• The Journal of the Acoustical Society of Korea
• /
• v.16 no.6
• /
• pp.85-93
• /
• 1997

Fixed systems are limited in their performances to achieve the more complicated and higher level operations. Accordingly adaptive system, which adjusts itself in accorance with the time-varying environments, has been introduced to camouflarge the defficiency of fixed systems in varying environment, and adaptive filter is the outstanding fields in adaptive system. Adaptive recursive filter is far more efficient in that it can perform the signal processing with relatively lower filter order, but there remains severe problem in stability(convergency). On the basis of hyperstability introduced by V.M. Popov, a hyperstable new adaptive recursive filter is introduced which is theoretically guaranteed in stability. In this paper a more stable algorithm for adaptive recursive filter is devised.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.148-153
• /
• 1999

In this paper, it is proposed the adaptive-sliding mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Over the past decade, the design of advanced control systems for industrial robotic manipulators has been a very active area of research and two major design categories have emerged. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in continuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple structure is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results how that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

• Proceedings of the KIEE Conference
• /
• 2000.07b
• /
• pp.1136-1139
• /
• 2000

The paper describes a new and rigorous mathematical model for the rotor field oriented system with induction motor which uses the estimated speed and rotor flux based on a Model Reference Adaptive System, as well as the real-time approach. The estimated speed and rotor flux is used for the speed and flux feedback control. The stability and the convergence of the estimator are improved on the basis of hyperstability theory for non-linear systems. The real-time controller and estimator are implemented with a sampling period of $926{\mu}s$ using a dual TMS320C44 floating-point digital signal processor. The validity of the proposed method is verified by simulation, and also, the sensorless control was tested on the propulsion system simulator, used for the development of Korean High-Speed Railway Train (KHSRT) [5].

• Proceedings of the KIEE Conference
• /
• 1995.07a
• /
• pp.334-336
• /
• 1995

An adaptive feedback linearization technique of a PM synchronous motor with specified output dynamic performance is proposed. The adaptive parameter estimation is achieved by a model reference adaptive technique where the stator resistance and flux linkage can be estimated with the current dynamic model and the state observer. Using these estimated parameters, the linearizing control inputs are calculated and a nonlinear coupled model of a PM synchronous motor is input-output linearized. The resultant model has the load torque disturbance. To get ti perfect decoupled model, the load torque is estimated. The adaptation laws are derived by the hyperstability theory and positivity concept. The robustness of the proposed control scheme will be proven through the computer simulations.