scholarly journals Research on Control Method of Keeping Flight Formation by Using SDRE on the Sun-Earth Libration Points

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
He Zhenqi ◽  
Zhang Ke ◽  
Lv Meibai
Keyword(s):  
Control Method ◽  
Libration Point ◽  
Linear Quadratic Regulator ◽  
Transition Process ◽  
Continuous Control ◽  
The Sun ◽  
Nonlinear Dynamic Model ◽  
Linear Quadratic ◽  
State Dependent ◽  
Lqr Controller

Keeping the flying formation of spacecraft is a key problem which needs to be solved in deep space exploration missions. In this paper, the nonlinear dynamic model of formation flying is established and a series of transformations are carried out on this model equation. By using SDRE (State-Dependent Riccati Equation) algorithm, the optimal control of flying formation is realized. Compared with the traditional control method based on the average orbit elements and LQR (Linear Quadratic Regulator) control method, the SDRE control method has higher control precision and is more suitable for the advantages of continuous control in practical engineering. Finally, the parameter values of the sun-earth libration point L2 are substituted in the equation and simulation is performed. The simulation curves of SDRE controller are compared with LQR controller. The results show that the SDRE controllers time cost is less than the LQR controllers and the former’s fuel consumption is less than the latter’s in the system transition process.

scholarly journals System design for inverted pendulum using LQR control via IoT

2020 ◽  
Vol 11 ◽  
pp. 12
Author(s):  
Dechrit Maneetham ◽  
Petrus Sutyasadi
Keyword(s):  
Inverted Pendulum ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Lqr Controller ◽  
Model Tuning ◽  
And Performance ◽  
Performance Results ◽  
And Control

This research proposes control method to balance and stabilize an inverted pendulum. A robust control was analyzed and adjusted to the model output with real time feedback. The feedback was obtained using state space equation of the feedback controller. A linear quadratic regulator (LQR) model tuning and control was applied to the inverted pendulum using internet of things (IoT). The system's conditions and performance could be monitored and controlled via personal computer (PC) and mobile phone. Finally, the inverted pendulum was able to be controlled using the LQR controller and the IoT communication developed will monitor to check the all conditions and performance results as well as help the inverted pendulum improved various operations of IoT control is discussed.

Study of the LQR Controller for Magnetic Flywheel Rotor System

2012 ◽  
Vol 150 ◽  
pp. 221-226 ◽  
Author(s):  
Xiang Long Wen ◽  
Chun Sheng Song ◽  
Cao Cao ◽  
Guo Ping Ding
Keyword(s):  
High Speed ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Rotor System ◽  
Linear Quadratic ◽  
Gyroscopic Effect ◽  
Lqr Controller ◽  
The Stability ◽  
Gyroscopic Effects ◽  
Flywheel Rotor

Gyroscopic effects in the flywheel rotor greatly influence rotor stability especially at high speed. When the pole-zero position moves to right of s-plane, the damping of the pole is getting smaller, and the stability of system is getting worse with the increasing of rotor speed when the decentralized PD control law is used only. The LQR (linear quadratic regulator) control method is used to reduce gyroscopic effect and forced vibration. The simulation results show that LQR controller have a good performance on the reduction of gyroscopic effect and vibration of magnetic flywheel rotor system.

scholarly journals Study on maintaining formations during satellite formation flying based on SDRE and LQR

Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 394-399 ◽  
Author(s):  
Zhang Ke ◽  
He Zhenqi ◽  
Lv Meibo
Keyword(s):  
Optimal Control ◽  
Control Algorithm ◽  
Formation Flying ◽  
Control Method ◽  
Process Time ◽  
Engineering Practice ◽  
Continuous Control ◽  
Linear Quadratic ◽  
Orbit Element ◽  
Lqr Controller

AbstractDue to the influence of various perturbations of space, satellites flying in formation cannot maintain specific configurations for long durations [1, 2]. In order to ensure that formation configurations are able to meet the requirements of space missions, it is important to maintain control of formation configurations. This is an urgent problem to be solved. The traditional control method for controlling formations is based on the average orbit element, and uses the assumption that the average orbit element deviation and the instantaneous orbit element deviation are approximately equal. However, the continuous control system is more difficult to achieve in engineering practice. Using a LQR (linear quadratic regulator) optimal control algorithm and SDRE (state-dependent Riccati equation) optimal control algorithm to maintain the formation flying [3, 4]. Through simulation, it was found that when using the SDRE controller in the system transition process time is shorter than when the LQR controller is used, and fuel consumption is less for the SDRE controller than for the LQR controller.

