• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1080-1085
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• 2005

A hybrid control scheme is proposed for the stabilization of backward movement along simple paths for a vehicle composed of a truck and six trailers. The hybrid comprises the combination of a linear quadratic regulator (LQR) and a neurocontroller (NC) that is trained by a genetic algorithm (GA). Acting singly, either the NC or the LQR are unable to perform satisfactorily over the entire range of the operation required, but the proposed hybrid is shown to be capable of providing good overall system performance. The evaluation function of the NC in the hybrid design has been modified from the conventional type to incorporate both the squared errors and the running steps errors. The reverse movement of the trailer-truck system can be modeled as an unstable nonlinear system, with the control problem focusing on the steering angle. Achieving good backward movement is difficult because of the restraints of physical angular limitations. Due to these constraints the system is impossible to globally stabilize with standard smooth control techniques, since some initial states necessarily lead to jack-knife locks. This paper demonstrates that a hybrid of neural networks and LQR can be used effectively for the control of nonlinear dynamical systems. Results from simulated trials are reported.

• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.391-402
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• 2015

In this paper, we present implementation of backward movement control of truck-trailer vehicles using a fuzzy mode-based control scheme considering practical constraints and computational overhead. We propose a fuzzy feedback controller where output is predicted with the delay of a unit sampling period. Analysis and design of the proposed controller is very easy, because it is synchronized with sampling time. Stability analysis is also possible when quantization exists in the implementation of fuzzy control architectures, and we show that if the trivial solution of the fuzzy control system without quantization is asymptotically stable, then the solutions of the fuzzy control system with quantization are uniformly ultimately bounded. Experimental results using a toy truck show that the proposed control system outperforms a conventional system.

• 전자공학회논문지 IE
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• 제46권2호
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• pp.33-45
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• 2009

본 논문은 실제적인 제약, 컴퓨팅 시간 지연, 양자화를 고려하여 퍼지 모델을 기초로 한 제어기를 트럭-트레일러 타입의 모바일 로봇의 귀환 제어기에 적용하여 설계하였다. 퍼지 귀환 제어기의 출력은 단위 샘플링 시간동안 지연되므로 이를 예측하여 설계하였다. 시간 지연을 고려한 해석 및 디자인 문제는 제안된 제어기가 샘플링 시간과 동기되어 있기 때문에 쉽게 해결된다. 또한 퍼지 제어기 구조 개발 시 양자화가 이루어지기 때문에 안정성 있는 해석이 가능하고 양자화 이외에 발생하는 사소한 문제도 역시 안정함을 보여주므로, 양자화한 시스템은 일반적으로는 극단적인 수렴을 한다. 실험결과에서 제안된 시스템의 효율성이 증명됨을 볼 수 있다.