Bui Ngoc Minh Truong

Hysteresis modeling and identification of a dielectric electro-active polymer actuator using an APSO-based nonlinear Preisach NARX fuzzy model

Dielectric electro-active polymer (DEAP) materials are attractive since they are low cost, lightweight and have a large deformation capability. They have no operating noise, very low electric power consumption and higher performance and efficiency than competing technologies. However, DEAP materials generally have strong hysteresis as well as uncertain and nonlinear characteristics. These disadvantages can limit the efficiency in the use of DEAP materials. To address these limitations, this research will present the combination of the Preisach model and the dynamic nonlinear autoregressive exogenous (NARX) fuzzy model-based adaptive particle swarm optimization (APSO) identification algorithm for modeling and identification of the nonlinear behavior of one typical type of DEAP actuator. Firstly, open loop input signals are applied to obtain nonlinear features and to investigate the responses of the DEAP actuator system. Then, a Preisach model can be combined with a dynamic NARX fuzzy structure to estimate the tip displacement of a DEAP actuator. To optimize all unknown parameters of the designed combination, an identification scheme based on a least squares method and an APSO algorithm is carried out. Finally, experimental validation research is carefully completed, and the effectiveness of the proposed model is evaluated by employing various input signals.

Study on energy regeneration system for hybrid hydraulic excavator

Nowadays, with the development of global energy crisiss compression and high fuel expenditure, the demands for energy saving and green emission of construction machineries, especially hydraulic excavators, have been rapidly increased. Meanwhile, the power efficiency of the conventional hydraulic excavators is very low. This study deals with the method to regenerate potential energy on the boom system of the hybrid hydraulic excavator. The novel hydraulic circuit as well as the control strategy are introduced to make sure that the performance of the system is satisfied and maximize the energy regeneration capability. The model of the proposed system and the control strategy are built and simulated by AMEsim and Matlab software while the system parameters are taken from a real system. The results show that the proposed energy recovery system and control strategy can improve energy recovery efficiency and optimize working performance of the system.

Adaptive grey predictor-based controller for force control of EHA system

This study aims to develop an effective control approach for force control of a typical EHA system. This control scheme is considered as an advanced combination of a feedforward neural network — based PID (FNNPID) controller and a fuzzy grey predictor (FGP), shortened as feedforward neural network fuzzy grey predictor (FNNFGP). Here, the FNNPID controller is used to drive the system to desired targets. Meanwhile, the FGP predictor with self-tuning ability of the predictor step size takes part in, first, estimating the system output in the near future to optimize the controller parameters in advance and, second, creating a compensating control signal accordingly to the system perturbations and, consequently, improving the control performance. Real-time experiments have been carried out to investigate the effectiveness of the proposed control approach.

Mathematical modeling of a variable displacement vane pump for engine lubrication

This paper developed a complete and accurate mathematical model for a typical variable displacement vane-type oil pump to investigate the working performance of the pump. Firstly, the detailed theoretical model was built based on pumps geometric design and dynamic analyses. Next, numerical simulations with the constructed model and experiments on the real pump system were carried out to analyze the main power loss factors in order to develop the complete model with high accuracy. The estimated pump performance using the complete pump model was finally verified by numerical simulations in comparison with the practical tests.

Research on energy regeneration and effect of dynamic characteristics of secondary control swing for hydraulic excavator system

In the modern era, the demand of energy saving is increasing more and more while the natural resources have been exhausted. Among various possibilities, some methods to recuperate energy during vehicle swing motion have been widely examined. After providing required drastic design changes, electric and hydraulic hybrids designs have shown a great improvement in fuel efficiency. The rotating movement of excavator is called swing or slew and is driven hydraulically. The swing drive is hence driven by a hydraulic motor creating a rotating motion. Following the movement of a joystick, the pump is controlled to match the spool positions, swiveling out. In the proposed system, swing braking time the remaining fluid will save as energy by a simple accumulator. This remaining save energy will be used in the system from accumulator. The proposed system is considered as secondary by using two combination of transformer (motor & pump combination) and have some dissimilarities from the conventional swing system. Furthermore, the paper simulates variable inertia and show the effect of variable moment of inertia in different simulation result. The proposed system will be developed in AMESim software. The proposed system will be more efficient in saving energy.