Ya-Fu Peng - IEEE Xplore Author Profile

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A wavelet neural network (WNN)-based robust total-sliding-mode control scheme is developed for the synchronization of uncertain chaotic systems. The proposed control system offers a design method to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive WNN controller and a robust compensator. The adaptive WNN controller acts as the principal tracking controll...Show More
In this study, an adaptive output recurrent cerebellar model articulation controller (AORCMAC) is proposed for a human conveyance vehicle (HCV) control problem. A mechatronic system structure of the two wheels vehicle driven by two dc motors is briefly described. The main purpose of this paper is to develop a self-dynamic balancing and motion control strategy. Variable learning-rates for analytica...Show More
In this paper, an adaptive intelligent tracking control (AITC) system employs an output recurrent cerebellar model articulation controller (ORCMAC) is developed for uncertain nonlinear system. In the AITC design, the Taylor linearization technique is employed to increase the learning ability of ORCMAC and the on-line adaptive laws are derived based on the Lyapunov stability analysis and the H℞ con...Show More
An output recurrent cerebellar model articulation controller (ORCMAC) via the backstepping control technique is designed to control a linear ultrasonic motor (LUSM) for the tracking of periodic reference trajectories in this paper. The proposed ORCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) in efficient learning mechanism and dynamic response. In...Show More
This paper describes the design and implement of a two-wheel transporter control system. In order to develop a self-dynamic balancing and motion control strategy, a fuzzy control algorithm has been proposed. Thus intelligent two-wheel transporter is demonstrated. Finally, experimental results prove that the proposed architecture can control the whole system very well.Show More
In this paper, an intelligent adaptive control system using an adaptive recurrent cerebellar model articulation controller (RCMAC) and based on H/sup /spl infin// control technique is developed for uncertain nonlinear system to achieve H/sup /spl infin// tracking performance. The proposed dynamic structure of RCMAC has superior capability to the conventional static cerebellar model articulation co...Show More
Since the dynamic characteristics of linear ultrasonic motor (LUSM) are highly nonlinear and time varying and the model is difficult to obtain, it is difficult to design a suitable controller to achieve high-precision position control by using the conventional control techniques. An intelligent tracking control system using an adaptive recurrent cerebellar model articulation controller (RCMAC) is ...Show More
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a ...Show More
In this study, an adaptive hybrid control system using a new cerebellar model articulation controller (CMAC) network paradigm called recurrent CMAC (RCMAC) network, which is proposed to control the moving table of the linear piezoelectric ceramic motor (LPCM) drive system to achieve high-precision position control with robustness. The architecture of RCMAC network is a modified model of the CMAC n...Show More
In this study, an adaptive recurrent cerebellar model articulation controller (ARCMAC) is designed for feedback control system with unknown dynamics. The proposed ARCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) in efficient learning mechanism, guaranteed system stability and dynamic response. Temporal relations are embedded in ARCMAC by adding fee...Show More
This work presents an adaptive hybrid control system using a diagonal recurrent cerebellar-model-articulation-computer (DRCMAC) network to control a linear piezoelectric ceramic motor (LPCM) driven by a two-inductance two-capacitance (LLCC) resonant inverter. Since the dynamic characteristics and motor parameters of the LPCM are highly nonlinear and time varying, an adaptive hybrid control system ...Show More
In this study, a robust cerebellar model articulation controller (RCMAC) is designed for unknown nonlinear systems. The RCMAC is comprised of a cerebellar model articulation controller (CMAC) and a robust controller. The CMAC is utilized to approximate an ideal controller, and the weights of the CMAC are on-line tuned by the derived adaptive law based on the Lyapunov sense. The robust controller i...Show More
This paper proposes a control scheme for the car-following collision prevention systems using a robust cerebellar model articulation controller (CMAC) via the backstepping control technique. In the robust CMAC backstepping control system, an adaptive CMAC is used to mimic an ideal backstepping control law and a robust controller is designed to compensate for the difference between the ideal backst...Show More
An adaptive cerebellar-model-articulation-controller (CMAC)-based supervisory control system is developed for uncertain nonlinear systems. This adaptive CMAC-based supervisory control system consists of an adaptive CMAC and a supervisory controller. In the adaptive CMAC, a CMAC is used to mimic an ideal control law and a compensated controller is designed to recover the residual of the approximati...Show More
In this paper, an adaptive cerebellar-model articulation computer (CMAC) neural network (NN) control system is developed for a linear piezoelectric ceramic motor (LPCM) that is driven by an LLCC-resonant inverter. The motor structure and LLCC-resonant driving circuit of an LPCM are introduced initially. The LLCC-resonant driving circuit is designed to operate at an optimal switching frequency such...Show More
In this study, we present a design method for a model reference control structure using a cerebellar model articulation controller (CMAC). Since the dynamic characteristics and motor parameters of the linear piezoelectric ceramic motor (LPCM) are highly nonlinear and time-varying. An adaptive CMAC model reference control system is proposed to control the position of the moving table of the LPCM to...Show More