Gang Yang

The powder-compaction process distributes the stress by a variety of kinematic processes that involve sliding, rotation, friction, particle deformation, and rupture. Thus, load stiffness presents complex nonlinear time-varying characteristics, and the so-called mismatched disturbances pose great challenges to the high accuracy tracking controller design of the electrohydraulic system for bidirectional powder compaction press (BPCP). Hence, designing a universal high-performance tracking controller applicable to the granular materials compaction process is of practical significance. In this article, a cancellation mechanism-based nonlinear load observation compensator is proposed to improve the position tracking performance and minimize the compaction velocity fluctuations of the BPCP. The proposed method consists of an open-loop control with feedforward based on a cancellation mechanism and a closed-loop system with negative feedback to yield a stable control system. The main contribution of this article is that the proposed solution attenuates the adverse effects of the nonlinear load disturbances and makes the system behave like a quasi-decoupled linear system, thereby reducing the complexity of the control system. Comparative experiments are performed on an electrohydraulic system for the BPCP to verify the superiority of the proposed control strategy.

A good surface texture design can effectively improve the tribological performance of the helical pair within a helical hydraulic rotary actuator(HHRA). However, the optimization design process can be time-consuming due to the multiple design variables involved and the complexity of the mathematical model. This paper proposes a modified efficient global optimization (MEGO) method for solving such demanding surface texture design challenges. The MEGO utilizes a Kriging model with the optimized Latin hypercube sampling (OLHS) for initial sampling and the proposed modified expected improvement (MEI) function for sequential sampling. A comparative study of several global optimization algorithms with the MEGO on the surface texture design is performed. Subsequently, surrogate-based optimization and parameter analysis are carried out, resulting in the identification of an optimal set of texture parameters. The findings reveal the superiority of the MEGO in both model prediction accuracy and refinement of minima. Moreover, compared to the base design, the friction coefficient can be reduced by up to 45.2%.

This paper aims to optimize the two-stage helical pairs (TSHPs) in a helical hydraulic rotary actuator (HHRA) in terms of volume, transmission efficiency, and maximum contact stress. Volume and transmission efficiency can be determined through analytical mathematical models. However, calculating the contact stress of helical pairs necessitates complex and time-consuming finite element simulation. To address this issue, a method for predicting the maximum contact stress using an ensemble of metamodels (EMs) is proposed, with an automated finite element simulation process developed for data provision. The superiority of the EMs is validated through comparative analysis with three stand-alone metamodels. The optimization is carried out using the NSGA-II algorithm, including four combinations of the three objectives, and global sensitivity is analyzed over the objectives. The results indicate a trade-off relationship between maximum contact stress and volume in the optimal space. Moreover, considering multiple combinations enhances the robustness of the optimization results. The method is effectively applied to the design of the TSHPs and provides a new idea for the related actuator design.

A high-temperature gas mixing chamber is a type of mechanical device which has been widely used to obtain airflow at a specific high temperature. When a temperature environment test for aviation equipment is performed, the airflow temperature should exceed 1,000 K and change fast. However, the existing mixing devices cannot meet the requirements for mixing speed and uniformity of temperature environment tests. To solve the problem of low mixing speed and uniformity, this paper proposes an innovative gas mixing chamber design. The proposed design allows cold and hot gases to be injected in directions perpendicular to each other, which increases the collision and heat exchange of gases with different temperatures. In this way, a faster mixing process and a more uniform outlet temperature field are obtained. Moreover, a genetic optimization method is used to improve the performance of a mixing chamber. This method considers temperature distribution, the velocity distribution of the outlet airflow, and the mixing speed. Simulation results show that the proposed method can reduce the mixing time from 4.4 s to 2.3 s, the standard deviation of the outlet temperature distribution from 25.2 to 14.7, and the standard deviation of velocity distribution from 1.3 to 0.36. The experimental results show good consistency with the simulation results, indicating that the simulation and optimization results are reliable, and the mixing performance of the cold and hot gas mixing chamber is significantly improved by the proposed method. The proposed method is important for optimizing the design of similar orifice plates and flow mixing structures.

Underwater gliders are a class of ocean observation equipment driven by buoyancy, and their energy consumption source is mainly generated by the active regulation of buoyancy. The periodic elastic deformation of the pressure hull during the upward and downward movement of the underwater glider can have a large impact on its driving buoyancy. This paper relates the optimization problem of the pressure hull with the energy consumption of underwater glider, and the energy improvement factor is taken as the optimization objective. Based on the mechanical theory, the theoretical optimization model and constraint model are derived. A hybrid genetic simulated annealing algorithm (HGSAA) is adopted to optimize the pressure hull of the underwater glider developed by Huazhong University of Science and Technology (HUST). Additionally, the effectiveness of the optimized mathematical model and optimization results were verified by the tests. The sea trial results show that after the pressure hull optimization, the energy consumption of the buoyancy regulation unit decreased by 21.9%, and the total energy carried increased by 12.4%.

Using high-speed on-off valves (HSVs) with small size, low cost, and high switching accuracy instead of expensive proportional/servo valves, and researching high-performance vacuum servo system can further enhance the competitiveness of vacuum servo technology. However, due to the delay characteristics of high-speed on-off valve (HSV), the average gas mass flow rate of the output has dead zone, saturated zone and nonlinear zone. A linear compensation method for flow output is designed, so that the average gas mass flow rate of the output is approximately positively correlated with the duty cycle of the pulse width modulation (PWM) signal. Furthermore, because of the air compression and the leakage of the system, there exist parametric uncertainties, unmodeled dynamics and disturbances in the vacuum servo system. An adaptive backstepping control (ABC) strategy based on discontinuous projection mapping is designed. The adaptive backstepping control strategy inhibit the influence of system’s parametric uncertainties through on-line update of the uncertain parameters, and uses its own robustness to eliminate the effects of unmodeled dynamics and disturbances. Compared with the sliding mode control (SMC) strategy, the experimental results show that when the tracking frequency reaches 3–4Hz, the adaptive backstepping control strategy can ensure good tracking performance.

An underwater glider is a type of autonomous profiling instrument platform used for gathering data to explore the ocean. Having a neutrally buoyant glider hull is one way to improve the glider's endurance with a passive compensation for buoyancy change. This article applies the bi-directional evolutionary structural optimization (BESO) method to the optimization of an underwater glider hull, based on two materials. Firstly, the method for determining the glider's neutral buoyancy is carried out. Secondly, the optimization problem is defined and the optimization procedure is presented. In the BESO procedure, the original design area elements with low strain energy are iteratively switched from high-value materials to low-value materials until a prescribed fraction is reached. Finally, an optimal underwater glider design is generated and the result demonstrates a reasonable material distribution of the neutrally buoyant glider hull. A 26.4% buoyancy adjustment is achieved and the mass of the glider is decreased by 31%.