scholarly journals A Congestion Detection Based Traffic Control for Signalized Intersection

2017 ◽  
Author(s):  
István Varga
Keyword(s):  
Traffic Control ◽  
Error Term ◽  
Control Method ◽  
Road Traffic ◽  
Fundamental Problem ◽  
Linear Quadratic Regulator ◽  
Detection Algorithm ◽  
Linear Quadratic ◽  
Congestion Detection ◽  
Detection Filter

The paper investigates a traffic-responsive control method applicable at isolated signalized intersections. The proposed strategy involves three basic parts: a traffic model, a reconfigurable regulator, and a congestion detection filter. Road traffic dynamics is modeled by the well-known store-and-forward approach. The controller is based on the efficient Linear Quadratic Regulator algorithm. The filter is designed by using the modified version (for discrete time case) of the Fundamental Problem of Residual Generation. The main achievement of the system is the ability to deal with a time-varying model parameter, namely the saturation flow rate of the road links. To this end, an error term is estimated continuously by appropriate fault detection algorithm. The predicted error term is further used by the reconfigurable controller which finally aims to mitigate the number of vehicles waiting at the stop line, i.e. the delay caused by the intersection. A simulation study is also carried out to demonstrate the effectiveness of the controller extended by congestion detection filter.

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.

scholarly journals Research on Control Methods for the Pressure Continuous Regulation Electrohydraulic Proportional Axial Piston Pump of an Aircraft Hydraulic System

2019 ◽  
Vol 9 (7) ◽  
pp. 1376
Author(s):  
Peng Zhang ◽  
Yunhua Li
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Piston Pump ◽  
Control Methods ◽  
Hydraulic Systems ◽  
Axial Piston Pump ◽  
Linear Quadratic ◽  
Delivery Pressure ◽  
Axial Piston

The objective of this paper is to design a pump that can match its delivery pressure to the aircraft load. Axial piston pumps used in airborne hydraulic systems are required to work in a constant pressure mode setting based on the highest pressure required by the aircraft load. However, the time using the highest pressure working mode is very short, which leads to a lot of overflow lose. This study is motivated by this fact. Pressure continuous regulation electrohydraulic proportional axial piston pump is realized by combining a dual-pressure piston pump with electro-hydraulic proportional technology, realizing the match between the delivery pressure of the pump and the aircraft load. The mathematical model is established and its dynamic characteristics are analyzed. The control methods such as a proportional integral derivative (PID) control method, linear quadratic regulator (LQR) based on a feedback linearization method and a backstepping sliding control method are designed for this nonlinear system. It can be seen from the result of simulation experiments that the requirements of pressure control with a pump are reached and the capacity of resisting disturbance of the system is strong.

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.

Flight Control System Design for Propulsion-Controlled Aircraft

2005 ◽  
Vol 219 (4) ◽  
pp. 329-340 ◽  
Author(s):  
Y Ochi
Keyword(s):  
Flight Control ◽  
Linear Models ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
State Feedback Control ◽  
Longitudinal Motion ◽  
Linear Quadratic ◽  
Engine Thrust ◽  
Model Following Control ◽  
Flight Controls

The loss of an aircraft's primary flight controls can lead to a fatal accident. However, if the engine thrust is available, controllability and safety can be retained. This article describes flight control using engine thrust only when an aircraft has lost all primary flight controls. This is a kind of flight control reconfiguration. For safe return, the aircraft must first descend to a landing area, decelerate to a landing speed, and then be capable of precise flight control for approach and landing. For these purposes, two kinds of controllers are required: a controller for descent and deceleration and a controller for approach and landing. The former controller is designed for longitudinal motion using a model-following control method, based on a linear quadratic regulator. The latter is designed by an H∞ state-feedback control method for both longitudinal and lateral-directional motions. Computer simulation is conducted using linear models of the Boeing 747. The results indicate that flight path control, including approach and landing, is possible using thrust only; however, speed control proves more difficult. However, if the horizontal stabilizer is available, the airspeed can be reduced to a safe landing speed.

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 The Design of Optimal PID Control Method for Quadcopter Movement Control

2018 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Hanum Arrosida ◽  
Mohammad Erik Echsony
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Controller Design ◽  
Minimum Energy ◽  
Linear Quadratic Regulator ◽  
Research Field ◽  
Unmanned Aircraft ◽  
Control Methods ◽  
Linear Quadratic ◽  
Optimal Pid Control

Nowadays, quadcopter motion control has become a popular research topic because of its versatile ability as an unmanned aircraft can be used to alleviate human labor and also be able to reach dangerous areas or areas which is unreachable to humans. On the other hand, the Optimal PID control method, which incorporates PID and Linear Quadratic Regulator (LQR) control methods, has also been widely used in industry and research field because it has advantages that are easy to operate, easy design, and a good level of precision. In the PID control method, the main problem to be solved is the accuracy of the gain value Kp, Ki, and Kd because the inappropriateness of those value will result in an imprecise control action. Based on these problems and referring to the previous study, the optimal PID control method was developed by using PID controller structure with tuning gain parameter of PID through Linear Quadratic Regulator (LQR) method. Through the integration of these two control methods, the optimum solutions can be obtained: easier controller design process for quadcopter control when crossing the determined trajectories, steady state error values less than 5% and a stable quadcopter movement with roll and pitch angle stabilization at position 0 radians with minimum energy function.

