An Error Space Controller for a Resonating Fiber Scanner: Simulation and Implementation

2006 ◽  
Vol 128 (4) ◽  
pp. 899-913 ◽  
Author(s):  
Quinn Y. J. Smithwick ◽  
Juris Vagners ◽  
Per G. Reinhall ◽  
Eric J. Seibel
Keyword(s):  
Tracking Error ◽  
Linear Quadratic Regulator ◽  
Open Loop ◽  
Linear Quadratic ◽  
Fiber Nonlinearities ◽  
Error Space ◽  
Nonlinear Dynamics Model ◽  
Error Dynamics ◽  
Scan Pattern ◽  
Spiral Scan

A robust error-space controller for an amplitude modulated resonating fiber scanner is developed and implemented. Using a nonlinear dynamics model, the system’s open loop temporal response for a spiral scan pattern is simulated and compared to experiments to understand scan distortions, such as, toroid, swirl, and beating. A feedback linearized linear quadratic regulator based on error dynamics drives the tracking error to zero. Controller simulations determine robustness limits, and effects of fiber nonlinearities and actuator time delay. Using real-time hardware, the controller asymptotically tracks and is capable of removing the scan distortions. Image acquisition with the controlled scanner produces nearly pixel accurate images.

Mechatronic suspension design for full rail vehicle system

2016 ◽  
Vol 231 (4) ◽  
pp. 571-590 ◽  
Author(s):  
Mortadha Graa ◽  
Mohamed Nejlaoui ◽  
Ajmi Houidi ◽  
Zouhaier Affi ◽  
Lotfi Romdhane
Keyword(s):  
Tracking Error ◽  
Linear Quadratic Regulator ◽  
Experimental Result ◽  
Railway Vehicle ◽  
Linear Quadratic ◽  
Rail Vehicle ◽  
Vehicle System ◽  
Frequency Domains ◽  
Rail Irregularities ◽  
Vehicle Motion

In this paper, an analytical mechatronic dynamic design model of a full rail vehicle system is developed. Based on the rail vehicle motion, its degree of freedom can be reduced to only 38. This reduction is necessary for the model simplicity. The developed model is validated with experimental result and compared with other one from literature. The real characteristics of the actuators are discussed, and its controller is designed. A mechatronic model that expresses the controlled tracking error as function of the vehicle dynamics and the actuator characteristics is developed. This model is used by the linear quadratic regulator approach to identify the mechatronic rail vehicle proportional–integral–derivative controller’s gains. The mechatronic rail vehicle comfort is evaluated in terms of the passenger displacement, acceleration and frequency as a response of a rail irregularities caused by a lateral and two vertical track irregularities. The simulations of vibration analysis are obtained in time and frequency domains and compared with railway vehicle status. The robustness of the designed mechatronic rail vehicle is verified by simulations, carried out for the cases of car body mass variations. The results show the effectiveness of the proposed mechatronic rail vehicle design which improves significantly the transportation of passengers.

Optimal attitude trajectory planning method for CMG actuated spacecraft

2017 ◽  
Vol 232 (1) ◽  
pp. 131-142 ◽  
Author(s):  
Lijun Zhang ◽  
Chunmei Yu ◽  
Shifeng Zhang ◽  
Hong Cai
Keyword(s):  
Trajectory Planning ◽  
Closed Loop ◽  
Pseudospectral Method ◽  
Linear Quadratic Regulator ◽  
Fixed Time ◽  
Open Loop ◽  
Planning Method ◽  
Global Perspective ◽  
Linear Quadratic ◽  
Loop Control

This paper presents an optimal attitude trajectory planning method for the spacecraft equipped with control moment gyros as the actuators. Both the fixed-time energy-optimal and synthesis performance optimal cases are taken into account. The corresponding nonsingular attitude maneuvering trajectories (i.e. open-loop control trajectories) with the consideration of a series of constraints are generated via Radau pseudospectral method. Compared with the traditional steering laws, the optimal steering law designed by this method can explicitly avoid the singularity from the global perspective. A linear quadratic regulator closed-loop controller is designed to guarantee the trajectory tracking performance in the presence of initial errors, inertia uncertainties and external disturbances. Simulation results verify the validity and feasibility of the proposed open-loop and closed-loop control methods.

