scholarly journals A Model Predictive Water-Level Difference Control Method for Automatic Control of Irrigation Canals

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 762 ◽  
Author(s):  
Kong ◽  
Lei ◽  
Wang ◽  
Long ◽  
Lu ◽  
...  
Keyword(s):  
Automatic Control ◽  
Water Level ◽  
Control Strategy ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Automatic Regulation ◽  
Irrigation Canal ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Level Difference

In this paper, automatic control of the water level in an irrigation canal by automatic regulation of intermediate gates was studied. Previous scholars have proposed a water level difference control strategy that works to keep relative deviations in all pools the same for a particular situation where the operator does not have full control over the canal inflow, with the centralized linear quadratic regulator (LQR) control method used. While in practice, the deviation tolerance of pools may differ in some canals which limits the applicability of the control strategy. In this work, a weight coefficient was added to the deviation and the algorithm was improved to keep the relative deviations to certain proportions. The model predictive control (MPC) method was then used with this improved control strategy and was compared to the LQR control method using the same control strategy. The results showed that the improved strategy can keep the water level deviations in all pools to certain proportions, as is our objective. Also, under this difference control strategy, the MPC method greatly improved the control performance compared to the LQR control method.

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.

Coordination Control Strategy for Active and Reactive Power of DFIG Based on Exact Feedback Linearization under Grid Fault Condition

2011 ◽  
Vol 48-49 ◽  
pp. 335-344
Author(s):  
Meng Zeng Cheng ◽  
Zhen Lan Dou ◽  
Xu Cai
Keyword(s):  
Nonlinear Control ◽  
Power System ◽  
Control Strategy ◽  
Feedback Linearization ◽  
Transient Stability ◽  
Reactive Power ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Nonlinear Control Method

In this paper, a control strategy for operation of rotor side converter (RSC) of Doubly Fed Induction Generators (DFIG) is developed by injecting reactive power into the grid in order to support the grid voltage during and after grid fault events. The novel nonlinear control method is based on differential geometry theory, and exact feedback linearization is applied for control system design of DFIG. Then the optimal control for the linearized system is obtained through introducing the linear quadratic regulator (LQR) design method. Simulation results on a single machine infinite bus power system show that the proposed nonlinear control method can inject reactive power to fault grid rapidly, reduce the oscillation of active power and improve the transient stability of power system.

Engagement Control of Automated Clutch for Vehicle Launching Considering the Instantaneous Changes of Driver's Intention

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Liang Li ◽  
Zaobei Zhu ◽  
Yong Chen ◽  
Kai He ◽  
Xujian Li ◽  
...  
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Sliding Mode ◽  
Linear Quadratic Regulator ◽  
Vehicle Speed ◽  
Linear Quadratic ◽  
Clutch Engagement ◽  
Automated Manual Transmission ◽  
Driver’S Intention ◽  
Artificial Neural Network Ann

Engagement control of automated clutch is essential during launching process for a vehicle equipped with an automated manual transmission (AMT), and instantaneous changes in the driver's launching intention make it more complicated to control the clutch. This paper studies the identification of the driver's launching intentions, which may change anytime, and proposes a clutch engagement control method for vehicle launching. First, a launching-intention-aware machine (LIAM) based on artificial neural network (ANN) is designed for real-time tracking and identifying the driver's launching intentions. Second, the optimal engagement strategy for different launching intentions is deduced based on the linear quadratic regulator (LQR), which figures out a compromise between friction loss, vehicle shock, engine speed, clutch speed, and desired vehicle speed. Third, the relationship between transmitted torque and clutch position is obtained by experiments, and a sliding-mode controller (SMC) is designed for clutch engagement. Finally, the clutch engagement control strategy is validated by a joint simulation model and an experiment bench. The results show that the control strategy reflects the driver's launching intentions correctly and improves the performance of vehicle launching.

