scholarly journals The Exact Linearization and LQR Control of Semiactive Connected Hydropneumatic Suspension System

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Xuyang Cao ◽  
Linlin Cao ◽  
Dianlong Wang
Keyword(s):  
Differential Geometry ◽  
Nonlinear System ◽  
Vibration Amplitude ◽  
Linear Quadratic Regulator ◽  
Exact Linearization ◽  
Linear Quadratic ◽  
Small Vibration ◽  
Lqr Control ◽  
Impact Acceleration ◽  
The Impact

Based on differential geometry theory, the nonlinear system of connected hydropneumatic suspension was transformed to a linear one. What is more, it realized the decoupling and inverter between the control variables and system outputs. With LQR (Linear Quadratic Regulator) control theory, a semiactive system has been developed for connected hydropneumatic suspension in this paper. By AMESim/Simulink cosimulation, the results show that the semiactive connected hydropneumatic suspension decreases the vibration of upper vehicle quickly and reduces the impact acceleration strongly both in displacement and inroll angle. Moreover, the semiactive suspension could increase the suspension dynamic deflection, which would make the system reach balance quickly and keep small vibration amplitude under the effect of disturbance.

Lateral Stability Analysis for Car-Trailer Combinations

2016 ◽  
Author(s):  
Eungkil Lee ◽  
Tao Sun ◽  
Yuping He
Keyword(s):  
Stability Analysis ◽  
Linear Stability ◽  
Linear Stability Analysis ◽  
Parametric Study ◽  
Degrees Of Freedom ◽  
Linear Quadratic Regulator ◽  
Lateral Stability ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Ct System

This paper presents a parametric study of linear lateral stability of a car-trailer (CT) combination in order to examine the fidelity, complexity, and applicability for control algorithm development for CT systems. Using MATLAB software, a linear yaw-roll model with 5 degrees of freedom (DOF) is developed to represent the CT combination. In the case of linear stability analysis, a parametric study was carried out using eigenvalue analysis based on a linear yaw-roll CT model with varying parameters. Built upon the linear stability analysis, an active trailer differential braking (ATDB) controller was designed for the CT system using the linear quadratic regulator (LQR) technique. The simulation study presented in this paper shows the effectiveness of the proposed LQR control design and the influence of different trailer parameters.

scholarly journals Signature PSO: A novel inertia weight adjustment using fuzzy signature for LQR tuning

2021 ◽  
Vol 10 (1) ◽  
pp. 308-318
Author(s):  
Achmad Komarudin ◽  
Novendra Setyawan ◽  
Leonardo Kamajaya ◽  
Mas Nurul Achmadiah ◽  
Zulfatman Zulfatman
Keyword(s):  
Linear Quadratic Regulator ◽  
Absolute Error ◽  
Control Parameters ◽  
Optimum Control ◽  
Exploration And Exploitation ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Inertia Weight ◽  
Adjustment Strategy ◽  
Complete Optimization

Particle swarm optimization (PSO) is an optimization algorithm that is simple and reliable to complete optimization. The balance between exploration and exploitation of PSO searching characteristics is maintained by inertia weight. Since this parameter has been introduced, there have been several different strategies to determine the inertia weight during a train of the run. This paper describes the method of adjusting the inertia weights using fuzzy signatures called signature PSO. Some parameters were used as a fuzzy signature variable to represent the particle situation in a run. The implementation to solve the tuning problem of linear quadratic regulator (LQR) control parameters is also presented in this paper. Another weight adjustment strategy is also used as a comparison in performance evaluation using an integral time absolute error (ITAE). Experimental results show that signature PSO was able to give a good approximation to the optimum control parameters of LQR in this case.

scholarly journals DYNAMICS BASED CONTROL OF A SKID STEERING MOBILE ROBOT

2016 ◽  
Vol 9 (2) ◽  
pp. 70 ◽  
Author(s):  
Osama Elshazly ◽  
Hossam Abbas ◽  
Zakarya Zyada
Keyword(s):  
Mobile Robot ◽  
Inverse Dynamics ◽  
Linear Quadratic Regulator ◽  
Nonlinear Controller ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Lqr Control ◽  
Control Schemes ◽  
Skid Steering ◽  
Drive Model

In this paper, development of a reduced order, augmented dynamics-drive model that combines both the dynamics and drive subsystems of the skid steering mobile robot (SSMR) is presented. A Linear Quadratic Regulator (LQR) control algorithm with feed-forward compensation of the disturbances part included in the reduced order augmented dynamics-drive model is designed. The proposed controller has many advantages such as its simplicity in terms of design and implementation in comparison with complex nonlinear control schemes that are usually designed for this system. Moreover, the good performance is also provided by the controller for the SSMR comparable with a nonlinear controller based on the inverse dynamics which depends on the availability of an accurate model describing the system. Simulation results illustrate the effectiveness and enhancement provided by the proposed controller.

