• Journal of Power Electronics
• /
• v.18 no.5
• /
• pp.1380-1397
• /
• 2018

The synchronous reluctance motor (SynRM) servo-drive system has highly nonlinear uncertainties owing to a convex construction effect. It is difficult for the linear control method to achieve good performance for the SynRM drive system. The nonlinear backstepping control system using upper bound with switching function is proposed to inhibit uncertainty action for controlling the SynRM drive system. However, this method uses a large upper bound with a switching function, which results in a large chattering. In order to reduce this chattering, a nonlinear backstepping control system using an adaptive law is proposed to estimate the lumped uncertainty. Since this method uses an adaptive law, it cannot achiever satisfactory performance. Therefore, a nonlinear backstepping control system using a reformed recurrent Hermite polynomial neural network with an adaptive law and an error estimated law is proposed to estimate the lumped uncertainty and to compensate the estimated error in order to enhance the robustness of the SynRM drive system. Further, the reformed recurrent Hermite polynomial neural network with two learning rates is derived according to an increment type Lyapunov function to speed-up the parameter convergence. Finally, some experimental results and a comparative analysis are presented to verify that the proposed control system has better control performance for controlling SynRM drive systems.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.6
• /
• pp.323-332
• /
• 2003

This paper proposes a variable structure position controller for an induction motor(IM) which uses a reaching law and an integral compensating nonlinear switching function. With the integral compensating nonlinear switching function, both very low overshoot and high steady state control accuracy can be obtained by compensating the states chattering problem due to the unmodelled dynamics of inverter and feedback sensors. With the reaching law, reaching mode can be established quantitatively during transient state so that dynamic control performance is improved. For experiment a digital servo driver which consists of a DSP and an IPM inverter was developed. With the various experimental results, IM position control performance was verified.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.3
• /
• pp.218-228
• /
• 2001

The switched reluctance motor(SRM) has been increasingly used in high-performance servo applications such as electric vehicles, aircraft, and direct-drive robots. The dynamic equations of SRMs are, however, highly nonlinear and this makes it difficult to control SRMs with high performance. In this paper, we propose a new robust current tracking controller for SAMs which can compensate the nonlinear characteristics of SRM(i.e., back-emf and inductance) completely and hence shows perfect tracking performance even with an arbitrary small current control loop gain. Furthermore, even in case that there exist some model uncertainties, our current controller guarantees that the stator currents can track the reference current commands with sufficiently small tracking errors. In order to justify our work, we present the tracking performance analysis and some simulation results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.6
• /
• pp.509-517
• /
• 2001

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require and accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is evaluated through a series of experiments for the various types of inputs while applying disturbances to the hydraulic system. The performance of this controller was compared with those of PID and PD controllers. From these results, We observe be said that the position tracking performance of neuro-fuzzy is better those of PID and PD controllers.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.1127-1132
• /
• 1991

Pneumatic control system has been used mainly for endpoint position control because of the compressibility, viscosity and low output stiffness of air which causes nonlinear flow characteristics. In this paper, pneumatic position control algorithms using fuzzy rule were developed to achieve faster and more stable response than conventional PI control algorithm. The performances of the proposed algorithms were compared by computer simulations with them of PI controller. From those simulations it was shown that the proposed algorithms are more efficient about settling time, steady state error and overshoot than PI control algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.4
• /
• pp.475-481
• /
• 2013

The control system of a direct drive servo valve is a nonlinear system, and the flow force effect on the spool motion is significant and dependent on the load pressure. To satisfy the control system design requirements, the optimal parameters of the lead-lag controller and the derivative feedback controller are searched for using a genetic algorithm and a complex constrained direct search type method. The obtained controller parameters successfully perform their role to satisfy the control system design requirements.

• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.242-244
• /
• 1992

Conventionally in the industrial control, PlD controller has been used because of its robustness, and nonlinear characteristic of a system under control. Although the PlD controller produce suitable parameter of the each system and also variable of PlD controller should be changed according to environment, disturbance, load. In this paper, the convergence and learning accuracy of the back-propagation(BP) method in neural network are investigated by analyzing the reason for decelerating the convergence of BP method. and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative. The modified logistic activation function it proposed by defining the convergence factor based on the analysis and applied to the position and speed control of a DC-servo motor. This paper revealed for experimental, a neural network and a PD controller combined off-line system using developed the position and speed characteristics of a DC-servo motor.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.5
• /
• pp.944-957
• /
• 2007

In general mechanical servo systems, friction deteriorates the performance of controllers by its nonlinear characteristics. Especially, friction phenomenon causes steady-state tracking errors and limit cycles in position and velocity control systems, even though gains of controllers are tuned well in linear system model. Even if sensor is used higher accuracy level, it is difficult to improve tracking performance of the position to the same level with a general control method such as PID type. Therefore, many friction models were proposed and compensation methods have been researched actively. In this paper, we consider that the variation of mover's mass is various by loading and unloading. The normal force variation occurs by it and other parameters. Therefore, the proposed control system is composed of main position controller and a friction compensator. A parameter estimator for a nonlinear friction model is designed by adaptive control law and adaptive backstopping control method.

• Journal of Power System Engineering
• /
• v.2 no.2
• /
• pp.55-59
• /
• 1998

In practice, the property of nonlinearity is contained in all physical systems. In other word, all physical systems are nonlinear to some degree. Therefore it is important that we acquires a facility for analyzing feedback control systems with varying degrees of nonlinearity. To operate the system linearly over wide range of variation of signal amplitude and frequency, the system requires components of an extremely high quality. Such a system would probably be impractical in the view points of cost, space and weight. In this context of view, it is worth noting that the nonlinearities may be intentionally introduced into a system in order to compensate for the effects of other undesirable nonlinearities or to obtain better performance than what could be achieved using linear element only. A simple example of an intentional nonlinearity is the use of a nonlinear damped system to optimize response in accordance with the magnitude of error. In this paper, an on-off type nonlinear controller is introduced and the applicability and validity of a simple on-off controller are presented by the experimental result.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.463-467
• /
• 2005

In this paper, the guidance law applicable to formation flight of UAV in three-dimensional space is proposed. The concept of miss distance, which is commonly used in the missile guidance laws, and Lyapunov stability theorem are effectively combined to obtain the guidance commands of the wingmen. The propose guidance law is easily integrated into the existing flight control system because the guidance commands are given in terms of velocity, flight path angle and heading angle to form the prescribed formation. In this guidance law, communication is required between the leader and the wingmen to achieve autonomous formation. The wingmen are only required the current position and velocity information of the leader vehicle. The performance of the proposed guidance law is evaluated using the complete nonlinear 6-DOF aircraft system. This system is integrated with nonlinear aerodynamic and engine characteristics, actuator servo limitations for control surfaces, various stability and control augmentation system, and autopilots. From the nonlinear simulation results, the new guidance law for formation flight shows that the vehicles involved in formation flight are perfectly formed the prescribed formation satisfying the several constraints such as final velocity, flight path angle, and heading angle.