• International Journal of Automotive Technology
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• v.6 no.6
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• pp.599-604
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• 2005

A functional suspension model is proposed as a kinematic describing function of the suspension, that represents the relative wheel displacement in polynomial form in terms of the vertical displacement of the wheel center and steering rack displacement. The relative velocity and acceleration of the wheel is represented in terms of first and second derivatives of the kinematic describing function. The system equations of motion for the full vehicle dynamic model are systematically derived by using velocity transformation method of multi-body dynamics. The comparison of test and simulation results demonstrates the validity of the proposed functional suspension modeling method. The model is computationally very efficient to achieve real-time simulation on TMS 320C6711 150 MHz DSP board of HILS (hardware-in-the-loop simulation) system for ECU (electronic control unit) evaluation of semi-active suspension.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.3
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• pp.164-172
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• 2001

Various HILS systems for developing and testing vehicle mechatronic systems have been proposed and constructed during the last few years. However, performance of those systems have not been evaluated in a systematic way. Based on the transfer function approach, this paper presents a method far evaluating performance such as stable dynamic simulation range of a proposed steering HILS system. In the evaluation, we have investigated effects of time delays that exist in the real-time dynamic simulation, additional actuators, and data transmission on the stable dynamic simulation range, simulation frequency range, and steering feel. This evaluation methodology may be useful to help engineers develop a HILS system for their own purposes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.255-260
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.113-118
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• 1999

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important n the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.794-799
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• 2012

The international standard, ISO-11783, was designed for the communication within an agriculture machinery. Even if it is based on the CAN (Control Area Network) protocol, its extended features which include point-to-point communication and large data transmission support show different network performance from the standard CAN. This paper proposes a dynamic priority allocation method to improve the real-time performance of ISO-11783. Computer simulation shows reduction of the deadline-missed cases and community latency via proposed algorithm.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1247-1267
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• 2014

Real-Time Hybrid Simulation (RTHS) is a novel approach conceived to evaluate dynamic responses of structures with parts of a structure physically tested and the remainder parts numerically modelled. In RTHS, delay estimation is often a precondition of compensation; nonetheless, system delay may vary during testing. Consequently, it is sometimes necessary to measure delay online. Along these lines, this paper proposes an online delay estimation method using least-squares algorithm based on a simplified physical system model, i.e., a pure delay multiplied by a gain reflecting amplitude errors of physical system control. Advantages and disadvantages of different delay estimation methods based on this simplified model are firstly discussed. Subsequently, it introduces the least-squares algorithm in order to render the estimator based on Taylor series more practical yet effective. As a result, relevant parameter choice results to be quite easy. Finally in order to verify performance of the proposed method, numerical simulations and RTHS with a buckling-restrained brace specimen are carried out. Relevant results show that the proposed technique is endowed with good convergence speed and accuracy, even when measurement noises and amplitude errors of actuator control are present.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.63-76
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• 1999

Recently in manufacturing environment, manufacturing order is characterized by unstable market demand, shorter product life cycle, a variety of product and shorter production lead time. In order to adapt this manufacturing order, flexible manufacturing systems(FMS) in manufacturing technology advances into the direction that machines become further versatile functionally and that tools are controlled by fast tool delivery device. Unlike conventional FMS to mainly focus on part flow, it is important to control tool flow in single-stage multimachine systems(SSMS), consisting of versatile machines and fast tool delivery device. This research is motivated by the thought that exact estimation of tool competition at part release in SSMS enhances the system performance. In this paper, in SSMS under dynamic tool allocation strategy to share tools among machines, we propose real-time part release and tool allocation algorithms which can apply real factory and which can improve system performance.

• Computational Structural Engineering
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• v.35 no.1
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• pp.25-34
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• 2022

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.109-111
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• 1996

This paper describes real time dynamic tests on the digital distance relay using new digital test system including RTDS(Real Time Digital Simulator) in KEPRI. The RTDS is developed by the Manitoba HVDC Reserch Centre and consists of specialized hardware and software which allows transients simulation of electrical power systems in real time. From high impedance fault test, it is known that the characteritics of distance reach is influenced by load flow. A detailed discussion of relay test using the RTDS simulator, high impedance faults and test results are included in the paper.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.100-104
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• 1998

This paper describes the real-time implementation of an adaptive controller fur the robotic manipulator. Digital signal processors(DSPs) are special purpose micro-processors that are particularly powerful for intensive numerical computations involving sums and products of variables. TMS320C50 chips are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the direct adaptive control theory. The adaptive controller consists of an adaptive feedforward controller and feedback controller. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a assembling robot.