LQR for State-Bounded Structural Control

1996 ◽  
Vol 118 (1) ◽  
pp. 113-119 ◽  
Author(s):  
C.-H. Chuang ◽  
D.-N. Wu ◽  
Q. Wang
Keyword(s):  
Structural Control ◽  
Vibration Amplitude ◽  
Gain Control ◽  
Linear Quadratic Regulator ◽  
Matching Condition ◽  
High Gain ◽  
Time Instant ◽  
Linear Quadratic ◽  
Earthquake Excitation ◽  
High Gain Control

In order to prevent structural damages, it is more important to bound the vibration amplitude than to reduce the vibration energy. However, in the performance index for linear quadratic regulator (LQR), the instantaneous amplitude of vibration is not minimized. An ordinary LQR may have an unacceptable amplitude at some time instant but still have a good performance. In this paper, we have developed an LQR with adjustable gains to guarantee bounds on the vibration amplitude. For scalar systems, the weighting for control is switched between two values which give a low-gain control when the amplitude is inside the bound and a high-gain control when the amplitude is going to violate the given bound. For multivariable systems, by assuming a matching condition, a similar controller structure has been obtained. This controller is favored for application since the main structure of a common LQR is not changed; the additional high-gain control is required only if the vibration amplitude fails to stay inside the bound. We have applied this controller to a five-story building with active tendon controllers. The results show that the largest oscillation at the first story stays within a given bound when the building is subject to earthquake excitation.

FULL-AND REDUCED- ORDER COMPENSATOR FOR INNOSAT ATTITUDE CONTROL

2015 ◽  
Vol 76 (12) ◽  
Author(s):  
Fadzilah Hashim ◽  
Mohd Yusoff Mashor ◽  
Siti Maryam Sharun
Keyword(s):  
State Space ◽  
Attitude Control ◽  
Space Form ◽  
Transfer Functions ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Lqr Control ◽  
Best Value ◽  
Control Scheme

This paper presents a study on the estimator based on Linear Quadratic Regulator (LQR) control scheme for Innovative Satellite (InnoSAT). By using LQR control scheme, the controller and the estimator has been derived for state space form in all three axes to stabilize the system’s performance. This study starts by converting the transfer functions of attitude control into state space form.  Then, the step continues by finding the best value of weighting matrices of LQR in order to obtain the best value of controller gain, K. After that, the best value of L is obtained for the estimator gain. The value of K and L is combined in forming full order compensator and in the same time the reduced order compensator is also formed. Lastly, the performance of full order compensator is compared to reduced order compensator. From the simulation, results indicate that both types of estimators have presented good stability and tracking performance. However, reduced order estimator has simpler equation and faster convergence to zero than the full order estimator. This property is very important in developing a satellite attitude control for real-time implementation.

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.

Energetically-Optimal Discrete and Continuous Stabilization of the Rimless Wheel With Torso

2019 ◽  
Author(s):  
Wankun Sirichotiyakul ◽  
Aykut C. Satici ◽  
Eric S. Sanchez ◽  
Pranav A. Bhounsule
Keyword(s):  
Closed Loop ◽  
Estimation Method ◽  
Linear Quadratic Regulator ◽  
Region Of Attraction ◽  
Closed Loop System ◽  
Linear Quadratic ◽  
Walking Gait ◽  
Rimless Wheel ◽  
The Impact ◽  
Discrete Controller

Abstract In this work, we discuss the modeling, control, and implementation of a rimless wheel with torso. We derive and compare two control methodologies: a discrete-time controller (DT) that updates the controls once-per-step and a continuous-time controller (CT) that updates gains continuously. For the discrete controller, we use least-squares estimation method to approximate the Poincaré map on a certain section and use discrete-linear-quadratic-regulator (DQLR) to stabilize a (closed-form) linearization of this map. For the continuous controller, we introduce moving Poincaré sections and stabilize the transverse dynamics along these moving sections. For both controllers, we estimate the region of attraction of the closed-loop system using sum-of-squares methods. Analysis of the impact map yields a refinement of the controller that stabilizes a steady-state walking gait with minimal energy loss. We present both simulation and experimental results that support the validity of the proposed approaches. We find that the CT controller has a larger region of attraction and smoother stabilization as compared with the DT controller.

