• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.38 no.6
• /
• pp.28-36
• /
• 2001

A robust adaptive sliding mode robot control algorithm is derived, which consists of a feed-forward compensation part and discontinuous control part. The unknown parameters is categorized into two groups, with group containing the parameters estimated on-line, and group containing the parameters not estimated on-line. Then a sliding control term is incorporated into the torque input in order to account for the effects of uncertainties on the parameters not estimated on-line and of disturbances. Moreover, the algorithm is computationally simple, due to an effective exploitation of the structure of manipulator dynamics. It is shown that, despite the existence of the parameter uncertainty and external disturbances, the controller is globally asymptotically stable and guarantees zero tracking errors.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.26 no.2
• /
• pp.157-164
• /
• 2016

The paper studies a comparison analysis of semi-active control strategies for a Macpherson strut type suspension system consisting of MR(magneto-rheological) damper. As a first step, in order to formulate governing, a dynamic full model of a Macpherson strut is developed considering the kinematics. The nonlinear equation of motion of the strut is then linearized around the equilibrium point. A new adaptive moving sliding model controller is developed for fast response of the system. A newly proposed adaptive moving sliding mode control strategy is then compared with conventional sliding mode controller and skyhook controller. The comparison is made for two different types of road inputs; bump and random road profiles showing superior vibration control performance in time and frequency domains.

• Journal of Ocean Engineering and Technology
• /
• v.16 no.1
• /
• pp.8-15
• /
• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.2
• /
• pp.95-102
• /
• 2001

Fuzzy system is capable of uniformly approximating any nonlinear function over compact input space. The applications of fuzzy system, however, have been primarily limited by the need for large number of fuzzy rules, in particular, for the high-order nonlinear system. In this paper, we propose the reconstruction methods of fuzzy systems, parallel type and cascade, based on the decomposition of some classes of high-order nonlinear functions. Using the both types appropriately, we can reduce the number of fuzzy rules geometrically. It can be applied to the fuzzy system that has an online adaptive structure. Two examples of adaptive fuzzy sliding mode control are shown in the computer simulations to verify the validity of the proposed algorithm.

• International Journal of Automotive Technology
• /
• v.8 no.2
• /
• pp.211-217
• /
• 2007

The wheel slip control systems are able to control the braking force more accurately and can be adapted to different vehicles more easily than conventional ABS (Anti-lock Brake System) systems. In realizing the wheel slip control systems, real-time information such as the tire braking force at each wheel is required. In addition, the optimal target slip values need to be determined depending on the braking objectives such as minimum braking distance and stability enhancement. In this paper, a robust wheel slip controller is developed based on the adaptive sliding mode control method and an optimal target slip assignment algorithm is proposed for maximizing the braking force. An adaptive law is formulated to estimate the braking force in real-time. The wheel slip controller is designed based on the Lyapunov stability theory considering the error bounds in estimating the braking force and the brake disk-pad friction coefficient. The target slip assignment algorithm searches for the optimal target slip value based on the estimated braking force. The performance of the proposed wheel slip control system is verified in HILS (Hardware-In-the-Loop Simulator) experiments and demonstrates the effectiveness of the wheel slip control in various road conditions.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.25 no.3
• /
• pp.262-268
• /
• 1988

In this paper conditions are derived, which ensure the existence of a quasi-sliding mode on the control switching hyperplane in discrete variable structure control systems and also remove the reaching phase problem observed in continuous-time variable structure systems. In addition, a discrete variable structure tracking controller which has adaptive properties is devised based on these results. This controller has useful properties, such as small sensitivity to the variation of plant parameters and to disturbances and its performing speed is fast compared to that of other adaptive controller.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.9
• /
• pp.788-792
• /
• 2001

Although the general sliding model control has the robust property, bounds on the disturbances and parameter variations should be known a prior to the designer of the control system. However, these bounds may not be easily obtained. Fuzzy logic provides an effective way to design a controller of the system with disturbances and parameter variations. Therefore, combination of the best feature of the fuzzy logic control and the sliding mode control is considered. In this paper, the adaptive fuzzy variable structure controller developed for variables of fuzzy logic. A variable length pendulum system is used to demonstrate the availability of the proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.2
• /
• pp.98-106
• /
• 2013

This paper proposes fault tolerant control laws using sliding mode control and adaptation laws for a satellite with reaction wheel faults. Considering system parameter errors and faults uncertainties in the dynamics of satellite, the control laws were designed. It was assumed that only reaction wheel failures occurred as faults. The reaction wheel faults were reflected in the multiply form. Because the proposed control laws satisfy the Lyapunov stability theorem, the stability is guaranteed. Through computer simulation, it was assured that the proposed adaptive sliding mode controller has a better performance than the existing sliding mode controller under unstable angular rates.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.05a
• /
• pp.249-255
• /
• 2000

HRIV(Hybrid Rule-Interval Variation) method is presented to stabilize a class of nonlinear systems, where SMC(Sliding Mode Control) and ADC (ADaptive Control) schemes are incorporated to overcome the unstable characteristics of a conventional FLC(Fuzzy Logic Control). HRIV method consists of two modes: I-mode (Integral Sliding Mode PLC) and R-mode(RIV method). In I-mode, SMC is used to compensate for MAE(Minimum Approximation Error) caused by the heuristic characteristics of FLC. In R-mode, RIV method reduces interval lengths of rules as states converge to an equilibrium point, which makes the defined Lyapunov function candidate negative semi-definite without considering MAE, and the new uncertain parameters generated in R-mode are compensated by SMC. In RIV method, the overcontraction problem that the states are out of a rule-table can happen by the excessive reduction of rule intervals, which is solved with a dynamic modification of rule-intervals and a transition to I-mode. Especially, HRIV method has advantages to use the analytic upper bound of MAE and to reduce Its effect in the control input, compared with the previous researches. Finally, the proposed method is applied to stabilize a simple nonlinear system and a modified inverted pendulum system in simulation experiments.

• Proceedings of the KIPE Conference
• /
• 1998.10a
• /
• pp.774-779
• /
• 1998

For the speed control of motors, the position or speed sensors are necessary to obtain the position information of the rotor. Specially, SRM(Switched Reluctance Motor) needs an accurate rotor position data because both the rotor and the stator have a salient pole structure. High functional sensors like resolver or encoder are expensive and have complex connecting lines to the controller so the pure signals are apt to be mixed with noised. In the sight of SRM drives, the high temperature, heavy dust, and the EMI surroundings reduce the reliability of speed and position sensors. Therefore, the speed and position sensorless control algorithms using observer have been accepted widely. In this paper An adaptive sliding observer is described to control the SRM without speed or position sensors. The adaptive sliding observer is set on the basis of variable structure control theory. The sliding surface is constructed by current error terms and this surface guarantees the errors converge to "zero". The stability of observer is affirmed by Lyapunov stability analysis and popov's hyper stability theory.ty theory.