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.

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 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 Rotor-Flying Manipulator: Modeling, Analysis, and Control

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Bin Yang ◽  
Yuqing He ◽  
Jianda Han ◽  
Guangjun Liu
Keyword(s):  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Combined System ◽  
Underwater Robots ◽  
Modeling Analysis ◽  
Full State Feedback ◽  
Lqr Controller ◽  
Linearized Model ◽  
And Control

Equipping multijoint manipulators on a mobile robot is a typical redesign scheme to make the latter be able to actively influence the surroundings and has been extensively used for many ground robots, underwater robots, and space robotic systems. However, the rotor-flying robot (RFR) is difficult to be made such redesign. This is mainly because the motion of the manipulator will bring heavy coupling between itself and the RFR system, which makes the system model highly complicated and the controller design difficult. Thus, in this paper, the modeling, analysis, and control of the combined system, called rotor-flying multijoint manipulator (RF-MJM), are conducted. Firstly, the detailed dynamics model is constructed and analyzed. Subsequently, a full-state feedback linear quadratic regulator (LQR) controller is designed through obtaining linearized model near steady state. Finally, simulations are conducted and the results are analyzed to show the basic control performance.

Simulation and Control of a Novel Two-Speed Uninterrupted Mechanical Transmission for Electric Vehicles

2015 ◽  
Author(s):  
Shengnan Fang ◽  
Jian Song ◽  
Yuzhuo Tai ◽  
Fei Li ◽  
Truong Sinh Nguyen
Keyword(s):  
Performance Improvement ◽  
Electric Vehicles ◽  
Control Method ◽  
Dynamic Performance ◽  
Linear Quadratic Regulator ◽  
Mechanical Transmission ◽  
Linear Quadratic ◽  
Robust Controller ◽  
Performance Requirements ◽  
And Control

Development of electric vehicle (EV) technology leads to the growing performance requirements of driving motor. Introducing a two-speed transmission to EV offers the possibility of economic and dynamic performance improvement of the whole powertrain. This paper presents an innovative two-speed Uninterrupted Mechanical Transmission (UMT), allowing the seamless shifting between two gears. Considering the uncertain factors during gearshift, a robust controller is designed based on H∞ control method. An optimal controller based on linear quadratic regulator is adopted for comparison. The results indicate that the UMT adopting robust controller provides an improvement of dynamic performance and shifting comfort for EV.

Modeling and Control Design for Active Trailer Steering of Heavy Vehicles

2017 ◽  
Author(s):  
Jesse Brown ◽  
Yuping He ◽  
Haoxiang Lang
Keyword(s):  
Degrees Of Freedom ◽  
Load Transfer ◽  
Linear Quadratic Regulator ◽  
Heavy Vehicles ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Software Packages ◽  
Lqr Controller ◽  
Control Evaluation ◽  
And Control

This paper presents a linear quadratic regulator (LQR) controller for active trailer steering (ATS) of a tractor-semitrailer. The tractor-semitrailer is modelled as a linear yaw/roll model with 5 Degrees-Of-Freedom (DOF). The linear yaw/roll model is validated with a nonlinear tractor-semitrailer model developed with TruckSim under a simulated single lane-change maneuver. Then, the validated linear yaw/roll model is used to design the LQR controller for ATS. The TruckSim model and the LQR controller are integrated by means of an interface between the software packages of TruckSim and Matlab/Simulink. The LQR controller is assessed using numerical simulation of the TruckSim model with and without the ATS control. Evaluation of the controller is based on the performance measures of the trailer in terms of rearward amplification (RA), peak roll angle, and load transfer ratio (LTR). It is demonstrated that the LQR controller leads to the decrease the peak values of the aforementioned measures by 4.81%, 20.7%, and 33%, respectively.

Aeromechanics and Control of a Shrouded Rotor Micro Air Vehicle in Hover and in Edgewise Flow

2011 ◽  
Vol 56 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Vikram Hrishikeshavan ◽  
Inderjit Chopra
Keyword(s):  
Linear Quadratic Regulator ◽  
Micro Air Vehicle ◽  
Pitching Moment ◽  
Attitude Dynamics ◽  
Linear Quadratic ◽  
Air Vehicle ◽  
Lqr Controller ◽  
Dynamics And Control ◽  
And Control ◽  
Shrouded Rotor

Shrouded rotors are efficient in hover but are quite sensitive to disturbances in external flow. In this paper, the dynamics and control of a shrouded rotor micro air vehicle is studied in hover and when it is subjected to edgewise gust. The importance of incorporating a hingeless rotor in a shrouded rotor configuration was shown and was flight-tested in hover using a proportional-integral attitude feedback controller. In edgewise flow, the shrouded rotor produced up to 300% higher pitching moment than the unshrouded rotor. To counter this pitching moment, the control moments were about 80–100% higher for the shrouded rotor. Time domain attitude dynamics identification of the vehicle, restrained in translation, was conducted with and without the flybar. It was shown to be desirable to incorporate a flybarless rotor for improved maneuverability and hover efficiency. A linear quadratic regulator (LQR) controller was developed based on the extracted attitude dynamics model. Gust disturbance rejection capabilities of the controller were tested with the vehicle in edgewise flow using a spherical gimbal setup. The shrouded vehicle was found to tolerate up to 2 m/s of edgewise gusts, whereas the unshrouded configuration could reject gusts of up to 4.8 m/s.

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 Mathematical Modelling and Control of a Two-Wheeled PUMA-LikeVehicle

2016 ◽  
Vol 6 (2) ◽  
pp. 11 ◽  
Author(s):  
Khaled M Goher
Keyword(s):  
Mathematical Modelling ◽  
Sliding Mode ◽  
Impact Load ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
The Body ◽  
Pole Placement ◽  
General Motors ◽  
Linear Quadratic ◽  
And Control

<p class="1Body">This paper presents mathematical modelling and control of a two-wheeled single-seat vehicle. The design of the vehicle is inspired by the Personal Urban Mobility and Accessibility (PUMA) vehicle developed by General Motors® in collaboration with Segway®. The body of the vehicle is designed to have two main parts. The vehicle is activated using three motors; a linear motor to activate the upper part in a sliding mode and two DC motors activating the vehicle while moving forward/backward and/or manoeuvring. Two stages proportional-integral-derivative (PID) control schemes are designed and implemented on the system models. The state space model of the vehicle is derived from the linearized equations. Controller based on the Linear Quadratic Regulator (LQR) and the pole placement techniques are developed and implemented. Further investigation of the robustness of the developed LQR and the pole placement techniques is emphasized through various experiments using an applied impact load on the vehicle.</p>

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.

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