The Design of Hopping Angle Control by Using PID and LQR Techniques

2013 ◽  
Vol 419 ◽  
pp. 693-700
Author(s):  
Saifullah Samo ◽  
Shu Yuan Ma ◽  
Bdran Sameh
Keyword(s):  
Pid Controller ◽  
Linear Quadratic Regulator ◽  
Dc Motor ◽  
Linear Quadratic ◽  
Matlab Simulink ◽  
Hopping Robot ◽  
Hopping Robots ◽  
Obstacle Height

It is very difficult for hopping robots to follow the trajectory without controlling hopping angle. A hopping angle controller is designed for combustion piston type hopping robot to adjust the angle of hop which is required to achieve a desired distance or height. So, the controller adds functionality to hopping robot for altering the hopping angle during operation according to obstacle height and obstacle distance. A proportional Integrated Derivative (PID) and Linear Quadratic Regulator (LQR) are designed and compared for adjusting hopping angle by using MATLAB / SIMULINK environment. As result, both controllers are capable to control hopping angle but PID gives better performance. An implementation of PID controller for the hopping angle control is given by using a DC motor. The experiment also carried out on prototype by using PID controller and found satisfactory results.

Stabilizing and Swinging-Up the Inverted Pendulum Using PI and PID Controllers Based on Reduced Linear Quadratic Regulator Tuned by PSO

2015 ◽  
Vol 4 (4) ◽  
pp. 52-69 ◽  
Author(s):  
M. E. Mousa ◽  
M. A. Ebrahim ◽  
M. A. Moustafa Hassan
Keyword(s):  
Pid Controller ◽  
Inverted Pendulum ◽  
Research Work ◽  
Linear Quadratic Regulator ◽  
Nonlinear Problems ◽  
Pid Controllers ◽  
Linear Quadratic ◽  
Swarm Optimization ◽  
Feed Forward ◽  
Forward Gain

The inherited instabilities in the Inverted Pendulum (IP) system make it one of the most difficult nonlinear problems in the control theory. In this research work, Proportional –Integral and Derivative (PID) Controller with a feed forward gain is used with Reduced Linear Quadratic Regulator (RLQR) for stabilizing the Cart Position and Swinging-up the Pendulum angle. Tuning the Controllers' gains is achieved by using Particle Swarm Optimization (PSO) Technique. Obtaining the combined PID controllers' gains with a feed forward gain and RLQR is a multi-dimensions control problem. The Proposed Controllers give minimum Settling Time, Rise Time, Undershoot and Over shoot for both the Cart Position and the Pendulum angle. A disturbance with different amplitudes is applied to the system, and the results showed the robustness of the systems based on the tuned controllers. The overall results are promising.

scholarly journals The linear quadratic regular algorithm-based control system of the direct current motor

2019 ◽  
Vol 10 (2) ◽  
pp. 768
Author(s):  
Trong-Thang Nguyen
Keyword(s):  
Control System ◽  
Direct Current ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
Response Speed ◽  
Dc Motor ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
Mathematical Equations ◽  
Feed Forward Controller

<span>This research aims to propose an optimal controller for controlling the speed of the Direct Current (DC) motor. Based on the mathematical equations of DC Motor, the author builds the equations of the state space model and builds the linear quadratic regulator (LQR) controller to minimize the error between the set speed and the response speed of DC motor. The results of the proposed controller are compared with the traditional controllers as the PID, the feed-forward controller. The simulation results show that the quality of the control system in the case of LQR controller is much higher than the traditional controllers. The response speed always follows the set speed with the short conversion time, there isn't overshoot. The response speed is almost unaffected when the torque impact on the shaft is changed.</span>

scholarly journals Cross Regulation Reduced Optimal Multivariable Controller Design for Single Inductor DC-DC Converters

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 477 ◽  
Author(s):  
S. Augusti Lindiya ◽  
N. Subashini ◽  
K. Vijayarekha
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Multiple Input Multiple Output ◽  
Linear Quadratic Regulator ◽  
Prototype Model ◽  
Linear Quadratic ◽  
Load Current ◽  
Practical Applications ◽  
Input Multiple Output ◽  
Single Input

