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A new online delay estimation-based robust adaptive stabilizer for multi-input neutral systems with unknown actuator nonlinearities

机译:基于新的在线延迟估算的鲁棒自适应稳定器,用于多输入中性系统,具有未知的执行器非线性

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Abstract This paper studies the problem of actuator-nonlinearities compensation in the multi-input uncertain neutral systems. The neutral systems with different unknown time-varying delays, unmodeled dynamics, nonlinear perturbations and disturbances are considered. A new methodology based on the online estimation of the delays to compensate for the effects generated by dead-zone and saturation, acting in series on a system's input are presented. The online estimations of the unknown delays are accomplished by adaptive laws that guarantee the exponential stabilities of the estimated delays. In the presence of state time delay, derivative state time delay, unmodeled dynamics, nonlinear perturbations, disturbances and both input dead-zone and saturation, the asymptotic stability of the closed-loop system is ensured and the state response converge to the origin. Finally, the practicability and the efficacy of the proposed approach is demonstrated via a numerical example. Highlights ? Constraints are common in all practical control systems and can have damaging effects on the system performance unless accounted for in the controller design process. ? The problem of actuator-nonlinearities compensation in the multi-input uncertain neutral systems is considered. ? A new approach based on the online estimation of the delays to compensate for the effects generated by unmodeled dynamics, nonlinear perturbations, disturbances and both dead-zone and saturation acting in series on a system's input are presented. ? The online estimations of the unknown delays are accomplished by novel adaptive laws that guarantee the exponential stabilities of the estimated delays. ? Under state time delay, derivative state time delay, system uncertainties and both input dead-zone and saturation, the robust stability of the closed-loop system is guaranteed and the state response converge to the origin. ]]>
机译:<![cdata [ 抽象 本文研究了多输入不确定中性系统中的执行器 - 非线性补偿问题。考虑了具有不同未知的时变延迟,未铭出动力学,非线性扰动和干扰的中性系统。提出了一种新方法,基于在系统输入中串联作用的延迟延迟的延迟的在线估计,以串联作用。未知延迟的在线估计是通过自适应法律实现的,以保证估计延迟的指数稳定性。在存在状态时延,衍生状态时间延迟,未铭出的动力学,非线性扰动,干扰和输入死区和饱和时,确保了闭环系统的渐近稳定性,并且状态响应会聚到原点。最后,通过数值示例来证明所提出的方法的实用性和功效。 突出显示 约束在所有实用控制系统中都是常见的,除非在控制器设计过程中占据账户,否则可能对系统性能有损害影响。 多输入不确定中性系统中的执行器 - 非线性补偿问题被考虑。 基于延迟延迟的在线估计的新方法,以补偿未拼接动态,非线性扰动产生的效果介绍了在系统输入中串联作用的干扰和饱和区和饱和区。 未知延迟的在线估计是通过新的自适应法律来实现,保证估计延迟的指数稳定性。 在状态下>时间延迟,衍生状态时间延迟,系统不确定性和输入死区和饱和,保证闭环系统的鲁棒稳定性,并且状态响应会聚到原点。 ]]>

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