Search

Deadbeat predictive control (DBPC) requires accurate model parameters in its application, therefore it is difficult to use DBPC for surface mounted permanent magnet synchronous motor (SPMSM) with uncertain motor parameters. As a solution, this paper proposes a strategy to obtain the needed parameters, and then uses them to achieve DBPC on SPMSMs whose parameters are unknown. A detailed investigation on parameter sensitivity of DBPC is presented, and attention is paid to different influences between the incremental inductance and the apparent inductance. On this basis, parameter configurations in the DBPC are suggested. And novel current-controller-free self-commissioning schemes are proposed to identify the stator resistance together with the stator inductances under different magnetic saturation levels. Compared with existing commissioning schemes that do not depend on current controllers, solutions for commissioning voltage auto-tuning is provided. So the methods are able to automatically decide the amplitudes of the injected voltage for a given motor, and achieve a controllable current feedback during the commissioning. This brings significant convenience for the inductance identification at a specific saturation level. Moreover, the inverter nonlinearity compensation is not needed but still, identification accuracy can be guaranteed. The feasibility and effectiveness of the proposed method are confirmed by the achieved DBPC and the corresponding current tracking performances on two different SPMSMs.

An obstacle avoidance and path planning algorithm for a multi-joint manipulator in a space robot is presented in this paper. In this paper, the end-effector of the manipulator is used to capture some special target in a space environment with obstacles. To ensure the safety of the operation, a collision-free path from the initial position to the target position is essential. Therefore, an obstacle avoidance and path planning algorithm based on the Rapidly-Exploring Random Tree (RRT) algorithm and the Forward and Backward Reaching Inverse Kinematics (FABRIK) algorithm is presented in this paper. First, a path planning algorithm based on the Rapidly-Exploring Random Tree (RRT) algorithm is designed for the multi-joint manipulator. Further, a method to generate a random point by artificial guidance is introduced for a higher searching speed. The RRT algorithm can effectively explore the entire workspace and find a feasible path without collision for the end-effector. To calculate the positions of each joint, the Forward and Backward Reaching Inverse Kinematics (FABRIK) algorithm is introduced and improved for the problem of inverse kinematics. The FABRIK algorithm avoids the use of rotational angles or matrices, and instead finds each joint position by locating a point on a line, and thus, it has a low computational cost. Therefore, the improved obstacle avoidance and path planning algorithm can quickly plan a feasible path for the multi-joint manipulator in a space environment with obstacles. A numerical simulation is carried out to analyze the proposed obstacle avoidance and path planning method. It is observed that the method finds a feasible path without collision for the multi-joint manipulator with a low computational cost. These results validated the effectiveness of the proposed method for path planning to avoid the obstacles.

This work put forward an analysis of the spectrum characteristics of deep water ambient noise in the West Pacific, in terms of depth dependence and the relationship to temperature, based on the experimental data obtained in the autumn of 2020. The results illustrate that the ambient noise is higher in the morning than the afternoon and evening; the minimum noise level is about 10dB and 40dB lower than the mean and maximum noise level; the mean standard deviation of noise level higher than 1kHz is about 6.3dB during the measurement.

As a potential solution to the “Energy Hole” problem of Wireless Sensor Networks (WSNs), UAV-based data collection is attracting extensive attention in recent years. Energy efficiency issues, including clustering and itinerary planning, are considered as the major challenges in this area. This paper proposes a UAV-based data collection approach which includes a cluster head selection algorithm with balanced energy, as well as an itinerary planning algorithm which provides optimal itinerary planning based on the comprehensive consideration of energy consumption and energy balancing.

The nonvolatile and continuous tuning of device conductance is the crucial requirement when developing novel materials and devices as artificial synapses. In this work we demonstrate that by exploiting various kinds of mechanisms such as ferroelectric tuning, floating gate controlling, ferroelectric-like transition in van der Waals layered 2-dimensional materials, electrokinetic phenomenon in nanofluid, etc. low dimensional devices have been successfully fabricated as memristive synapses. The advantages and challenges of using these low dimensional materials and devices as electronic synapses are illustrated with the hope of providing guidelines for the future development of this promising topic.

Novel complementary graphene-ferroelectric transistors (C-GFTs) based synapses are proposed and experimentally demonstrated for the first time. By exploiting the unique zero-bandgap property of graphene, GFT based synapses can be dynamically reconfigured between potentiative and depressive (PD) modes corresponding to hole-and electron dominated transport in graphene channels, respectively. Both modes demonstrate excellent linearity, small (2%) cycle-to-cycle variation and > 32 levels when used as synapses. By configurating the PD modes into a pair of C-GFTs, the hardware architecture of spiking neural networks (SNNs) can be substantially innovated, where the complicated circuitry previously required for supervised learning is now completely removed. With C-GFTs, a synapse footprint of 100 μm2 and a power consumption of 8 pJ/per operation are demonstrated in the MNIST learning task.

Nowadays, the System on Chip (SoC) based multi-axis control drive integration platform has been a good alternative to the classic distributed servo system structure. Compared with the distributed structure, the integration structure can reduce the manufacturing cost, achieve a faster internal information sharing, and has richer resources of multi-class chips. Hence, SoC-based integration platforms have greater potential and better control performance. In this paper an easy-to-follow SoC-based multi-axis control-drive integration platform design method is presented at first. The hardware design and software structure are discussed in detail. Then, based on the SoC-based platform, several control performance improvement strategies are listed out to verify the advantages of the SoC-based integration platform. The results of the analyses and experiments show that SoC-based integration servo system structure can be a good technology carrier for the advanced servo system in future.