Minimizing Human Tracking Error for Robotic Rehabilitation Device

2015 ◽  
Vol 9 (4) ◽  
Author(s):  
Andrew J. Homich ◽  
Megan A. Doerzbacher ◽  
Eric L. Tschantz ◽  
Stephen J. Piazza ◽  
Everett C. Hills ◽  
...  
Keyword(s):  
State Space ◽  
Tracking Error ◽  
Linear Quadratic Regulator ◽  
Gait Training ◽  
Average Error ◽  
Linear Quadratic ◽  
Optimal State ◽  
Filter Performance ◽  
Complementary Filter ◽  
Angular Velocities

This paper explores the design of a novel robotic device for gait training and rehabilitation, a method to estimate a human's orientation within the rehabilitation device, as well as an optimal state space controller to actuate the rehabilitation device. The robotic parallel bars (RPBs) were designed to address the shortcomings of currently available assistive devices. The RPB device moves in response to a human occupant to maintain a constant distance and orientation to the human. To minimize the error in tracking the human, a complementary filter was optimized to estimate the human's orientation within the device using a magnetometer and gyroscope. Experimental measurements of complementary filter performance on a test platform show that the filter estimates orientation with an average error of 0.62 deg over a range of angular velocities from 22.5 deg/s to 180 deg/s. The RPB device response was simulated, and an optimal state space controller was implemented using a linear quadratic regulator (LQR). The controller has an average position error of 14.1 cm and an average orientation error of 14.3 deg when tracking a human, while the simulation predicted an average error of 10.5 cm and 5.6 deg. The achieved level of accuracy in following a human user is sufficiently sensitive for the RPB device to conduct more advanced, realistic gait training and rehabilitation techniques for mobility impaired patients able to safely support their body weight with their legs and arms.

Hovering stability of a model helicopter

2016 ◽  
Vol 88 (6) ◽  
pp. 810-817 ◽  
Author(s):  
Ilker Murat Koc ◽  
Semuel Franko ◽  
Can Ozsoy
Keyword(s):  
Initial Conditions ◽  
Linear Quadratic Regulator ◽  
Open Loop ◽  
Small Scale ◽  
Linear Quadratic ◽  
Parameter Uncertainties ◽  
Control Effort ◽  
Content Type ◽  
Modeling Uncertainties ◽  
Angular Displacements

Purpose The purpose of this paper is to investigate the stability of a small scale six-degree-of-freedom nonlinear helicopter model at translator velocities and angular displacements while it is transiting to hover with different initial conditions. Design/methodology/approach In this study, model predictive controller and linear quadratic regulator are designed and compared within each other for the stabilization of the open loop unstable nonlinear helicopter model. Findings This study shows that the helicopter is able to reach to the desired target with good robustness, low control effort and small steady-state error under disturbances such as parameter uncertainties, mistuned controller. Originality/value The purpose of using model predictive control for three axes of the autopilot is to decrease the control effort and to make the close-loop system insensitive against modeling uncertainties.

Steering control of six-wheeled vehicles using linear quadratic regulator techniques

2007 ◽  
Vol 221 (10) ◽  
pp. 1231-1240 ◽  
Author(s):  
B-C Chen ◽  
C-C Yu ◽  
W-F Hsu
Keyword(s):  
Linear Quadratic Regulator ◽  
Rear Wheel ◽  
Front Wheel ◽  
Open Loop ◽  
Slip Angle ◽  
Steering Control ◽  
Linear Quadratic ◽  
Integral Control ◽  
Side Slip Angle ◽  
Wheeled Vehicles

The middle- and rear-wheel steering angles of a six-wheeled vehicle need to be coordinated with the front-wheel steering angle to obtain the maximum manoeuvrability. A steering control strategy using the linear quadratic regulator technique with integral control is proposed in this paper such that both zero side-slip angle and target yaw rate following can be achieved simultaneously. An estimator to be used with the control law is also designed to provide the estimate of side-slip angle. AutoSim is used to establish a complex vehicle model with tyre dynamics in MATLAB/Simulink. Both open-loop and closed-loop manoeuvres are performed to evaluate the control performance of the proposed strategy.

