scholarly journals Control for the Space Tether System Motion

2020 ◽  
pp. 106-116
Author(s):  
Maria Cecilia Zanardi ◽  
Paola da Rosa Prado ◽  
Leandro Baroni
Keyword(s):  
State Feedback ◽  
Equations Of Motion ◽  
Orbital Plane ◽  
Linear Quadratic Regulator ◽  
Effective Control ◽  
Feedback Gain ◽  
Second Variation ◽  
Linear Quadratic ◽  
Space Tether ◽  
The Second Variation

This paper proposed a study of a spatial tether system (STS), composed by two satellite (a main satellite and a subsatellite), with the objective of developing a control system in which the motion of the subsatellite is limited in the orbital plane of the main satellite. The linear quadratic regulator (LQR) method is used to implement this control, which is an optimal control with state feedback to predict the linearization of the equations of motion to calculate the feedback gain, using the resolution of Riccati equation. The results show an effective control, with the motion of the subsatellite limited only to the stretch of the cable that links both satellites. However, it is necessary to introduce an auxiliary torque, since the linearized equation associated with the second variation of the angle out of the plan does not have a term independent of the state vector.

Two-degree-of-freedom multi-input multi-output proportional–integral–derivative control design: Application to quadruple-tank system

2018 ◽  
Vol 233 (3) ◽  
pp. 303-319
Author(s):  
Jatin Kumar Pradhan ◽  
Arun Ghosh ◽  
Chandrashekhar Narayan Bhende
Keyword(s):  
State Feedback ◽  
Control Design ◽  
Linear Quadratic Regulator ◽  
Linear Matrix ◽  
Feedback Gain ◽  
Matrix Inequality ◽  
Proportional Integral Derivative ◽  
Linear Quadratic ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral

This article is concerned with designing a 2-degree-of-freedom multi-input multi-output proportional–integral–derivative controller to ensure linear quadratic regulator performance and H∞ performance using a non-iterative linear matrix inequality–based method. To design the controller, first, a relation between the state feedback gain and proportional–integral–derivative gain is obtained. As the gains of proportional–integral–derivative controller cannot, in general, be found out from this relation for arbitrary stabilizing state feedback gain, a suitable form of the matrices involved in linear matrix inequality–based state feedback design is then chosen to obtain the proportional–integral–derivative gains directly. The special structure of the above matrices allows one to design proportional–integral–derivative controller in non-iterative manner. As a result, multi-objective performances, such as linear quadratic regulator and H∞, can be achieved simultaneously without increasing the computational burden much. To enhance the reference-input-to-output characteristics, a feedforward gain is also introduced and designed to minimize certain closed-loop H∞ performance. The proposed control design method is applied for multi-input multi-output proportional–integral compensation of a laboratory-based quadruple-tank process. The performance of the compensation is studied through extensive simulations and experiments.

scholarly journals Takagi-Sugeno Fuzzy Modeling and PSO-Based Robust LQR Anti-Swing Control for Overhead Crane

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Xuejuan Shao ◽  
Jinggang Zhang ◽  
Xueliang Zhang
Keyword(s):  
Linear Quadratic Regulator ◽  
Pso Algorithm ◽  
Fuzzy Modeling ◽  
Linear Matrix ◽  
Feedback Gain ◽  
Overhead Crane ◽  
Linear Quadratic ◽  
Highly Nonlinear ◽  
The Stability ◽  
Takagi Sugeno

The dynamic model of overhead crane is highly nonlinear and uncertain. In this paper, Takagi-Sugeno (T-S) fuzzy modeling and PSO-based robust linear quadratic regulator (LQR) are proposed for anti-swing and positioning control of the system. First, on the basis of sector nonlinear theory, the two T-S fuzzy models are established by using the virtual control variables and approximate method. Then, considering the uncertainty of the model, robust LQR controllers with parallel distributed compensation (PDC) structure are designed. The feedback gain matrices are obtained by transforming the stability and robustness of the system into linear matrix inequalities (LMIs) problem. In addition, particle swarm optimization (PSO) algorithm is used to overcome the blindness of LQR weight matrix selection in the design process. The proposed control methods are simple, feasible, and robust. Finally, the numeral simulations are carried out to prove the effectiveness of the methods.