Single Inductor (SI) converters with the advantage of using one inductor for any number of inputs/outputs find wide applications in portable electronic gadgets and electrical vehicles. SI converters can be used in Single Input Multiple Output (SIMO) and Multiple Input Multiple Output (MIMO) configurations but they need controllers to achieve good transient and steady state responses, to improve the stability against load and line disturbances and to reduce cross regulation. Cross regulation is the change in an output voltage due to change in the load current at another output and it is an added constraint in SI converters. In this paper, Single Input Dual Output (SIDO) and Dual Input Dual Output (DIDO) converters with applications capable of handling high load current working in Continuous Conduction Mode (CCM) of operation are taken under study. Conventional multivariable PID and optimal Linear Quadratic Regulator (LQR) controllers are developed and their performances are compared for the above configurations to meet the desired objectives. Generalized mathematical models for SIMO and MIMO are developed and a Genetic Algorithm (GA) is used to find the parameters of a multivariable PID controller and the weighting matrices of optimal LQR where the objective function includes cross regulation as a constraint. The simulated responses reveal that LQR controller performs well for both the systems over multivariable PID controller and they are validated by hardware prototype model with the help of DT9834® Data Acquisition Module (DAQ). The methodologies used here generate a fresh dimension for the case of such converters in practical applications.

Comparison of Performance Measures of Speed Control for a DC Motor Using Hybrid Intelligent Controller and Optimal LQR

2014 ◽  
Vol 622 ◽  
pp. 23-31
Author(s):  
T. Velayudham Narmadha ◽  
Chackaravarthy Baskaran ◽  
K. Sivakumar
Keyword(s):  
Rise Time ◽  
Linear Quadratic Regulator ◽  
Speed Control ◽  
Dc Motor ◽  
Pid Controllers ◽  
Rule Base ◽  
Fuzzy Pid ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
Fuzzy Pd

-In this paper , performance of fuzzy PD , fuzzy PI , fuzzy PD+I , fuzzy PID controllers are evaluated and compared. This paper also describes the speed control based on Linear Quadratic Regulator (LQR) technique. The comparison is based on their ability of controlling the speed of DC motor, which merely focuses on performance index of the controllers, and also time domain specifications such as rise time, settling time and peak overshoot. The controller is modelled using MATLAB software, the simulation results shows that the fuzzy PID controllers are the best performing candidates in all aspects but it as higher overshoot and IAE in comparison with optimal LQR. The Fuzzy PI controller exhibited null offset but suffers from poor stability and peak overshoot, whereas the fuzzy PD controller has fast rise time, with no overshoots but the IAE is much greater. Thus, the comparative analysis recommends fuzzy PID controller but it is usually associated with complicated rule base and tedious tuning. To circumvent these problems, the proposed LQR controller gives better performance than the other controllers.

scholarly journals Analyze and Evaluate the Performance Velocity Control in DC Motor

2020 ◽  
Vol 12 (4) ◽  
pp. 507-516
Author(s):  
Hazim M. Alkargole ◽  
◽  
Abbas S. Hassan ◽  
Raoof T. Hussein ◽  
◽  
...  
Keyword(s):  
Fuzzy Logic Controller ◽  
Linear Quadratic Regulator ◽  
Dc Motor ◽  
Rule Base ◽  
Velocity Control ◽  
Linear Quadratic ◽  
Proportional Integral ◽  
Motor Controller ◽  
Different Types ◽  
Rule Bases

A mathematical model of controlling the DC motor has been applied in this paper. There are many and different types of controllers have been used with purpose of analyzing and evaluating the performance of the of DC motor which are, Fuzzy Logic Controller (FLC), Linear Quadratic Regulator (LQR), Fuzzy Proportional Derivative (FPD) ,Proportional Integral Derivative (PID), Fuzzy Proportional Derivative with integral (FPD plus I) , and Fuzzy Proportional Integral (FPI) with membership functions of 3*3, 5*5, and 7*7 rule bases. The results show that the (FLC) controller with 5*5 rule base provides the best results among all the other controllers to design the DC motor controller.

