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All Journal IAES International Journal of Robotics and Automation (IJRA) International Journal of Applied Power Engineering (IJAPE) Journal of Robotics and Control (JRC)
Van, Chi Nguyen
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Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Tracking Iterative Learning Control of TRMS using Feedback Linearization Model with Input Disturbance Danh, Hoang Dang; Van, Chi Nguyen; Van, Quy Vu
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.25579

Abstract

This paper presents a method for angular trajectory tracking control of the Twin Rotor Multi-Input Multi-Output System (TRMS) experimental model using linearized feedback control with nonlinear compensation and iterative learning-based angular trajectory tracking control. First, the dynamic model of the Twin Rotor MIMO System (TRMS) is developed in the form of Euler-Lagrange (ELF), including descriptions of uncertain parameters and input disturbances such as energy dependence related to the mass of components, friction forces, the effect of the TRMS flat cable, and the impact of the main rotor and tail rotor speeds on horizontal and vertical movements. Based on the nonlinear acceleration equations for the pitch and yaw angles of the TRMS, a compensator is designed to address the nonlinearity of the EL model. Notably, this compensator self-adjusts the compensation signal so that the closed-loop system, consisting of the TRMS and the compensator, becomes a predetermined linear model. Therefore, the structure of the compensator does not need to be designed based on the nonlinear model of the TRMS. After incorporating the compensator, the ELF becomes nearly linear with sufficient accuracy as designed. This system is then controlled using a predefined trajectory tracking controller based on iterative learning with proportional-type learning parameters. By adjusting a sufficiently small optional time parameter, the trajectory tracking error of the pitch and yaw angles of the closed-loop system can be reduced to a desired small-radius neighborhood. Simulation and experimental results demonstrate the trajectory-tracking capability of the closed-loop system. Although the convergence rate depends on the complexity of the TRMS dynamics, the robustness of this method with varying initial conditions is always ensured. The computational complexity is slightly higher compared to other methods, Still, this study contributes a straightforward yet effective trajectory control method under conditions of noise depending on the position, velocity, pitch and yaw angles and unmeasured kinematic model parameters for the TRMS system.
State-augmented adaptive sliding-mode observer for estimation of state of charge and measurement fault in lithium-ion batteries Vinh, Thuy Nguyen; Van, Chi Nguyen; Van, Vy Nguyen
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i2.pp291-299

Abstract

Estimating the state of charge (SoC) in lithium-ion batteries (LiB) encounters challenges due to model uncertainties and sensor measurement errors. To solve this issue, this study introduces an estimator based on an innovative adaptive augmented sliding mode approach. This approach incorporates measurement faults as additional state variables to minimize the impacts of uncertainties effectively. Furthermore, based on the sliding mode framework, the design of this estimator addresses resistance to model uncertainties. However, sliding estimators commonly face the chattering issue. To counteract this, the paper suggests employing adaptive dynamics to determine the estimator's gain. This adaptive approach allows the gain calculation to minimize estimation errors across all time steps, effectively reducing chattering and enhancing estimation accuracy. The performance of the proposed method is validated through simulations using two practical data sets. Results demonstrate superior accuracy compared to conventional sliding methods, with improvements in SoC and terminal voltage estimation.
The algorithm of adaptive control for active suspension systems using pole assign and cascade design method Van, Chi Nguyen
IAES International Journal of Robotics and Automation (IJRA) Vol 9, No 4: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v9i4.pp271-280

Abstract

This paper presents the active suspension system (ASS) control method using the adaptive cascade control scheme. The control scheme is implemented by two control loops, the inner control loop and outer control loop are designed respectively. The inner control loop uses the pole assignment method in order to move the poles of the original system to desired poles respect to the required performance of the suspension system. To design the controller in the inner loop, the model without the noise caused by the road profile and velocity of the car is used. The outer control loop then designed with an adaptive mechanism calculates the active control force to compensate for the vibrations caused by the road profile and velocity of the car. The control force is determined by the error between states of the reference model and states of suspension systems, the reference model is the model of closed-loop with inner control loop without the noise. The simulation results implemented by using the practice date of the road profile show that the capability of oscillation decrease for ASS is quite efficient.
Co-Authors Danh, Hoang Dang Van, Quy Vu Van, Vy Nguyen Vinh, Thuy Nguyen