THE EVALUATION OF CONTROLLER TRACKING PERFORMANCE BASED ON TAYLOR’S SERIES EXPANSION MODEL

2015 ◽  
Vol 74 (9) ◽  
Author(s):  
Maziyah Mat Noh ◽  
M. R. Arshad ◽  
Rosmiwati Mohd-Mokhtar
Keyword(s):  
Series Expansion ◽  
Sliding Mode ◽  
Equations Of Motion ◽  
Linear Quadratic Regulator ◽  
Tracking Performance ◽  
Convergence Time ◽  
Linear Quadratic ◽  
Glide Path ◽  
Expansion Model ◽  
Taylor’S Series

This paper presents the controller tracking performance of Underwater Glider. The controllers are designed based on linearised model. The equations of motion are restricted to longitudinal plane. The controllers are designed and tested for the glide path moving from 45° to 30° downward and upward. The model is linearised using Taylor’s series expansion linearisation method. The controller developed here is Sliding Mode Control (SMC), and Linear Quadratic Regulator (LQR). The performance of both controllers are compared and analysed. The simulations show SMC produce better performance with about over 30% faster than LQR based its convergence time.

scholarly journals LQR-Based Power Train Control Method Design for Fuel Cell Hybrid Vehicle

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Yun Haitao ◽  
Zhao Yulan ◽  
Liu Zunnian ◽  
Hao Kui
Keyword(s):  
Fuel Cell ◽  
Cell Hybrid ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Hybrid Vehicle ◽  
Feedback Gain ◽  
Linear Quadratic ◽  
Power Train ◽  
Fuel Cell Hybrid Vehicle ◽  
Fuel Cell Hybrid

Based on the mathematical model of fuel cell hybrid vehicle (FCHV) proposed in our previous study, a multistate feedback control strategy of the hybrid power train is designed based on the linear quadratic regulator (LQR) algorithm. A Kalman Filter (KF) observer is introduced to estimate state of charge (SOC) of the battery firstly, and then a linear quadratic regulator is constructed to compute the state feedback gain matrix of the closed-loop control system. At last, simulation and actual test are utilized to demonstrate this new approach.

Dynamic Modeling and Vibration Control of a Space Flexible Manipulator Using Piezoelectric Actuators and Sensors

2011 ◽  
Vol 345 ◽  
pp. 46-52 ◽  
Author(s):  
Jun Qiang Lou ◽  
Yan Ding Wei
Keyword(s):  
Vibration Control ◽  
Dynamic Modeling ◽  
Vibration Suppression ◽  
Equations Of Motion ◽  
Linear Quadratic Regulator ◽  
Flexible Manipulator ◽  
Coupled Vibration ◽  
Linear Quadratic ◽  
Space Manipulator ◽  
Tip Mass

This paper concerns the dynamic modeling and vibration control of a space two-link flexible manipulator. Two types of PZT actuators, PZT shear actuator and torsional actuator, are used to suppress the bending-torsional-coupled vibration of the space manipulator. Using extended Hamilton’s principle and the finite element method, equations of motion of the space flexible manipulator with PZT actuators and tip mass are obtained. Based on modal analyze theory, the state space model of the system is then used to design the control system. A linear quadratic regulator (LQR) controller is designed to achieve vibration suppression of the space manipulator system. From the numerical results, we can get that the proposed controller has a suitable and efficient performance suppressing the bending-torsional-coupled vibration of the space two-link flexible manipulator.

scholarly journals Elevation, pitch and travel axis stabilization of 3DOF helicopter with hybrid control system by GA-LQR based PID controller

