Abbas Nadir, Pan Xuejun, Raheem Abdur, Shakoor Rabia, Arfeen Zeeshan Ahmad, Rashid Muhammad, Umer Farhana, Safdar Nouman, Liu Xiaodong
School of Electrical Engineering, Dalian University of Technology, Dalian, 116024, China.
Department of Electrical Engineering, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan.
Sci Rep. 2022 Oct 25;12(1):17852. doi: 10.1038/s41598-022-21357-3.
This work is used to design a novel robust optimization control law augmented with Robust Generalized Dynamic Inversion (RGDI) for continuous varying perturbations in the Twin Rotor MIMO System (TRMS). The perturbations like coupling effect, un-known states, gyroscopic disturbance torque, parametric uncertainties and parametric disturbances are considered as unwanted signal which should be optimized by an efficient controller. The variable structured systems like the TRMS (prototype) have great focus due to its high computational cost with a higher order non-linear behavior. The RGDI based controller designed to remove nonlinear dynamics as well as to avoid singularity issue with the augmentation of stability based mathematical operations (lyapunov stability analysis, controllability and observability matrices ) in the presence of considered perturbations during implementation. In this paper, we develop estimation of state deviation calculation between control angles and desired angles known as Euclidean error norm. The next step was to design RGDI based controller [Sliding Mode Control (SMC) and [Formula: see text] optimization] to minimize considered perturbations as well as the computational cost. The sharp (rapid) chattering phenomena in RGDI based SMC reduce the actuators performance that goes towards the failure of actuators. While the RGDI based [Formula: see text] optimization overcome the computational cost and minimizes [Formula: see text] norm that's guaranteeing the robust stability as well as robust performance. The robustness of the optimization control technique validated by taking its worst case via MATLAB-Simulation. A real-time implementation applied to evaluate the worth of novel dynamic approach.
这项工作用于设计一种新颖的鲁棒优化控制律，该控制律通过鲁棒广义动态逆（RGDI）增强，以应对双转子多输入多输出系统（TRMS）中的连续变化扰动。诸如耦合效应、未知状态、陀螺干扰力矩、参数不确定性和参数扰动等扰动被视为有害信号，应由高效控制器进行优化。像TRMS（原型）这样的变结构系统因其高阶非线性行为带来的高计算成本而备受关注。基于RGDI设计的控制器旨在消除非线性动力学，并在实施过程中存在所考虑的扰动时，通过基于稳定性的数学运算（李雅普诺夫稳定性分析、可控性和可观性矩阵）的增强来避免奇异性问题。在本文中，我们开发了控制角度与期望角度之间的状态偏差计算估计，即欧几里得误差范数。下一步是设计基于RGDI的控制器[滑模控制（SMC）和[公式：见原文]优化]，以最小化所考虑的扰动以及计算成本。基于RGDI的SMC中的尖锐（快速）抖振现象会降低执行器性能，甚至导致执行器故障。而基于RGDI的[公式：见原文]优化克服了计算成本，并最小化了[公式：见原文]范数，从而保证了鲁棒稳定性和鲁棒性能。通过MATLAB仿真采用其最坏情况验证了优化控制技术的鲁棒性。应用实时实现来评估这种新颖动态方法的价值。
