A Study on Linear Quadratic Regulator with the Desired Low-Pass Property

2013 ◽  
Vol 133 (12) ◽  
pp. 2167-2175 ◽  
Author(s):  
Katsuhiko Fuwa ◽  
Satoshi Murayama ◽  
Tatsuo Narikiyo
2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Oscar Andrew Zongo ◽  
Anant Oonsivilai

This paper presents a comparison between a proportional-integral controller, low pass filters, and the linear quadratic regulator in dealing with the task of eliminating harmonic currents in the grid-connected photovoltaic system. A brief review of the existing methods applied to mitigate harmonic currents is presented. The Perturb & Observe technique was employed for maximum power point tracking. The PI control, low pass filters, and the linear quadratic regulator are discussed in detail in terms of their control strategies. The grid current was analyzed in the system with all three of the controllers applied to control the voltage source inverter of the solar photovoltaic system connected to the grid through an L filter and LCL filter and simulated in MATLAB/SIMULINK. The simulation results obtained have proven the robustness of the linear quadratic regulator over other methods. The technique lowers the grid current total harmonic distortion from 7.85% to 2.13%.


Author(s):  
Jingwen Huang ◽  
Tingting Zhang ◽  
Jian-Qiao Sun

This paper studies control problems of underactuated mechanical systems with model uncertainties. The control is designed with the method of backstepping. The first-order low-pass filters are used to estimate the unknown quantities and to avoid the “explosion of terms.” A novel method is also proposed to implement the control without the knowledge of the control coefficient, which makes the whole process of backstepping control data-driven. The stability of the proposed control in the Lyapunov sense is studied. It is numerically and experimentally validated, and compared with the well-known model-based linear quadratic regulator (LQR) control. The data-driven backstepping control is found to provide comparable performances to that of the LQR control with the advantage of being model-free and robust.


Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 287
Author(s):  
Byeongjin Kim ◽  
Soohyun Kim

Walking algorithms using push-off improve moving efficiency and disturbance rejection performance. However, the algorithm based on classical contact force control requires an exact model or a Force/Torque sensor. This paper proposes a novel contact force control algorithm based on neural networks. The proposed model is adapted to a linear quadratic regulator for position control and balance. The results demonstrate that this neural network-based model can accurately generate force and effectively reduce errors without requiring a sensor. The effectiveness of the algorithm is assessed with the realistic test model. Compared to the Jacobian-based calculation, our algorithm significantly improves the accuracy of the force control. One step simulation was used to analyze the robustness of the algorithm. In summary, this walking control algorithm generates a push-off force with precision and enables it to reject disturbance rapidly.


2020 ◽  
Vol 53 (2) ◽  
pp. 3072-3078
Author(s):  
C. Amo Alonso ◽  
D. Ho ◽  
J.M. Maestre

Author(s):  
Ishan Chawla ◽  
Vikram Chopra ◽  
Ashish Singla

AbstractFrom the last few decades, inverted pendulums have become a benchmark problem in dynamics and control theory. Due to their inherit nature of nonlinearity, instability and underactuation, these are widely used to verify and implement emerging control techniques. Moreover, the dynamics of inverted pendulum systems resemble many real-world systems such as segways, humanoid robots etc. In the literature, a wide range of controllers had been tested on this problem, out of which, the most robust being the sliding mode controller while the most optimal being the linear quadratic regulator (LQR) controller. The former has a problem of non-robust reachability phase while the later lacks the property of robustness. To address these issues in both the controllers, this paper presents the novel implementation of integral sliding mode controller (ISMC) for stabilization of a spatial inverted pendulum (SIP), also known as an x-y-z inverted pendulum. The structure has three control inputs and five controlled outputs. Mathematical modeling of the system is done using Euler Lagrange approach. ISMC has an advantage of eliminating non-robust reachability phase along with enhancing the robustness of the nominal controller (LQR Controller). To validate the robustness of ISMC to matched uncertainties, an input disturbance is added to the nonlinear model of the system. Simulation results on two different case studies demonstrate that the proposed controller is more robust as compared to conventional LQR controller. Furthermore, the problem of chattering in the controller is dealt by smoothening the controller inputs to the system with insignificant loss in robustness.


Author(s):  
Shaharyar Yousaf ◽  
Neelam Mughees ◽  
Abdullah Mughees ◽  
Ali Abbas ◽  
Syed Zulqadar Hassan ◽  
...  

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