Nguyen Duy Cuong

Design of MRAS-based adaptive control systems

In this paper, simple adaptive control schemes based on Model Reference Adaptive Systems (MRAS) algorithm are developed for the asymptotic output tracking problem with changing system parameters and disturbances under guaranteeing stability. The adaptive adjusting law is derived by using Lyapunov theory. The direct and indirect adaptive schemes are proposed that constantly adjust the gains in the controllers and/or observers. The adaptive algorithm that is shown in this study is quite simple, robust and converges quickly. Performances of the controlled systems are studied through simulation in Matlab/Simulink environment. The effectiveness of the methods is demonstrated by numerical simulations.

Application of LQG combined with MRAS-based LFFC to Electromechanical Motion Systems

Abstract In this paper we introduce a new control structure which consists of a Linear Quadratic Gaussian (LQG) controller and a Model Reference Adaptive System (MRAS)-based Learning Feed-Forward Controller (LFFC) to Electromechanical Motion Systems. Feed-forward is used in addition to LQG because LQG is still required to account for imperfections in the feed-forward system model. By adding a Learning Feed-Forward (LFF) component to the LQG controller, an extra degree of freedom in the controller design is created. The advantages of the proposed method are verified by simulation and experimental results. A control scheme is derived which has good properties in common with both the LQG and LFFC controller. This control structure can capture many aspects of the control problems. The responses to setpoint changes and reproducible disturbances are mainly obtained by the LFFC. The LQG is designed to obtain a stable closed-loop system that is insensitive to measurement noise and variations and uncertainties in process behavior.

Design of MRAS based control systems for load sharing of two DC motors with a common stiff shaft

In this paper, the behavior of a stiff shaft in a drive system consisting of two DC motors driving a common load is investigated. The expectation is to get both motor armature currents to match, indicating successful load sharing. The new idea of using Model Reference Adaptive Systems (MRAS) approach has been applied to design a control system such that two motors are identical in speed-torque characteristics. The design can be achieved in such a way that the two motors can contribute the same amount to the total load in the case that the DC motors are identical, or contribute partly to the total load and proportionally to their nominal torques in the case that the two motors are not identical. Both simulation and experimental results confirm the precise and robust performance and the ease of tuning and implementation, featured by the proposed control structure. The slave motor current strictly follows the master motor current with a maximum error between them is always smaller than 5%.

Design of Dynamic - Static VAr compensation based on microcontroller for improving power factor

The issues related to control of reactive power in order to improve the quality of the electric transmission and distribution nowadays get more interests in readers. There are two most commonly used methods which are dynamic and static VAr compensation (denoted by DVC and SVC respectively) for improving power factor, but both ways still remain some drawbacks such as the over/under or corrupted compensation phenomena due to DVC, or an expensive cost for a large size of inductors of SVC. This paper proposes a new scheme combining both DVC and SVC in order to get the best performance with low installing cost. The proposed scheme, called Dynamic-Static VAr compensation (DSVC), includes two controlled loops. The inner loop, DVC controller, has a function of providing a large amount of the compensating reactive power until a little capacitive leading, then the outer loop, SVC controller, acts on the system to eliminate the over compensation from the inner controlled loop. The feed-back signal in this case is the power factor (cosϕ) that is the same as the reference signal, and the power factor (PF) meter design based on the microcontrollers will be deeply described in this paper. The work is firstly validated via simulating on Matlab/Simulink, and then applied on the experimental setup. The results indicate that the proposed solution gives the good qualities not only in technical requirements, but also in financial statement.

Harmonic elimination based on fuzzy logic in combination with hysteresis control algorithm

Harmonics have significant harmful effects on the electric network. Many solutions have been introduced, and one of the most popular ways is use of a shunt active power filter based on hysteresis current controller combining with an inverter. The hysteresis current controller functions to compare the current error to the upper and lower thresholds for generating the trigger pulses for the Insulated Gate Bipolar Transistor (IGBT) bridge. The efficiency of this method depends on the displacement between upper and lower values. The smaller displacement provides a good tracking performance, but the switching frequency of the pulses sending to IGBT is very high. However, in the real world, the switching frequency of IGBT is limited, not infinity. Hence, this paper presents the methodology in which the fuzzy logic control is used for adapting the upper and lower thresholds. This work not only gives the lower value of total harmonic distortion (THD) (%THD from 29.9% to 1.54%), but also reduces the switching frequency (from 500 kHz to 60 kHz). The proposed scheme is firstly implemented and tested on MATLAB/SIMULINK environment, and then applied on experimental setup.

Improving Control Quality for Two-Wheeled Mobile Robot

An approach for improving quality of motion control and stabilizing for two-wheeled mobile robot which is affected by internal and external distubances is presented in this paper. An output feedback controller using backstepping combined with high gain observer (HGOs) technique is designed. The decoupling technique for coupling system of two-wheeled mobile robot is also applied. Results of simulation show the effectiveness of the designed controller.

Design of a PD Controller Combined with a MRAS-Based LFFC for a Two - Link Robot Manipulator

In this paper we introduce a new control structure which consists of a PD controller and a Model Reference Adaptive System-based Learning Feed-Forward Controller to a two-link robot manipulator. The proposed approach seeks to benefit the multi-variable control of multi-input multi-output systems with variable parameters, nonlinear behavior, and significant coupling in the system dynamics. Conventionally, the function approximators with standard neural networks were used which enabled to approximate complex non-linear functions. The idea of LFFC is applied but without using the complex neural networks. Instead, we propose to use MRAS-based adaptive components. The well-known Lyapunov approach is used to find stable adaptive laws for the feed-forward parameters in such way that learning converges. The effectiveness of the proposed approach is demonstrated by simulation analysis.