scholarly journals DC Motor Speed Control using Internal Model Controller: Industrial Transformation Strategy

2020 ◽  
Vol 9 (5) ◽  
pp. 300-306
Keyword(s):  
Transfer Function ◽  
Pid Control ◽  
Pid Controller ◽  
Internal Model ◽  
Dc Motor ◽  
Motor Speed ◽  
Matlab Simulink ◽  
Dc Motors ◽  
Control Schemes ◽  
Motor Model

In developed nations, industries are made to function at control engineering costs via the use of appropriate control schemes for dc motors. This paper introduces the role played by dc motors in industries thereby necessitating the analysis and performance validation of dc motor in Internal Model Control (IMC) scheme as against the Proportional– Integral–Derivative (PID) control schemes that is widely used in most industries. Theories on dc motor model, PID and IMC controller were detailed to paved the way for the methodical approach of getting specifications and transfer function for a typical dc motor (model RMCS-3011). Matlab/Simulink software was then used to tune the PID controller for the purpose of finding the values of PID gains that meets the design requirements to achieve best performance, thereby enabling the simulation of the PID controller. Using Matlab m-file environment, IMC controller transfer function was generated and simulated. The IMC controller transfer function aimed at achieving a unity gain that tracks the set-point was approximately realized. In the realization process, it was obvious that a filter is required. The aim of this work is to evaluate the performance of the IMC controller over PID controller. Simulated plots in Matlab-Simulink using the PID gains for the PID controller, and time constants and filter order for the IMC were presented. The quantitative results of the IMC method when compared with that of PID control provides a commendable performance. However, the performance in terms of rise time is small and preferred with the use of Matlab-Simulink tuned PID controller. Conclusively, IMC controller would be the preferred controller where the robustness and accuracy of the dc motor speed control counts more than faster response

scholarly journals Elevation, pitch and travel axis stabilization of 3DOF helicopter with hybrid control system by GA-LQR based PID controller

2020 ◽  
Vol 10 (2) ◽  
pp. 1868 ◽  
Author(s):  
Ibrahim K. Mohammed ◽  
Abdulla I. Abdulla
Keyword(s):  
Pid Controller ◽  
Hybrid Control ◽  
Research Work ◽  
Linear Quadratic Regulator ◽  
Optimization Method ◽  
Feedback Gain ◽  
Algorithm Optimization ◽  
Linear Quadratic ◽  
Control Approach ◽  
Lqr Controller

This research work presents an efficient hybrid control methodology through combining the traditional proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) optimal controlher. The proposed hybrid control approach is adopted to design three degree of freedom (3DOF) stabilizing system for helicopter. The gain parameters of the classic PID controller are determined using the elements of the LQR feedback gain matrix. The dynamic behaviour of the LQR based PID controller, is modeled and the formulated in state space form to enable utlizing state feedback controller technique. The performance of the proposed LQR based LQR controller is improved by using Genetic Algorithm optimization method which are adopted to obtain optimum values for LQR controller gain parameters. The LQR-PID hybrid controller is simulated using Matlab environment and its performance is evaluated based on rise time, settling time, overshoot and steady state error parameters to validate the proposed 3DOF helicopter balancing system. Based on GA tuning approach, the simulation results suggest that the hybrid LQR-PID controller can be effectively adopted to stabilize the 3DOF helicopter system.

scholarly journals MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

Robotics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 36 ◽  
Author(s):  
Rafael Guardeño ◽  
Manuel J. López ◽  
Víctor M. Sánchez
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Low Cost ◽  
Robustness Analysis ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Estimation Errors ◽  
Plant Model ◽  
Bias Drift ◽  
Noise Characteristics

In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design method for multivariable PID controller is robust with respect to: (a) parametric uncertainty in the plant model, (b) disturbances acting at the plant input, (c) sensors measurement and estimation errors.

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