Modelling, System Identification and Position Control Based on LQR Formulation for an Electro-Hydraulic Servo System

2019 ◽  
Author(s):  
Carlos Borrás Pinilla ◽  
José Luis Sarmiento ◽  
Rubén Darío Guiza
Keyword(s):  
Control Strategies ◽  
Tracking Error ◽  
Servo System ◽  
Open Loop ◽  
Position Tracking ◽  
Linear Quadratic ◽  
Open Loop System ◽  
Hydraulic Servo ◽  
Hydraulic Servo System ◽  
Modelling System

Abstract This study presents the mathematical modelling, system identification using grey-box model estimation and position-tracking control for an electro-hydraulic servo system (EHSS) using four control strategies based on LQR formulation: Linear quadratic regulator (LQR) approach for servo systems, linear quadratic integral (LQI), linear quadratic tracking (LQT) and a variation of LQT named here LQTβ. First, the nonlinear model of the electro-hydraulic servo system was obtained using differential equations based on hydraulic theory and physical laws. The model was then linearized and its parameters were estimated using grey-box method when the open-loop system was excited with a chirp signal from 0 to 30 [Hz]. The estimated model was verified with experimental data of the open-loop system response for square wave and continuous step inputs of different amplitudes and frequencies. For the position-tracking four control strategies based on LQR formulation were proposed. The main difference among them is the conception of the cost function that is minimized: the LQR includes all the system’s states and the control signal, the LQI includes all system’s states, the tracking error and the control signal, the LQT includes only the tracking error and the LQTβ the tracking error and its derivative. The four control strategies were simulated in MATLAB Simulink and initially tuned using Bryson’s rule, then were implemented in the real system and finely tuned by trial and error until the best performance is achieved. They all were tested using step, square wave and sine wave inputs, and were analyzed in terms of settling time, rising time, peak time, overshoot margin, steady-state error, energy consumption and repeatability against a conventional PID controller. The experimental results showed better tracking, better repeatability and less energy consumption using the LQR based techniques than using the PID control, specifically the LQR and the LQTβ showed the fastest response and smallest steady-state error among the LQR based strategies. This study was carried out with the electro-hydraulic servo system (EHSS) of the seismic shaker table of the Dynamics and Structural Control Lab at Universidad Industrial de Santander. The seismic shaker table is composed of a Parker double rod dynamic hydraulic cylinder commanded by an MTS 252.24G-04 servo valve and powered by an MTS 505.11 hydraulic power unit. Cylinder’s position was measured using an integrated Trans-Teck LVDT. The control system was build and implemented in MATLAB Simulink using Quanser Q8-USB card.

scholarly journals Design and Simulation of a Steam Turbine Generator using Observer Based and LQR Controllers

2020 ◽  
Author(s):  
mustefa jibril ◽  
Messay Tadese ◽  
Eliyas Alemayehu
Keyword(s):  
Steam Turbine ◽  
Performance Improvement ◽  
Linear Quadratic Regulator ◽  
Electrical Energy ◽  
Open Loop ◽  
Loop System ◽  
Linear Quadratic ◽  
Turbine Generator ◽  
Open Loop System ◽  
Lqr Controller

A steam turbine generator is an electromechanical system which converts heat energy to electrical energy. In this paper, the modelling, design and analysis of a simple steam turbine generator have done using Matlab/Simulink Toolbox. The open loop system have been analyzed to have an efficiency of 76.92 %. Observer based & linear quadratic regulator (LQR) controllers have been designed to improve the generating voltage. A comparison of this two proposed controllers have been done for increasing the performance improvement to generate a 220 DC volt. The simulation result shows that the steam turbine generator with observer based controller has a small percentage overshoot with minimum settling time than the steam turbine generator with LQR controller and the open loop system. Finally, the steam turbine generator with observer based controller shows better improvement in performance than the steam turbine generator with LQR controller.

