scholarly journals Real-time implementation of an enhanced nonlinear PID controller based on harmony search for one-stage servomechanism system

2018 ◽  
Vol 12 (4) ◽  
pp. 4161-4179
Author(s):  
Mohamed. A. Shamseldin ◽  
Mohamed Sallam ◽  
A. M. Bassiuny ◽  
A. M. Abdel Ghany
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Controller Design ◽  
Optimization Technique ◽  
Harmony Search ◽  
Reference Test ◽  
Variable Position ◽  
Labview Software ◽  
One Stage ◽  
Search Optimization

This paper presents a real-time implementation of an enhanced nonlinear PID (NPID) controller to follow a preselected position profile of one stage servomechanism drive system. This purpose should be realized regardless the different operating points and external disorders (friction and backlash). In this study, the MATLAB Simulink used for purpose of controller design while the result from simulation will be executed in real time using LABVIEW software. There is not enough information about the servomechanism experimental setup so, the system identification techniques will be used via collecting experimental input/output data. The optimum parameters for the controllers have been obtained via harmony search optimization technique according to an effective cost function. Also, the performance of enhanced NPID controller has been investigated by comparing it with linear PID controller.  The experimental and simulation results show that the proposed NPID controller has minimum rise time and settling time through constant position reference test. Also, the NPID control is faster than the linear PID control by 40% in case of variable position reference test.

scholarly journals PID Controller Design Based on Global Optimization Technique with Additional Constraints

2016 ◽  
Vol 67 (3) ◽  
pp. 160-168 ◽  
Author(s):  
Stepan Ozana ◽  
Tomas Docekal
Keyword(s):  
Global Optimization ◽  
Pid Controller ◽  
Controller Design ◽  
Linear Time ◽  
Optimization Technique ◽  
Phase Margin ◽  
Linear Time Invariant ◽  
Pid Controller Design ◽  
Static Systems ◽  
Time Invariant

Abstract This paper deals with design of PID controller with the use of methods of global optimization implemented in Matlab environment and Optimization Toolbox. It is based on minimization of a chosen integral criterion with respect to additional requirements on control quality such as overshoot, phase margin and limits for manipulated value. The objective function also respects user-defined weigh coefficients for its particular terms for a different penalization of individual requirements that often clash each other such as for example overshoot and phase margin. The described solution is designated for continuous linear time-invariant static systems up to 4th order and thus efficient for the most of real control processes in practice.

Fuzzy Controller Design for Multi-Legged Robot

2011 ◽  
Vol 383-390 ◽  
pp. 7345-7350
Author(s):  
Zhi Yong Tang ◽  
Hai Xiao Zhong ◽  
Zhong Cai Pei ◽  
Yan Hao Bu
Keyword(s):  
Control System ◽  
Real Time ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
High Accuracy ◽  
Dynamics Analysis ◽  
Legged Robot ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

In this paper, we propose a mechanical structure for multi-legged robot. Referring the request of control system, we also made a proper choice on driving means. After dynamics analysis on a single leg of the robot, we make a simulation using ADAMS and get how the torque of each joint is changing when the robot is walking. The model of DC motor is established for the control system. Fuzzy PID controller was used to get real-time response and high accuracy of control system.

scholarly journals FSD-HSO Optimization Algorithm for Closed Fringes Interferogram Demodulation

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ulises H. Rodriguez-Marmolejo ◽  
Miguel Mora-Gonzalez ◽  
Jesus Muñoz-Maciel ◽  
Tania A. Ramirez-delreal
Keyword(s):  
Relative Error ◽  
Optimization Technique ◽  
Harmony Search ◽  
Mathematical Optimization ◽  
Physical Nature ◽  
Algorithm Optimization ◽  
Interference Phenomenon ◽  
Sinusoidal Modulation ◽  
Search Optimization ◽  
Mathematical Optimization Model