Control of Slender-Beam Payloads During Lift-Up Operations

2018 ◽  
Author(s):  
Shenghai Wang ◽  
Aldo Ferri ◽  
William Singhose ◽  
Yujia Yang
Keyword(s):  
Control Strategy ◽  
Pid Controller ◽  
Linear Quadratic Regulator ◽  
Double Pendulum ◽  
Linear Quadratic ◽  
Pivot Point ◽  
Lqr Control ◽  
Payload Mass ◽  
Two Phases

When lifting up a long slender beam from ground, the payload may slip or move suddenly in unintended and unpredictable ways. This occurs during crane operations when the movements of the overhead trolley and the hoist cable are not properly coordinated. Also, it is difficult to keep the centers of hook and payload mass aligned with the pivot point when the payload is lifted off the ground, resulting in undesired hook and payload swing. The payload’s unintended sliding or swing can potentially cause damage and reduce efficiency. This paper divides the lift-up process into two phases including a constrained phase and a free hanging phase, develops a combination of PID controller and speed envelope to prevent slip in the constrained phase, and presents an observer-based Linear Quadratic Regulator (LQR) control strategy to stabilize the double-pendulum oscillations in the free hanging phase. The robustness of the proposed observer-based LQR was analyzed. Lift-up experiments were carried out to verify the controller development.

scholarly journals ENHANCEMENT OF STABILITY ON AUTONOMOUS WAYPOINT MISSION OF QUADROTOR USING LQR INTEGRATOR CONTROL

2022 ◽  
Vol 23 (1) ◽  
pp. 129-158
Author(s):  
Oktaf Agni Dhewa ◽  
Tri Kuntoro Priyambodo ◽  
Aris Nasuha ◽  
Yasir Mohd Mustofa
Keyword(s):  
Steady State ◽  
Trajectory Tracking ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
System Specification ◽  
Linear Quadratic ◽  
Environmental Disturbances ◽  
Essential Requirement ◽  
Lqr Control ◽  
State Error

The ability of the quadrotor in the waypoint trajectory tracking becomes an essential requirement in the completion of various missions nowadays. However, the magnitude of steady-state errors and multiple overshoots due to environmental disturbances leads to motion instability. These conditions make the quadrotor experience a shift and even change direction from the reference path. As a result, to minimize steady-state error and multiple overshoots, this study employs a Linear Quadratic Regulator control method with the addition of an Integrator. Comparisons between LQR without Integrator and LQR with Integrator were performed. They were implemented on a quadrotor controller to track square and zig-zag waypoint patterns. From experimental results, LQR without Integrator produce of 2 meters steady-state error and -1.04 meters undershoot average with an accuracy of 64.84 % for square pattern, along 3.19 meters steady-state error, and -1.12 meters undershoot average with an accuracy of 46.73 % for a zig-zag way. The LQR method with integrator produce of 1.06 meters steady-state error with accuracy 94.96 % without multiple-overshoot for square pattern, the 1.06 meters steady-state error, and -0.18 meters undershoot average with an accuracy of 86.49 % for the zig-zag way. The results show that the LQR control method with Integrator can minimize and improve steady-state error and multiple overshoots in quadrotor flight. The condition makes the quadrotor able to flying path waypoints with the correct system specification. ABSTRAK: Kemampuan quadrotor dalam pengesanan lintasan waypoint menjadi syarat penting dalam menyelesaikan pelbagai misi pada masa kini. Walau bagaimanapun, besarnya ralat keadaan mantap dan banyak kelebihan kerana gangguan persekitaran menyebabkan ketidakstabilan pergerakan. Keadaan ini menjadikan quadrotor mengalami pergeseran dan bahkan mengubah arah dari jalur rujukan. Oleh itu, kajian ini menggunakan kaedah kawalan Linear Quadratic Regulator dengan penambahan integrator dalam meminimumkan ralat keadaan mantap dan banyak kelebihan. Perbandingan antara LQR tanpa Integrator dan LQR dengan Integrator dilakukan. Mereka dilaksanakan pada pengawal quadrotor untuk mengesan corak titik jalan persegi dan zig-zag. Dari hasil eksperimen, LQR tanpa Integrator menghasilkan ralat keadaan mantap 2 meter dan -1.04 meter rata-rata undur tembak dengan ketepatan 64.84% untuk corak persegi, sepanjang ralat keadaan tetap 3.19 meter, dan -1.12 meter rata-rata undur bawah dengan ketepatan 46.73 % untuk cara zig-zag. Kaedah LQR dengan integrator menghasilkan ralat keadaan mantap 1.06 meter dengan ketepatan 94.96% tanpa tembakan berlebihan untuk corak segi empat sama, ralat keadaan mantap 1.06 meter, dan rata-rata undur tembak -0.18 meter dengan ketepatan 86.49% untuk zig-zag cara. Hasilnya menunjukkan bahawa kaedah kawalan LQR dengan Integrator dapat meminimumkan dan memperbaiki ralat keadaan mantap dan banyak overhoot dalam penerbangan quadrotor. Keadaan tersebut menjadikan quadrotor dapat terbang ke titik jalan dengan spesifikasi sistem yang betul.

