Abstract. Emission inversion using data assimilation fundamentally relies on having the correct assumptions on the emission background error covariance. A perfect covariance accounts for the uncertainty based on prior knowledge, and is able to explain differences between model simulations and observations. In practice, emission uncertainties are constructed empirically, hence a partially unrepresentative covariance is unavoidable. Concerning its complex parameterization, dust emissions are a typical example where the uncertainty could be induced from many underlying inputs, e.g., information on soil composition and moisture, landcover and erosive wind velocity, and these can hardly be taken into account together. This paper describes how an adjoint model can be used to detect errors in the emission uncertainty assumptions. This adjoint based sensitivity method could serve as a supplement of a data assimilation inverse modeling system to trace back the error sources, in case that large observation-minus-simulation residues remain after assimilation based on empirical background covariance. The method follows on application of a data assimilation emission inversion for an extreme severe dust storm over East Asia (Jin et al., 2019b). The assimilation system successfully resolved observation-minus-simulation errors using satellite AOD observations in most of the dust-affected regions. However, a large underestimation of dust in northeast China remained despite the fact the assimilated measurements indicated severe dust plumes there. An adjoint implementation of our dust simulation model is then used to detect the most likely source region for these unresolved dust loads. The backward modeling points to the Horqin desert as source region, which was indicated as a non-source region by the existing emission scheme. The reference emission and uncertainty are then reconstructed over the Horqin desert by assuming higher surface erodibility. After the emission reconstruction, the emission inversion is performed again and the posterior dust simulations and reality are now in much closer harmony. Based on our results, it is advised that emission sources in dust transport models include Horqin desert as a more active source region.

In the design process of lightweight harmonic drive system, low-frequency resonance generally affects controller design, and restricts system servo performance. In the design stage of system, it has great significance that the resonant frequencies and dynamic performances could be predicted. This paper presents a modeling method of harmonic drive system which has low-frequency resonance. Takes an uniaxial harmonic drive system as example to describe the implementation process of the modeling method. The dynamics model of harmonic drive system has been built. Using Ansys, Recurdyn and Matlab, the rigid-flexible coupling dynamics simulation model of system has been established. The simulation model analysis and the actual system experiment have been done respectively. Comparing the simulation and experiment results, it shows that: the open-loop time-frequency domain characteristics and the structural modals of simulation and experiment results are basically consistent. Using this method, the resonant frequency and dynamic performance of harmonic drive system can be predicted in the system design stage, and improve design efficiency.

In modern mechatronic system design process, how to shorten the design schedule and to ensure that the performance of the system designed to meet the indicator has been the focus of attention. This paper presents a mechatronic system co-designing method based on Matlab and Recurdyn. Takes a typical uniaxial direct drive system as example, describes the implementation process of the co-designing method. The dynamics model of direct drive system has been builded, on this basis, the co-simulation model based on Matlab and Recurdyn has been established. Simulates and analyzes time domain and frequency domain characteristics of the co-simulation model in different conditions, and compares simulation results and corresponding experiment results. Comparison results showed that: Open-loop time-frequency domain simulation results and experimental results are basically consistent, amplitude-frequency characteristics matching degree (ACMD) greater than 73%, phase frequency characteristics matching degree (PCMD) greater than 87%, time domain response matching degree (TRMD) greater than 89%. It verifies the validity and correctness of the co-designing method.

A CPLD-based Photoelectric encoder that measures angle and angular velocity was designed aiming at precise requirements on angle and angular velocity measures in photo-electric servo system. Based on the work principle of photoelectric encoder, a segmented velocity-measure algorithm based on different measure time intervals was presented, and the concrete process in the environment of Isplever Project Navigator was detailed described. Finally, DSP processor TMS320F2812 and CPLD chip LC4512V-75T176 were used for verification. The result showed that this circuit has the features of realization-simple, high measure precision and reliability as well as good commonality. It will lay a solid foundation for the realization of photoelectric servo system’s digital control.

A composite control scheme is proposed to solve the problems of friction toque and carrier disturbance lag in the stabilized loop of inertial stabilized platform. Based on analysis of composite control structure, the performance of single rate loop, double rate loop and composite control in the inhibition of carrier disturbance, friction torque and sensor noise are compared. In order to further verify the composite control method, an experimental setup is built. The experimental results show that: when the disturbance is 1deg-1Hz sinusoidal signal, the peak value of residual error of the single rate loop is 0.055 deg, the double rate loop is 0.031deg, and the composite control is the 0.0188deg, so the performance of isolation carrier disturbance of platform is effectively improved.