Design of a safety operational envelope protection system for the pitch angle of a submarine

2016 ◽  
Vol 231 (2) ◽  
pp. 441-451
Author(s):  
Jong-Yong Park ◽  
Nakwan Kim
Keyword(s):  
Pitch Angle ◽  
Linear Quadratic Regulator ◽  
Protection System ◽  
Linear Quadratic ◽  
On Line ◽  
Envelope Protection ◽  
Error Dynamics ◽  
Operational Envelope ◽  
Limit Detection ◽  
On Line Learning

Submarines have a safety operating envelope, the boundary of which is closely related to structural limits and the safety of crew. An envelope protection system guarantees that the submarine does not exceed the boundary, which reduces the frequency of operational accidents and mission time. In this article, an envelope protection system for the pitch angle is designed for a submarine. The envelope protection system consists of limit detection and limit avoidance. Limit detection is designed using a dynamic trim algorithm, and command limiting is used for the limit avoidance. An artificial neural network is adopted for on-line learning and modeling uncertainty compensation, and a linear quadratic regulator is employed to stabilize the error dynamics. A submarine maneuvering simulation program developed from the experimental data is used to validate the designed envelope protection system. The simulation results show the effectiveness of the envelope protection system.

Genetic algorithm-based multi-objective design of optimal discrete sliding mode approach for trajectory tracking of nonlinear systems

2019 ◽  
Vol 233 (15) ◽  
pp. 5237-5252
Author(s):  
Anouar Benamor ◽  
Wafa Boukadida ◽  
Hassani Messaoud
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Nonlinear Systems ◽  
Optimization Problem ◽  
Sliding Mode ◽  
Tracking Error ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Multi Objective ◽  
Highly Nonlinear

In this paper, a novel multi-objective design of optimal control for robotic manipulators is considered. Generally, robots are known by their highly nonlinearities, unmodeled dynamics, and uncertainties. In order to design an optimal control law, based on the linear quadratic regulator, the robotic system is described as a linear time varying model. The compensation of both disturbances and uncertainties is ensured by the integral sliding mode control. The problem of deciding the optimal configuration of the linear quadratic regulator controller is considered as an optimization problem, which can be solved by the application of genetic algorithm. The main contribution of this paper is to consider a multi-objective optimization problem, which aims to minimize not only the chattering phenomenon but also other control performances including the rise time, the settling-time, the steady-state error and the overshoot. For that, a novel dynamically aggregated objective function is proposed. As a result, a set of nondominated optimal solutions are provided to the designer and then he selects the most preferable alternative. To demonstrate the efficacy and to show complete performance of the new controller, two nonlinear systems are treated in this paper: firstly, a selective compliance assembly robot arm robot is considered. The results show that the manipulator tracing performance is considerably improved with the proposed control scheme. Secondly, the proposed genetic algorithm-based linear quadratic regulator control strategy is applied for pitch and yaw axes control of two-degrees-of-freedom laboratory helicopter workstation, which is a highly nonlinear and unstable system. Experimental results substantiate that the weights optimized using genetic algorithm, result in not only reduced tracking error but also improved tracking response with reduced oscillations.

Robust Compensator Control of a Non-Resonant MEMS Gyroscope With Linear Quadratic Regulator

2010 ◽  
Author(s):  
Wei Cui ◽  
Xiaolin Chen ◽  
Wei Xue
Keyword(s):  
Closed Loop ◽  
Linear Quadratic Regulator ◽  
Open Loop ◽  
High Order ◽  
Behavior Modeling ◽  
Linear Quadratic ◽  
Parameter Uncertainties ◽  
Control Effort ◽  
Wide Range ◽  
Sinusoidal Input

This paper presents a controller design for a four degrees-of-freedom (4-DOF) non-resonant gyroscope via the linear quadratic regulator (LQR) technique. Compared to conventional MEMS gyroscopes, non-resonant gyroscopes are less vulnerable to fabrication perturbations. However, closed-loop performance of non-resonant gyroscopes has not been investigated previously. The control of non-resonant gyroscopes involves consideration of high order systems. LQR, which achieves balances between a fast response and a low control effort, has proven to be effective for high order systems. Our simulation results show that the closed-loop 4-DOF non-resonant gyroscope presented in this paper is able to achieve faster response and higher robustness to parameter uncertainties than the open-loop device. Under the sinusoidal input, compared to an error of 11.06% for the open-loop system, the closed-loop scale factor uniformity error is reduced to 0.014% under ±10% parameter perturbations. The device performance is analyzed by the behavior modeling approach in CoventorWare. The results show that the closed-loop non-resonant gyroscope achieves better performance through the LQR. The method reported here is proven to be effective and can be used in a wide range of applications.

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