2020 ◽  
Vol 10 (2) ◽  
pp. 1868 ◽  
Author(s):  
Ibrahim K. Mohammed ◽  
Abdulla I. Abdulla
Keyword(s):  
Pid Controller ◽  
Hybrid Control ◽  
Research Work ◽  
Linear Quadratic Regulator ◽  
Optimization Method ◽  
Feedback Gain ◽  
Algorithm Optimization ◽  
Linear Quadratic ◽  
Control Approach ◽  
Lqr Controller

This research work presents an efficient hybrid control methodology through combining the traditional proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) optimal controlher. The proposed hybrid control approach is adopted to design three degree of freedom (3DOF) stabilizing system for helicopter. The gain parameters of the classic PID controller are determined using the elements of the LQR feedback gain matrix. The dynamic behaviour of the LQR based PID controller, is modeled and the formulated in state space form to enable utlizing state feedback controller technique. The performance of the proposed LQR based LQR controller is improved by using Genetic Algorithm optimization method which are adopted to obtain optimum values for LQR controller gain parameters. The LQR-PID hybrid controller is simulated using Matlab environment and its performance is evaluated based on rise time, settling time, overshoot and steady state error parameters to validate the proposed 3DOF helicopter balancing system. Based on GA tuning approach, the simulation results suggest that the hybrid LQR-PID controller can be effectively adopted to stabilize the 3DOF helicopter system.

Robust eigenstructure assignment using the genetic algorithm and constrained state feedback

1997 ◽  
Vol 211 (1) ◽  
pp. 53-61 ◽  
Author(s):  
T Clarke ◽  
R Davies
Keyword(s):  
Genetic Algorithm ◽  
State Feedback ◽  
Linear Quadratic Regulator ◽  
Eigenstructure Assignment ◽  
Dynamic Feedback ◽  
Linear Quadratic ◽  
Stability Margins ◽  
Lateral Dynamics ◽  
Genetic Algorithm Approach ◽  
Handling Quality

This paper describes a robust eigenstructure assignment methodology for a constrained state feedback problem. The method, which is based upon the linear quadratic regulator and involves the minimization, via the genetic algorithm, of a multiobjective cost function, is applied to L1011 Tristar aircraft lateral dynamics. The design example generates a fixed-gain state feedback solution which shows independent phase margins of 51· in each channel, while exhibiting an eigenstructure close to that desired, lying well within specified handling quality requirements. If two states are made unavailable for feedback, the robustness properties are seriously eroded. When a dynamic feedback compensator is then used, there is a substantial recovery of the robustness. It is concluded that the genetic algorithm approach described here is easy to use and generates good multivariable stability margins.

Use of Rotor State Feedback to Improve Closed-Loop Stability and Handling Qualities

2012 ◽  
Vol 57 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Joseph F. Horn ◽  
Wei Guo ◽  
Gurbuz Taha Ozdemir
Keyword(s):  
Disturbance Rejection ◽  
State Feedback ◽  
Closed Loop ◽  
Linear Quadratic Regulator ◽  
Linear Analysis ◽  
Dynamic Inversion ◽  
Control Law ◽  
Linear Quadratic ◽  
Handling Qualities ◽  
Model Following

A rotorcraft control law that uses rotor state feedback (RSF) is presented and demonstrated in simulation. The baseline control law uses a model following/dynamic inversion approach to control the roll, pitch, and yaw axes. The RSF control law was designed to integrate seamlessly with the baseline control law and can be readily engaged or disengaged. The RSF control gains were designed using linear quadratic regulator synthesis. Linear analyses showed that RSF could allow for the feedback gains on rates and attitude to be increased to values that would result in closed-loop instability without the use of RSF. The increased gains can be used to increase bandwidth and improve disturbance rejection. The controller was tested on a nonlinear model in both non–real-time and piloted simulations, and results confirmed the linear analysis. The RSF control law design has potential to improve handling qualities by allowing higher bandwidth and better disturbance rejection with reduced risk of closed-loop instability.

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