In this paper, the servo system mechanical drive is analyzed, flexible beam vibration will cause end point trajectory distortion. Simplify the flexible beam load as a second-order system, which is a low frequency light damped vibration system, the ZVD input shaper which is very suitable for vibration suppression of low frequency light damping system is adopted. Due to the different vibration frequencies and damping coefficients of the X-Y platform flexible load, the X-axis and Y-axis input shapers cause different command lags, which can cause trajectory distortion. The adaptive feedforward controller based on phase angle error is used to solve trajectory distortion problem. Combined with the input shaper and adaptive feedforward control based on phase error, it can solve the vibration suppression of X-axis and Y-axis flexible load with different vibration characteristics, and can guarantee the track accuracy. Finally, the effectiveness of the algorithms is verified by simulation.

This paper presents a Field Programmable Gate Array (FPGA) -based platform for integrated multi-axis motion control and motor drive. As the development of FPGA, the integrated high-performance ARM processor on the FPGA has become the direction of FPGA development. This paper chooses the Xilinx Zynq-7020 programmable system-on-chip(SoC) which integrated dual-core ARM CPU and FPGA as a High-performance hardware platform. This platform is suits for the requirements of integrated multi-axis motion control and motor drive well, one ARM CUP completes the multi-axis position loop algorithm, speed loop algorithm and multi-axis trajectory generation, the other completes the human-computer interaction function. 4-axis current loop pipeline control and double sampling double updating current loop algorithm are accomplished by FPGA which can expand the current loop bandwidth and save FPGA logic resources. This platform’s architecture will improve the overall bandwidth of the system, achieve multi-axis synchronization accuracy at nanosecond level which makes position trajectory more accurate.

Rank deficiency issues dictate that parameter identification for permanent magnet synchronous motor (PMSM) must be a step by step procedure. In this paper, the influence of parameter identification sequence to identification accuracy is analyzed and an off-line and on-line combined sequence is assessed to be the optimal sequence for improving the accuracy of resistance and flux identification. Overall parameter identification and voltage source inverter (VSI) non-linearity compensation are realized with adoption of the recursive least square (RLS) method. For comparative study, three different sequences, under same operation condition, are considered on a bidirectional PMSM 750W test bench to establish the advantages of the proposed optimal sequence.

A Dual-gate graphene field effect transistor was fabricated with HfO2 and SiO2 as the back and top dielectric layers on silicon substrate, respectively. The CVD grown graphene was transferred a process by spin-coating a PMMA layer. The electrical properties of the graphene transistors were investigated. Ambipolar behavior of field effect transistor is demonstrated with the carrier mobility of the channel between 3000 to 4500cm2/Vs. It is found that the AZ5214 photoresist covered on graphene during the fabrication process induces its p-type doping and annealing can reduce the impurity concentration dramatically.

A cost-effective and low-overhead chromatic dispersion (CD) compensation scheme in TDM PON systems is proposed in this paper. In our scheme only one Electronic Dispersion Compensation (EDC) equalizer is used in OLT receiver to compensate each ONUs' CD, which is different due to ONUs' different fiber length. Therefore the cost of TDM PON systems could be reduced greatly. EDC first acquires the tap coefficient corresponding to each ONU by using training sequence and then switch the tap coefficient at corresponding time slot to compensate each ONU's dispersion respectively. Then the known field of existed overhead in PON system is used to adjust the tap coefficient, which could save overhead significantly. Simulation results show that the scheme is feasible.

According to the characteristics of Reusable Boost Vehicle (RBV) during the large attitude adjusting phase, like strong nonlinearity, strong coupled and multi input-output, the nonlinear modeling is established (with the nonlinearity of aerodynamic coefficients varies with factors fully considered, such as Mach number, attack angle, sideslip angle and so on). A RBV flying control strategy based on neural network robust adaptive inverse is proposed. First, RBV system is completely decoupled using nonlinear dynamic inverse; secondly, the effect of model uncertainty is eliminated using robust adaptive method; finally, the feasibility and validity of the control strategy during the large attitude adjusting phase are verified with nonlinear simulation.

Mindlin plate theory was first developed to provide accurate solutions for vibrations of thickness-shear mode, which has a much higher frequency than usual flexure vibrations. It has been widely used in the analysis of high frequency vibrations of quartz crystal plates, which are the core of resonators. The vibration frequency solutions obtained with Mindlin plate theory are proven much closer to the exact solutions. However, due to the truncation and approximation, the plate equations need to be corrected, as compared with the three-dimensional elasticity solutions. This has been done for the high-order Mindlin plate theory with and without electrodes for the AT-cut quartz crystal plates, and correction factors have been obtained though both natural and symmetric procedures. The correction factors could be used in the dispersion relationship and frequency spectrum in the analytical solutions, while the symmetric correction factors can be used in the finite element method implementation. Both correction schemes can provide improved and accurate results in the analysis of quartz crystal resonators. The electrodes are considered though its inertia effect as mass ratio known in resonator analysis.

We formulate the first-order nonlinear Mindlin plate equations in the finite element method to study the high frequency thickness-shear vibrations of quartz crystal plates. Iterative algorisms are utilized to solve the resulted nonlinear eigensystems. High performance computational software packages are integrated into our nonlinear finite element program to speed up the extremely large scale computations. We considered both kinematic and material nonlinearities in vibrations analyses, and obtained the frequency-amplitude relations. We also compared distributions of the thickness-shear deformation at different amplitudes. This nonlinear finite element software can be further improved to study nonlinear phenomena arising from miniaturized quartz crystal resonators.

Addressing topology mismatch and network instability problems existing in Application Layer Multicast (ALM), a novel ALM scheme based on redirection is proposed. Simulation results show that the scheme would decrease the traffic of core network and end-to-end delay of service effectively.