe2O3-CaSO4 displayed high redox activity and cycling stability in the multiple redox cycles.However,both Fe2O3-Al2O3 and Fe2O3-SiO2 experienced serious deactivation during redox reactions.It indicated that the inert Fe-Si solid solution (Fe2SiO4) was formed in the spent Fe2O3-SiO2 sample,which decreased the oxygen carrying capacity of this sample.The XPS results showed that the oxygen species on the surface of Fe2O3-CaSO4 could be fully recovered after the 20 redox cycles.It can be concluded that CaSO4 is the key to the high redox activity and cycling stability of pyrite cinder.     

CHARAC TERIZATION OF TiAl POWDER PRODUCED BY MECHANICAL ALLOYING

The microstructure,alloying reaction and sintering behavior of the powder produced by Mechanical Al-loying(MA)for 8 h from 64 wt.-% Ti powder and 36 wt.-% Al powder were studied by scanning electronmicroscopy,optical microscopy,X-ray diffractometry,differential scanning calorimetry(DSC)and dilatometry.The mechanically alloyed powder partictes are Ti-Al composite particles.Thus,titanium aluminides can formeasily in the powder through diffusion during heat treatment.It is shown that the sintering behavior of this pow-der,different from the behaviors of TiAl alloy powder and mixed powder of 64 wt.-% Ti powder and 36 wt.-%Al powder,changes from expansion at temperatures below 1000℃ to shrinkage at temperatures above 1000℃.Homogeneously alloyed TiAl material with a density over 96% of the theoretical density can be produced fromthe mechanically alloyed powder by compaction-sintering.