Desired dynamic equational proportional‐integral‐derivative controller design based on probabilistic robustness

Author(s):  
Gengjin Shi ◽  
Donghai Li ◽  
Yanjun Ding ◽  
Yang Quan Chen
Author(s):  
Balázs Varga ◽  
Balázs Kulcsár ◽  
Leo Laine ◽  
Manjurul Islam ◽  
Balázs Németh

In this paper, different actuation level steering control methods for an A-double vehicle combination (tractor–semitrailer–dolly–semitrailer) are proposed. The aim of the paper is to show the viability of advanced actuation control strategies for a practical vehicular application. Three different types of robust controller are proposed: a robust proportional–integral–derivative controller, an output feedback linear ℋ∞ controller and an induced ℒ2-norm minimizing linear parameter-varying controller. All controllers are augmented with anti-windup compensators to respect the steering-angle limit and the steering-rate limit. Each model-based controller robustly rejects external disturbances and tracks a reference steering angle generated by the motion control system. Frequency-domain analysis and time-domain analysis prove that the ℋ∞ controller and the linear parameter-varying controller outperform the proportional–integral–derivative controller in terms of reference tracking and disturbance rejection. Comparative simulation scenarios are provided on the basis of the high-fidelity vehicle simulator developed by Volvo Group Trucks Technology.


2021 ◽  
pp. 107754632110055
Author(s):  
Abolfazl Simorgh ◽  
Abolhassan Razminia ◽  
Vladimir I Shiryaev

The second-order systems can capture the dynamics of a vast majority of industrial processes. However, the existence of uncertainty in second-order approximation of such processes is inevitable because the approximation may not be accurate or the operating condition changes, resulting in performance degradation or even instability. This article aims at designing a novel robust proportional–integral–derivative controller for the uncertain second-order delay-free and time-delay systems in an optimal manner. The method is simple, effective, and can efficiently improve the performance of the uncertain systems. The approach is based on the linear quadratic theory, in which by adding a new matrix in the quadratic cost function regarding the uncertainties, the stability of the perturbed system is guaranteed and proven for both time-delay and delay-free second-order cases. The comparison with the recent works in the literature supports the effectiveness of the proposed methodology.


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