Design of Robust Tracking and Disturbance Attenuation Control for Vehicle Lateral Systems: A Modified Equivalent Input Disturbance Approach

IF 3.9 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
S. Mohanapriya, A. Dhavasumani, C. Antony Crispin Sweety, T. Satheesh, R. Sakthivel
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Abstract

In this article, a unified input delay and disturbance compensation issue has been addressed for vehicle lateral systems. Specifically, by compensating for the input delay and disturbances in the addressed system, the intended tracking performance is achieved. Moreover, a modified higher-order equivalent-input-disturbance approach is developed in light of the Majhi-Atherton modified Smith predictor technique, which aids in estimating the disturbances in the system model. In particular, the developed technique integrates the transfer function into the conventional Smith predictor block, so accurate disturbance estimation with the desired input delay compensation is guaranteed. Subsequently, sufficient criteria are formulated in the frame of linear matrix inequalities to affirm the desired tracking performance. Further, the generated linear matrix inequalities are solved to obtain the required gain matrices. In the end, the efficacy and superiority of the suggested control approach are ultimately verified through the simulation analysis for the considered numerical example.

Abstract Image

车辆横向系统鲁棒跟踪与扰动衰减控制设计:一种改进的等效输入扰动方法
本文研究了车辆横向系统的统一输入延迟和扰动补偿问题。具体来说,通过补偿寻址系统中的输入延迟和干扰,达到预期的跟踪性能。此外,在Majhi-Atherton修正Smith预测器技术的基础上,提出了一种改进的高阶等效输入-扰动方法,有助于估计系统模型中的扰动。特别是,该方法将传递函数集成到传统的Smith预测块中,从而保证了在期望的输入延迟补偿下的准确干扰估计。随后,在线性矩阵不等式的框架下,制定了充分的准则来确认期望的跟踪性能。进一步,对生成的线性矩阵不等式进行求解,得到所需的增益矩阵。最后,通过对所考虑的数值算例进行仿真分析,最终验证了所提控制方法的有效性和优越性。
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来源期刊
CiteScore
5.30
自引率
16.10%
发文量
163
审稿时长
5 months
期刊介绍: The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.
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