Dynamics Analysis and Control Method of a Novel Spherical Robot

2009 ◽  
Author(s):  
Hanxu Sun ◽  
Yili Zheng ◽  
Qingxuan Jia
Keyword(s):  
Control Method ◽  
Linear Quadratic Regulator ◽  
High Rate ◽  
Pd Controller ◽  
Velocity Control ◽  
Spherical Robot ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
Gyroscopic Effects ◽  
And Control

A novel omni-directional rolling spherical robot equipped with a high-rate flywheel (BYQ-V) is presented; the mechanical structure of the robot are given, and the gyroscopic effects of high-rate flywheel can improve the dynamic stability of the robot. The simplified dynamic model of the robot is derived based on the constrained Lagrangian method. Moreover, a Linear Quadratic Regulator (LQR) controller and a Percentage Derivative (PD) controller are designed to implement the pose and velocity control of the robot respectively, Finally, the control method are validated through continuous circle motion experiment. This robot is designed for territory or lunar exploration in the future.

Robust stabilization control of a spatial inverted pendulum using integral sliding mode controller

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ishan Chawla ◽  
Vikram Chopra ◽  
Ashish Singla
Keyword(s):  
Inverted Pendulum ◽  
Sliding Mode ◽  
Robust Stabilization ◽  
Linear Quadratic Regulator ◽  
Humanoid Robots ◽  
Sliding Mode Controller ◽  
Linear Quadratic ◽  
Integral Sliding Mode ◽  
Wide Range ◽  
Lqr Controller

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.

scholarly journals FULL CAR ACTIVE DAMPING SYSTEM FOR VIBRATION CONTROL

2020 ◽  
Vol 6 (4) ◽  
pp. 1-17
Author(s):  
G. Yakubu ◽  
G. Sani ◽  
S. B. Abdulkadir ◽  
A. A.Jimoh ◽  
M. Francis
Keyword(s):  
Mathematical Model ◽  
Linear Quadratic Regulator ◽  
Active Damping ◽  
Settling Time ◽  
Linear Quadratic ◽  
Body Acceleration ◽  
The Road ◽  
Road Profile ◽  
Lqr Controller ◽  
Mass Displacement

Full car passive and active damping system mathematical model was developed. Computer simulation using MATLAB was performed and analyzed. Two different road profile were used to check the performance of the passive and active damping using Linear Quadratic Regulator controller (LQR)Road profile 1 has three bumps with amplitude of 0.05m, 0.025 m and 0.05 m. Road profile 2 has a bump with amplitude of 0.05 m and a hole of -0.025 m. For all the road profiles, there were 100% amplitude reduction in Wheel displacement, Wheel deflection, Suspension travel and body displacement, and 97.5% amplitude reduction in body acceleration for active damping with LQR controller as compared to the road profile and 54.0% amplitude reduction in body acceleration as compared to the passive damping system. For the two road profiles, the settling time for all the observed parameters was less than two (2) seconds. The present work gave faster settling time for mass displacement, body acceleration and wheel displacement.

scholarly journals The linear quadratic regular algorithm-based control system of the direct current motor

2019 ◽  
Vol 10 (2) ◽  
pp. 768
Author(s):  
Trong-Thang Nguyen
Keyword(s):  
Control System ◽  
Direct Current ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
Response Speed ◽  
Dc Motor ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
Mathematical Equations ◽  
Feed Forward Controller

<span>This research aims to propose an optimal controller for controlling the speed of the Direct Current (DC) motor. Based on the mathematical equations of DC Motor, the author builds the equations of the state space model and builds the linear quadratic regulator (LQR) controller to minimize the error between the set speed and the response speed of DC motor. The results of the proposed controller are compared with the traditional controllers as the PID, the feed-forward controller. The simulation results show that the quality of the control system in the case of LQR controller is much higher than the traditional controllers. The response speed always follows the set speed with the short conversion time, there isn't overshoot. The response speed is almost unaffected when the torque impact on the shaft is changed.</span>

scholarly journals Simulation of a Steam Injected Gas Turbine Plant Control System

