• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.555-561
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• 2012

This paper describes the design of a fuzzy adaptive sliding mode controller for tracking control of robotic manipulators. The proposed controller incorporates a modified traditional sliding mode controller to drive the system state to a sliding surface and then keep the system state on this surface, and a fuzzy logic controller to accelerate the reaching phase. The stability of the control system is ensured by using Lyapunov theory. To verify the effectiveness of the proposed controller, computer simulation is conducted for a five-bar planar robotic manipulator. The simulation results show that the proposed controller can improve the reaching time and eliminate chattering of the control system at the same time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.977-983
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• 2011

This paper proposes a new adaptive speed controller to achieve a robust speed control of a permanent magnet synchronous motor(PMSM). The proposed adaptive regulator does not require any information on the motor parameter and load torque values, so it is very insensitive to model parameter and load torque variations. Also, the stability of the proposed adaptive control system is proven. To validate the robustness of the proposed adaptive speed controller, both simulation and experimental results are provided under motor parameter and load torque variations. It is clearly demonstrated that the proposed adaptive regulator can accurately control the speed of permanent magnet synchronous motors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.177-178
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• 2012

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.140-146
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• 1993

Active noise control uses the intentional superposition of acoustic waves to create a destructive interference pattern such that a reduction of the unwanted sound occurs. In active noise control system the choice of a control structure and design of the controller are the main issues of concern. In real acoustic fields there are a vast number of noise sources with time-varying nature and the characteristics of transducers and the geometric set-up of control system are subject to change. Accordingly the control system should be designed to adapt such circumstances so that required level of performance is maintained. In this paper, the adaptive control algorithm for self-tuning adaptive controller is presented for the application in active noise control system. Self-tuning is a direct integration of identification and controller design algorithm in such a manner that the two processes proceed sequentially. The least mean square algorithm was used for the identification schemes and adaptive weighted minimum variance control algorithm was applied for self-tuning controller. Computer simulation results for self-tuning feedback controller are presented. And simulation results was shown to be useful for the situation in which the periodic noise sources act on the acoustic field.

• Journal of Mechanical Science and Technology
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• v.15 no.9
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• pp.1248-1256
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• 2001

In this study, a test bed for vehicle longitudinal control is developed using a chassis dynamometer and real time 3-D graphics. The proposed test bed system consists of a chassis dynamometer on which test vehicle can run longitudinally, a video system that shows virtual driver view, and computers that control the test vehicle and realize the real time 3-D graphics. The purpose of the proposed system is to test vehicle longitudinal control and warning algorithms such as Adaptive Cruise Control(ACC), stop and go systems, and collision warning systems. For acceleration and deceleration situations which only need throttle movements, a vehicle longitudinal spacing control algorithm has been tested on the test bed. The spacing control algorithm has been designed based on sliding mode control and road grade estimation scheme which utilizes the vehicle engine torque map and gear shift information.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.596-606
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• 2008

In this paper, we present a co-design methodology of dynamic optimal network-bandwidth allocation (ONBA) and adaptive control for networked control systems (NCSs) to optimize overall control performance and reduce total network-bandwidth usage. The proposed dynamic co-design strategy integrates adaptive feedback control with real-time scheduling. As part of this co-design methodology, a "closed-loop" ONBA algorithm for NCSs with communication constraints is presented. Network-bandwidth is dynamically assigned to each control loop according to the quality of performance (QoP) information of each control loop. As another part of the co-design methodology, a network quality of service (QoS)-adaptive control design approach is also presented. The idea is based on calculating new control values with reference to the network QoS parameters such as time delays and packet losses measured online. Simulation results show that this co-design approach significantly improves overall control performance and utilizes less bandwidth compared to static strategies.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.40.2-40
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• 2002

This paper presents the reconfigurable flight controller in the presence of jammed actuator fault using the adaptive sliding mode control scheme. It is developed under the assumption that the control surface fault cannot be detected and the positions of stuck control surfaces are unknown. It is well known that sliding mode controller shows good performance for the systems with various uncertainties. None-operating stuck actuator makes the system behave like bias which degrades the system performance and sometimes destabilizes the system. Therefore, the bias term generated by actuator faults has to be compensated by the control system. To the objective, we adopt the adaptive sliding mode cont...

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.547-555
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• 2003

This paper presents an adaptive control against uncertainties in tail-controlled STT (Skid-to-Turn) missiles. We derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.637-650
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• 2007

A new on-line fault detection and isolation(FDI) scheme has been proposed for engines using an adaptive neural network classifier; this paper investigates the robustness of this scheme by evaluating in a wide range of operational modes. The neural classifier is made adaptive to cope with the significant parameter uncertainty, disturbances, and environmental changes. The developed scheme is capable of diagnosing faults in the on-line mode and can be directly implemented in an on-board diagnosis system(hardware). The robustness of the FDI for the closed-loop system with crankshaft speed feedback is investigated by testing it for a wide range of operational modes, including robustness against fixed and sinusoidal throttle angle inputs, change in load, change in an engine parameter, and all changes occurring simultaneously. The evaluations are performed using a mean value engine model(MVEM), which is a widely used benchmark model for engine control system and FDI system design. The simulation results confirm the robustness of the proposed method for various uncertainties and disturbances.

• 전기의세계
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• v.30 no.12
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• pp.822-831
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• 1981

Many different schemes of the adaptive observer and controller have been developed for both continuous and discrete systems. In this paper we have presented a new scheme of the reduced order adaptive observer for the single input discrete linear time invariant plant. The output equation of the plant, is transformed into the bilinear form in terms of system parameters and the states of the state variable filters. Using the plant output equation the discrete implicit adaptive observer based on the similar philosophy to Nuyan and Carroll is derived and the parameter adaptation algorithm is derived based on the exponentially weighted least square method. The adaptive model following control system is also constructed according to the proposed observer scheme. The proposed observer and controller are rather than simple structure and have a fast adaptive algorithm, so it may be expected that the scheme is suitable to the practical application of control system design. The effectiveness of the algorithm and structure is illustrated by the computer simulation of a third order system. The simulation results show that the convergence speed is proportinal to the increasing of weighting factor alpha, and that the full order and reduced order observer have similar convergence characteristics.