scholarly journals Stabilized controller of a two wheels robot

2020 ◽  
Vol 9 (4) ◽  
pp. 1357-1363
Author(s):  
Ahmad Fahmi ◽  
Marizan Sulaiman ◽  
Indrazno Siradjuddin ◽  
I Made Wirawan ◽  
Abdul Syukor Mohamad Jaya ◽  
...  
Keyword(s):  
Control Method ◽  
Control Function ◽  
Balance Control ◽  
Linear Quadratic Regulator ◽  
Zero Point ◽  
Stability Control ◽  
Pole Placement ◽  
Linear Quadratic ◽  
Balancing Robot ◽  
The Stability

The Segway Human Transport (HT) robot, it is dynamical self-balancing robot type. The stability control is an important thing for the Segway robot. It is an indisputable fact that Segway robot is a natural instability framework robot. The case study of the Segway robot focuses on running balance control systems. The roll, pitch, and yaw balance of this robot are obtained by estimating the Kalman Filter with a combination of the pole placement and the Linear Quadratic Regulator (LQR) control method. In our system configuration, the mathematical model of the robot will be proved by Matlab Simulink by modelling of the stabilizing control system of all state variable input. Furthermore, the implementation of this system modelled to the real-time test of the Segway robot. The expected result is by substitute the known parameters from Gyro, Accelero and both rotary encoder to initial stabilize control function, the system will respond to the zero input curve. The coordinate units of displacement response and inclination response pictures are the same. As our expected, the response of the system can reach the zero point position. 

scholarly journals Improve Linear Quadratic Regulator by Particle Swarm Optimization Algorithms for Two Wheeled Self Balancing Mobile robot

2017 ◽  
Vol 13 (2) ◽  
pp. 173-179
Author(s):  
Ekhlas Karam ◽  
Noor Mjeed
Keyword(s):  
Particle Swarm Optimization ◽  
Numerical Method ◽  
Control Method ◽  
Particle Swarm ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Swarm Optimization ◽  
Balancing Robot ◽  
The Stability ◽  
Multivariable Feedback

The aim of this paper is to suggest a methodical smooth control method for improving the stability of two wheeled self-balancing robot under effect disturbance. To promote the stability of the robot, the design of linear quadratic regulator using particle swarm optimization (PSO) method and adaptive particle swarm optimization (APSO). The computation of optimal multivariable feedback control is traditionally by LQR approach by Riccati equation. Regrettably, the method as yet has a trial and error approach when selecting parameters, particularly tuning the Q and R elements of the weight matrices. Therefore, an intelligent numerical method to solve this problem is suggested by depending PSO and APSO algorithm. To appraise the effectiveness of the suggested method, The Simulation result displays that the numerical method makes the system stable and minimizes processing time.

New genetic algorithm for structural active control by considering the effect of time delay

2020 ◽  
pp. 107754632093346
Author(s):  
Ali Banaei ◽  
Javad Alamatian
Keyword(s):  
Genetic Algorithm ◽  
Time Delay ◽  
Active Control ◽  
Control Method ◽  
Control Process ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
The Common ◽  
New Generation ◽  
Active Control Method

This study focuses on a new active control method by improving specification of a well-known intelligent numerical search method, that is the genetic algorithm. The proposed scheme modifies the specifications of the common genetic algorithm by using two strategies. First, a new constrained objective function is proposed. Then, a procedure is designed for evaluating and reducing time delay in control process. These procedures lead to a new generation of the genetic algorithm, which is more reliable. For verifying the efficiency of the proposed method, vibrations of several structures are controlled, and results are compared with other well-known methods such as the common genetic algorithm, linear quadratic regulator, and equivalent critical damping. Numerical results clearly prove the accuracy and efficiency of the proposed control process in comparison with other methods.

Fractional Order LQR for Optimal Robust Control of a Simple Structure

2007 ◽  
Author(s):  
Abdollah Shafieezadeh ◽  
Keri Ryan ◽  
YangQuan Chen
Keyword(s):  
Robust Control ◽  
Control Problem ◽  
Fractional Order ◽  
Simple Structure ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Fractional Damping ◽  
Fractional Order Control

This study combines fractional order control with linear quadratic regulator (LQR) for optimal robust control of a simple civil structure. As a first attempt, the purpose of this paper is to demonstrate that, when fractional damping is introduced, additional benefits can be obtained over the best traditional control method. The control problem of this paper can be used as a simple benchmark example to test new control ideas before applying to more complicated models.

Sign in / Sign up

Export Citation Format

Share Document