Modeling and Control of a Hybrid Wheeled Legged Robot: Disturbance Analysis

2020 ◽  
Author(s):  
Fahad Raza ◽  
Dai Owaki ◽  
Mitsuhiro Hayashibe
Keyword(s):  
Position Control ◽  
Control Method ◽  
System Modeling ◽  
Linear Quadratic Regulator ◽  
Human Robot Interaction ◽  
Physical Disorder ◽  
Legged Robot ◽  
Linear Quadratic ◽  
Control Approach ◽  
Lqr Control

Abstract The most common cause of injuries among older adults is falling. Recently, there have been numerous developments in assistive and exoskeleton systems. However, comparatively little work is being done on systems that may help people to keep an upright position and avoid falling over. In this preliminary work, we investigate the feasibility of the wheel-legged robot as a balance-assist system for the people who cannot maintain balance and walk because of an injury, old age, or neurological or physical disorder. We perform motion stability analyses of the wheel-legged robot under different conditions such as system modeling errors, sensor noise, and external disturbances. The linear quadratic regulator (LQR) control approach is adopted for balancing, steering, and translational position control of the robot. To validate our control framework and visualize results, the robot is modeled and tested in the Gazebo simulator using ROS (Robot Operating System). Subsequently, the simulation results demonstrate the effectiveness of the LQR control method under the translational and rotational pushes of the wheel-legged system for human-robot interaction.

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.

Experimental Investigation of Full-Order Observered and LQR Controlled Building-Like Structure Under Seismic Excitation

2013 ◽  
Vol 307 ◽  
pp. 316-320
Author(s):  
Mustafa Tinkir ◽  
Mete Kalyoncu ◽  
Yusuf Şahin
Keyword(s):  
Control Strategy ◽  
Dynamic Behaviour ◽  
Linear Quadratic Regulator ◽  
Seismic Excitation ◽  
Velocity Control ◽  
Passive Mode ◽  
Linear Quadratic ◽  
Active Mass ◽  
Active Mode ◽  
Two Degree Of Freedom

In this paper, the dynamic behaviour of two degree of freedom building-like structure system against unexpected input such as seismic excitation is considered by experimentally. Proposed system consists of two floors structure with active mass damping (AMD) and shaker. Passive and active mode deflection responses of the floors are investigated and also a cart is used to suppress vibrations, which moves linear direction and is mounted on the second floor. PV (proportional and velocity) control of the cart is realized in passive mode. Moreover LQR (Linear Quadratic Regulator) control is designed to control the cart in active mode while system under excitation. For this aim a full-order observer is designed and implemented to control strategy. Displacements of cart, deflections and accelerations results of the floors are presented separately for passive and active mode responses of the system in the form of graphics.

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