A MIMO Robust Servo Controller Design for Three-Wheeled Automated Guided Vehicles Using a Linear Shift Invariant Differential Operator

Nguyen Van Lanh,Sung-Won Kim(김성원),Dae-Hwan Kim(김대환),Choong-Hwan Lee(이충환),Hak-Kyeong Kim(김학경),Sang-Bong Kim(김상봉) 제어로봇시스템학회 2019 제어·로봇·시스템학회 논문지 Vol.25 No.12

This paper proposes a multi-input multi-output (MIMO) robust servo controller design for three-wheeled Omnidirectional Automated Guided Vehicles (OAGVs) with a disturbance to track desired references using a linear shift invariant differential (LSID) operator. To design the proposed MIMO robust servo controller, the followings are performed. Firstly, a MIMO model of a threewheeled OAGV is presented. Secondly, by operating the LSID operator according to a state-space model and an output error vector, a new extended system and a new control law are obtained. Thirdly, the proposed MIMO robust servo controller for the given threewheeled OAGV is designed by using the pole assignment approach. Fourthly, by applying the inverse LSID operator, a servo compensator and a control law for the MIMO system are obtained. Finally, to verify the effectiveness of the proposed MIMO robust servo controller, the numerical simulation and experimental results are presented. The simulation and experimental results demonstrate that the proposed MIMO robust servo controller has adequate tracking performance under an external disturbance and complicated higher-order reference signals such as step, ramp, and parabola. These results are compared with those of the sliding mode control method proposed by N. Hung in 2010. The proposed MIMO robust servo controller demonstrates faster tracking performance than the sliding mode control method.

Trajectory Tracking Controller Design for Caterpillar Vehicles Using a Model Reference Adaptive Controller

Van Lanh Nguyen,Dae Hwan Kim,Sang Kwun Jeong,Choong Hwan Lee,Hak Kyeong Kim,Sang Bong Kim 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10

This paper proposes a trajectory tracking controller for Caterpillar Vehicles (CVs) with uncertain parameters that combines a kinematic controller based on a backstepping method and a dynamic controller based on a model reference adaptive controller (MRAC). To do this task, the followings are done. Firstly, a system configuration of the CV is described. Secondly, kinematic modeling and dynamic modeling of the CV with some uncertain parameters are presented. Thirdly, a kinematic controller is designed based on kinematic modeling such that a local posture tracking error vector converges to zero. Fourthly, a dynamic controller based on MRAC is designed based on dynamic modeling such that CV’s output velocity vector converge to a virtual control input vector. Thus, a trajectory tracking controller using backstepping-based MRAC is utilized to estimate these uncertain parameters. By choosing a suitable Lyapunov function candidate, system stability is guaranteed, and a control law and update laws are obtained. Finally, the simulation and experimental results are presented to verify the effectiveness of the proposed MRAC controller.

Positioning and Trajectory Tracking for Caterpillar Vehicles in Unknown Environment

Van Lanh Nguyen,Dae Hwan Kim,Van Sy Le,Sang Kwun Jeong,Choong Hwan Lee,김학경,Sang Bong Kim 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.12

This paper proposes positioning and trajectory tracking for Caterpillar Vehicles (CVs) in unknown environments. To do these tasks, the following are performed. Firstly, a system modeling of the Caterpillar Vehicle is presented. Secondly, solving the complicated tracking control problem in unknown environments is a challenging mission. Therefore, to guarantee the Caterpillar Vehicle system to be strong robustness against external disturbances in the unknown environments, a MIMO robust servo controller for tracking the desired trajectory is designed by using a Linear Shift Invariant Differential (LSID) operator. The CVs are able to accomplish various tasks in dangerous places where workers cannot enter. Thirdly, the positioning of the CV can be obtained using a Simultaneous Localization and Mapping (SLAM) method. This paper develops perfectly the SLAM algorithm for positioning of the CV based on laser sensor Lidar. The main advantage of this method is that it does not need to use more landmarks. Landmarks can be obtained from the unknown environment. Thus, the CV can work even in unknown environments and unsafe places. Finally, to verify the effectiveness of the proposed MIMO robust servo controller and the SLAM positioning algorithm, the experimental results are presented. The experimental results demonstrate the adequate tracking performance of the proposed MIMO robust servo controller in the unknown environment.

The Relationship between Information Distribution and Intention to Choose a University

NGUYEN Lanh Van,NGUYEN Dat Ngoc,NGUYEN Duyen Thi Kim 한국유통과학회 2022 유통과학연구 Vol.20 No.7

Purpose: Research on the intention to choose a university has an important role for universities in enrollment. The information element is considered essential to help students have specific information before making their decisions. However, how to distribute this information appropriately is an issue that needs to be studied. Therefore, this study was conducted to evaluate the influence of information distribution on intention to choose a university. Research design, data, and methodology: The study showed a survey on 259 samples from first-year students at public universities in Vietnam. PLS-SEM model was performed to find out the relationship between information distribution and intention to choose a university. Result: The results show that information quality and information helpfulness positively impact on attitudes towards universities. Attitude towards university has a positive effect on the intention to choose a university. Conclusion: From the results of this study, the authors also make some recommendations to help universities have good communication policies to improve their ability to attract students to choose a university. Quality and helpful information will help universities to be able to attract students more effectively to enroll based on an effective communication strategy.

Linkage Between Exchange Rate and Stock Prices: Evidence from Vietnam

DANG, Van Cuong,LE, Thi Lanh,NGUYEN, Quang Khai,TRAN, Duc Quang Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.12

The study investigates the asymmetric effect of exchange rate changes on stock prices in Vietnam. We use the nonlinear autoregressive-distributed lag (ARDL) analysis for monthly data from 2001:01 to 2018:05, based on VN-Index stock price collected from Ho Chi Minh Stock Exchange (HOSE); the nominal exchange rate is separated into currency depreciation and appreciation through a partial sum decomposition process. Asymmetry is estimated both in the long-run relationship and the short-run error correction mechanism. The research results show that the effect of exchange rate changes on stock prices is asymmetrical, both in the short run and in long run. Accordingly, the stock prices react to different levels to depreciation and appreciation. However, the currency appreciation affects a stronger transmission of stock prices when compared to the long-run currency depreciation. In the absence of asymmetry, the exchange rate only has a short-run impact on stock prices. This implies a symmetrical assumption that underestimates the impact of exchange rate changes on stock prices in Vietnam. This study points to an important implication for regulators in Vietnam. They should consider the relationship between exchange rate changes and stock prices in both the long run and the short run to manage the stock and foreign exchange market.

Learning Control Applications for Autonomous Driving in Extreme Maneuver Scenarios

Tong Duy Son,Lanh Nguyen,Herman Van der Auweraer 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10

This work presents the applications of iterative learning control for autonomous vehicle in extreme maneuver scenarios. By exploiting data from previous executions, the proposed learning algorithm that uses a simple kinematic model can generate optimal feedforward control signals to improve vehicle control performance against nonlinearity, model uncertainties and disturbance. The design developments are validated using a co-simulation structure of Siemens Simcenter Amesim and Prescan software. Simcenter Amesim provides an integrated simulation platform to predict the performance of vehicle dynamics, while Simcenter Prescan is a physics-based platform that can simulate traffic scenarios and sensors. We validate and analyze the results with two driving use cases: racing car and drift parking.