scholarly journals Synthesis of A Digital PID/LQR Control System for Duty-Cycle Modulation Buck Converters

2020 ◽  
pp. 185-189
Author(s):  
Paul Owoundi Etouke ◽  
Jean Mbihi ◽  
Leandre Nneme Nneme
Keyword(s):  
Control System ◽  
Transfer Function ◽  
Duty Cycle ◽  
Linear Quadratic Regulator ◽  
Buck Converter ◽  
Step Response ◽  
Buck Converters ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Digital Pid

<p>This research paper presents a synthesis approach of a digital optimal PID/LQR control system for DCM (duty-cycle cycle modulation) Buck converters. The step response of the DCM Buck converter is obtained under Multisim virtual simulation framework. The related data file is saved as *.SCP format, and imported into EditPad Lite7 editor, then exported as Matlab file to be processed. The transfer function of the DCM Buck converter is computed from the imported step response data. Then, using the zoh (zero order holder) discretization method with 100 ms resampling period, the z-transfer function of the DCM Buck converter is computed, and that of the analog optimal PID/LQR(linear quadratic regulator) controller is calculated using Tustin’s discretization technique. Furthermore, the step response of the related closed loop digital PID control system is simulated and compared to that of the original analog PID/LQR control system. The simulation results obtained are presented in order to show the high precision as well as the reliability of Matlab-based synthesis of digital optimal PID/LQR control systems for DCM Buck converters.</p>

scholarly journals Evaluation of Three Common Algorithms for Structure Active Control

2017 ◽  
Vol 7 (3) ◽  
pp. 1638-1646
Author(s):  
M. Sareban
Keyword(s):  
Fuzzy Control ◽  
Active Control ◽  
Control Method ◽  
Variable Mass ◽  
Structural Response ◽  
Linear Quadratic Regulator ◽  
Relative Displacement ◽  
Control Methods ◽  
Linear Quadratic ◽  
The Impact

Recently active structure controllers were considered to deal with the impact of earthquake forces and the result of the investigations provided multiple algorithms to calculate force control and many different ways to apply these forces on the structure. In this study, the efficiency and effectiveness of three methods (linear quadratic regulator, fuzzy logic and pole assigning) are investigated. In addition, three buildings with different height classes with an active tuned mass damper (ATMD) on the top floor are considered to compare the active control methods. Examples with known mass and stiffness and with variable mass are considered. The results show that all three control methods used for the ATMD device reduce the structural response. The fuzzy control method, caused a sharp decline in relative displacement of building floors up to 80%. But in LQR and pole allocation procedures the applied force is limited. The best performance of fuzzy control is for high-rise buildings. The three different methods of control are stable in different masses and even under a random change of floor masses, their effectiveness can be trusted.

scholarly journals Analisis Respon Sistem Kendali LQR (Linear Quadratic Regulator) Pada Simulasi Gimbal Kamera Dua Sumbu

2019 ◽  
Vol 2 (1) ◽  
pp. 49-55
Author(s):  
Qalisha Putri Syahna ◽  
Elvan Yuniarti ◽  
Edi Kurniawan
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pitch Angle ◽  
Linear Quadratic Regulator ◽  
Q Value ◽  
Linear Quadratic ◽  
Tuning Method ◽  
Lqr Control ◽  
System Output ◽  
Response Method

Research has been conducted to analyzed the responses of the two axis camera gimbal control system for pitch and roll direction using the Linear Quadratic Regulator (LQR) control system. It focused on the effect from the value of gain Q in calculation of the LQR. The system output was plotted into a step signal so it will be analyzed with transient response method and plotted into sinusoidal signals to find the amplitude value along with the amplitude time. For comparison, the PID control system with the auto-tuning method was also used in this study. It has been done in order to find out whether the LQR control system is more appropriate to use in the two axis camera gimbal system or not. The result from the analysis of the variation of the Q value given at both angles is that the system runs stable when the value of P= 4 for roll angle and P= 6 for pitch angle. For the effect from value of gain Q on the whole system is it will make the output significally changed when the P=1-10. While the results of the comparison can prove that the LQR control system has a better system responses.

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