Due to the physical nature of the interference phenomenon, extracting the phase of an interferogram is a known sinusoidal modulation problem. In order to solve this problem, a new hybrid mathematical optimization model for phase extraction is established. The combination of frequency guide sequential demodulation and harmony search optimization algorithms is used for demodulating closed fringes patterns in order to find the phase of interferogram applications. The proposed algorithm is tested in four sets of different synthetic interferograms, finding a range of average relative error in phase reconstructions of 0.14–0.39 rad. For reference, experimental results are compared with the genetic algorithm optimization technique, obtaining a reduction in the error up to 0.1448 rad. Finally, the proposed algorithm is compared with a very known demodulation algorithm, using a real interferogram, obtaining a relative error of 1.561 rad. Results are shown in patterns with complex fringes distribution.

scholarly journals PSO-Based PID Controller Design for a Class of Stable and Unstable Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
K. Latha ◽  
V. Rajinikanth ◽  
P. M. Surekha
Keyword(s):  
Comparative Study ◽  
Real Time ◽  
Pid Controller ◽  
Controller Design ◽  
Pso Algorithm ◽  
Search Space ◽  
Process Models ◽  
Stabilizing Controller ◽  
Fixed Weight ◽  
Unstable Process

Nonlinear processes are very common in process industries, and designing a stabilizing controller is always preferred to maximize the production rate. In this paper, tuning of PID controller for a class of time delayed stable and unstable process models using Particle Swarm Optimization (PSO) algorithm is discussed. The dimension of the search space is only three (, , and ); hence, a fixed weight is assigned for the inertia parameter. A comparative study is presented between various inertia weights such as 0.5, 0.75, and 1. From the result, it is evident that the proposed method helps to attain better controller settings with reduced iteration number. The efficacy of the proposed scheme has been validated through a comparative study with classical controller tuning methods and heuristic methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Finally, a real-time implementation of the proposed method is carried on a nonlinear spherical tank system. From the simulation and real-time results, it is evident that the PSO algorithm performs well on the stable and unstable process models considered in this work. The PSO tuned controller offers enhanced process characteristics such as better time domain specifications, smooth reference tracking, supply disturbance rejection, and error minimization.

Online Controller Setpoint Optimization for Traction Control Systems Applied to Construction Machinery

2018 ◽  
Author(s):  
Addison Alexander ◽  
Annalisa Sciancalepore ◽  
Andrea Vacca
Keyword(s):  
Control System ◽  
Control Systems ◽  
Real Time ◽  
Controller Design ◽  
Optimization Technique ◽  
Parameter Tuning ◽  
System Model ◽  
Model Parameters ◽  
Time Data ◽  
Traction Control

The development of a suitable traction control system for off-road heavy machinery is complicated by several different factors, which differentiate these machines from typical on-road systems. One such difficulty arises from the fact that they are often operated on ground conditions which can vary widely and rapidly. Due to this, traction control systems designed for these vehicles must be robust to a large array of surface types, and they must be capable of reacting quickly to significant changes in those types. In order to accomplish this, this paper proposes an online parameter optimization technique suitable for tuning the setpoint of a control system to maximize the tractive potential of a construction vehicle in real time. The traction control principle itself is based on selectively braking wheels which are slipping. It also attempts to account for the interactions of the transmission systems that deliver power from the engine to the wheels. This research uses a wheel loader as a reference machine for assessing controller performance. Drawing on previous work in simulation and controller design, a system model was developed which incorporates the vehicle dynamics of the machine as well as the behavior of the electrohydraulic brakes. This system model was leveraged to understand the effect of different optimization schemes on the performance of the traction control. The self-tuning algorithm is based on a compound optimization method utilizing both a system identification component and a parameter tuning component. The first part optimizes the model parameters to fit it as well as possible to measured slip-friction data. Based on the results of this, the second part draws from theories of wheel traction to maximize a balance of pushing force and traction effectiveness. The result is a method which can achieve the proper setpoint based on real-time data describing the ground condition. This system was run first in simulation and then on a modified vehicle system. In both cases, the algorithm allows the controller to find better setpoints to improve the traction control performance online.

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