1997 ◽  
Author(s):  
Shusheng Zang ◽  
Jaqiang Pan
Keyword(s):  
Gas Turbine ◽  
Flow Rate ◽  
Controller Design ◽  
Dynamic Performance ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Turbine Plant ◽  
Fuel Flow ◽  
Lqr Controller ◽  
Gas Turbine Plant

The design of a modern Linear Quadratic Regulator (LQR) is described for a test steam injected gas turbine (STIG) unit. The LQR controller is obtained by using the fuel flow rate and the injected steam flow rate as the output parameters. To meet the goal of the shaft speed control, a classical Proportional Differential (PD) controller is compared to the LQR controller design. The control performance of the dynamic response of the STIG plant in the case of rejection of load is evaluated. The results of the computer simulation show a remarkable improvement on the dynamic performance of the STIG unit.

Real-Time Control of a Rotary Inverted Pendulum using Robust LQR-based ANFIS Controller

2018 ◽  
Vol 19 (3-4) ◽  
pp. 379-389 ◽  
Author(s):  
Ishan Chawla ◽  
Ashish Singla
Keyword(s):  
Fuzzy Inference System ◽  
Inverted Pendulum ◽  
Fuzzy Inference ◽  
Sliding Mode ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Inference System ◽  
Wide Range ◽  
Lqr Controller ◽  
Rotary Inverted Pendulum

AbstractFrom the last five decades, inverted pendulum (IP) has been considered as a benchmark problem in the control literature due to its inherit nature of instability, non-linearity and underactuation. Its applicability in wide range of practical systems, demands the need of a robust controller. It is found in the literature that wide range of controllers had been tested on this problem, out of which the most robust being sliding mode controller while the most optimal being linear quadratic regulator (LQR) controller. The former has a problem of discontinuity and chattering, while the latter lacks the property of robustness. To address the robustness issue in LQR controller, this paper proposes a novel robust LQR-based adaptive neural based fuzzy inference system controller, which is a hybrid of LQR and fuzzy inference system. The proposed controller is designed and implemented on rotary inverted pendulum. Further, to validate the robustness of proposed controller to parametric uncertainties, pendulum mass is varied. Simulation and experimental results show that as compared to LQR controller, the proposed controller is robust to variations in pendulum mass and has shown satisfactory performance.

scholarly journals Nonlinear Control Design of a Half-Car Model Using Feedback Linearization and an LQR Controller

2020 ◽  
Vol 10 (9) ◽  
pp. 3075
Author(s):  
Muhammad Aseer Khan ◽  
Muhammad Abid ◽  
Nisar Ahmed ◽  
Abdul Wadood ◽  
Herie Park
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
Control Technique ◽  
Effective Control ◽  
Ride Quality ◽  
Linear Quadratic ◽  
Suspension Systems ◽  
Car Model ◽  
Road Disturbance ◽  
Lqr Controller

Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for off-road applications. The nonlinearities tend to degrade the performance of active suspension systems; these introduce harshness to the ride quality and reduce off-road mobility. Typical control strategies rely on linear models of the suspension dynamics. While these models are convenient, nominally accurate, and controllable due to the abundance of linear control techniques, they neglect the nonlinearities present in real suspension systems. The techniques already implemented and methods used to cope with problem of Half-Car model were studied. Every method and technique had some drawbacks in terms of complexity, cost-effectiveness, and ease of real time implementation. In this paper, an improved control method for Half-Car model was proposed. First, input/output feedback linearization was performed to convert the nonlinear system of Half-Car model into an equivalent linear system. This was followed by a Linear Quadratic Regulator (LQR) controller. This controller had minimized the effects of road disturbances by designing a gain matrix with optimal robustness properties. The proposed control technique was applied in the presence of the deterministic road disturbance. The results were verified using the Matlab/Simulink toolbox.

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