Dong-Ji Xuan

International Conference on Control, Automation and Systems

The following topics are dealt with: intelligent control; spacecraft guidance; process control; PID control; dextrous manipulation; mobile robot; signal processing; UAV flight control; nonlinear control; embedded systems; obstacle avoidance; virtual reality; time-delay system and adaptive control.

Control of an Active Suspension Based on Fuzzy Logic

In this paper, a control strategy of active suspension based on the fuzzy logic control has been investigated. Using incorporating feedback from force sensor at front and rear active suspension system, the control system shows the improvement of the dynamic responses of the vehicle. A multi degree-of-freedom nonlinear model is co-simulated by MATLAB/Simulink and ADAMS/car. The simulation results indicate that the proposed active suspension is very effective in the vibration isolation.

A study on active suspension system using time delay control

Time Delay Control (TDC) method was proposed as a promising technique in the robust control area, where the plants have unknown dynamics with parameter variations and substantial disturbances are present. In this paper, the TDC technique is applied to design the force loop controller of an electro-hydraulic active suspension system. Based on the quarter-car active suspension system model, the TDC is designed, and the PID-controller is also designed for comparison. The simulation results show that the TDC is the effective means in controlling the hydraulic system and it can be utilized as one of the control candidates for the active vehicle suspension.

A quantitative feedback control system design for the multi-axis simulator having uncertain plants

This paper presents the design of quantitative feedback control system of three axes hydraulic road simulator. The road simulator is the multiple input-output (MIMO) system with parameter uncertainties which should be compensated with robust control method. The objective of the present paper is to reproduce the road vibration signal by three hydraulic cylinders. The replaced m² MISO equivalent control system is suggested, which satisfies the design specification of the original mxm MIMO control system by decoupling each three axes. Quantitative feedback theory (QFT) is used to control the simulator. The QFT illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) having the minimum bandwidth for the uncertain plant with parameter uncertainty. The simulation and the experimental results show that the proposed control technique works well under uncertain hydraulic plant system.

Control of a magnetic flywheel by a fuzzy neural network algorithm

In this paper a magnetic flywheel system is studied with a magnetic bearing, which is able to support the shaft without mechanical contacts, and it is also able to control the rotational vibration. Magnetic flywheel system is composed of position sensors, a digital controller, actuating amplifiers, electromagnets and a flywheel. This work applies the fuzzy neural network (FNN) algorithm to control the vibration of a magnetic flywheel system. It proposes the design skill of an optimal controller when the system has the uncertainty, i.e. it has a difficulty in extracting the exact mathematical expressions. Two controllers are designed for the FNN in order to reduce the rotor vibration effectively. Unbalance response, which is a serious problem in rotating machineries, is improved by using a magnetic bearing with a FNN algorithm.

The force control system design of road simulator using QFT

This paper presents the force control system design of road simulator for reproducing the random input signal to implement the real road vibrations data. The force control system using quantitative feedback theory controls the road simulator effectively. The force control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) having the minimum bandwidth for parameters of uncertain plant. A force controller is designed to communicate the control signal between simulator and digital controller. Tracking specification is satisfied with upper and lower bound tolerances on the steep response of the system to the reference signal. The efficacy of the QFT force controller is verified through the numerical simulation, in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under uncertain hydraulic plant system. The Labview software is used to make up for the real controller in the real-time basis. The experimental results show that the proposed algorithm works well for the road simulator. The road simulator consists of the specimen, hydraulic pump, servo valve, hydraulic actuator and its control equipments.

Design of Force Control System for a Hydraulic Road Simulator Using Quantitative Feedback Theory

This paper presents the road simulator control technology for reproducing the road input signal to implement the real road data. The simulator consists of the hydraulic pump, servo valve, hydraulic actuator and its control equipment. The QFT(Quantitative Feedback Theory) is utilized to control the simulator effectively. The control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) for a parametric uncertain model. A force controller is designed to communicate the control signal between simulator and digital controller. Tracking specification is satisfied with upper and lower bound tolerances on the steep response of the system to the reference signal. The efficacy of the QFT force controller is verified through the numerical simulation, in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under uncertain hydraulic plant system. The conventional software (Labview) is used to make up for the real controller in the real-time basis, and the experimental works show that the proposed algorithm works well for a single road simulator.

Modeling and Simulation for Fuel Cell-Battery Hybrid Electric Vehicle

a model for the Fuel Cell-Battery Hybrid Electric Vehicle (FCHEV) power train in parallel configuration simulation based on the empirical formulation and MATLAB/Simulink blocks has been constructed with the power control strategy using logic threshold approach. Using accelerator pedal signal generated by the driving schedule as the primary input, the simulation implements difference power flow and management under the vehicle operating modes: start, cruise, accelerate and pause. It also incorporates regenerative braking for battery capacity recovery. Main control variables and three group threshold values are evaluated for the vehicle driven under the New Europe Driving Cycle (NEDC) schedule. The results indicate that this configuration of the FCHEV model has capability for battery state of charge (SOC) recovery while meeting vehicle speed and drive power request. The effect that the control thresholds impact on the power distribution and fuel consumption has also been simulated.