scholarly journals Optimal Covid-19 Based PD/PID Cascaded Tracking Control for Robot Arm driven by BLDC Motor

2021 ◽  
Vol 20 ◽  
pp. 217-227
Author(s):  
Mohamed A. Shamseldin
Keyword(s):  
Tracking Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Harmony Search ◽  
Optimization Techniques ◽  
Robot Arm ◽  
Continuous Change ◽  
Parameter Variations ◽  
Optimal Values ◽  
Proper Values

This paper presents an efficient covid-19 optimization algorithm to find the optimal values of the PD/PID cascaded controller. The purpose of the control algorithm is to force the link shaft to follow the desired reference position with good accuracy all time. This objective should be achieved for different position/time tracks regardless of load disturbance and parameter variations. This work, simulating how the covid-19 spreads and infects to optimize the parameters of the PD/ PID control. The initial values of PD/PID controller parameters consider the zero patient, which infects new patients (other values of PD/PID controller parameters). The optimization model simulates as accurately as possible the covid-19 activity. The covid-19 has two major advantages compared to other similar strategies. First, the covid-19 parameters are already adjusted according to disease statistics to prevent designers from initializing them with arbitrary values. Second, the approach has the ability to finish after several iterations where the infected population initially grows at an exponential rate. However, after some iterations. The proposed covid-19 was investigated with well-known optimization techniques such as the genetic algorithm (GA) and Harmony Search (HS) optimization. A multi-objective function is used to allow the designer to select the desired rise time, the desired settling time, the desired overshoot, and the desired steady-state error. Several tests have been performed to investigate the obtained proper values of PD/PID controller parameters. In the first test, a step position reference had been applied. In the second test, the continuous change in position reference had been subjected to the robot arm. The results provide that the covid-19 based PD/PID controller has the best performance among other techniques. In addition, the covid-19 based PID controller can track accurately the position command compared to other techniques.

scholarly journals Gait Tracking Control of Quadruped Robot Using Differential Evolution Based Structure Specified Mixed SensitivityH∞Robust Control

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Petrus Sutyasadi ◽  
Manukid Parnichkun
Keyword(s):  
Tracking Control ◽  
Control Algorithm ◽  
Joint Angle ◽  
Gait Pattern ◽  
Quadruped Robot ◽  
Robust Controller ◽  
Quadruped Robots ◽  
Parameter Variations ◽  
Real Hardware ◽  
Dynamic Gait

This paper proposed a control algorithm that guarantees gait tracking performance for quadruped robots. During dynamic gait motion, such as trotting, the quadruped robot is unstable. In addition to uncertainties of parameters and unmodeled dynamics, the quadruped robot always faces some disturbances. The uncertainties and disturbances contribute significant perturbation to the dynamic gait motion control of the quadruped robot. Failing to track the gait pattern properly propagates instability to the whole system and can cause the robot to fall. To overcome the uncertainties and disturbances, structured specified mixed sensitivityH∞robust controller was proposed to control the quadruped robot legs’ joint angle positions. Before application to the real hardware, the proposed controller was tested on the quadruped robot’s leg planar dynamic model using MATLAB. The proposed controller can control the robot’s legs efficiently even under uncertainties from a set of model parameter variations. The robot was also able to maintain its stability even when it was tested under several terrain disturbances.

Disturbance Observer Based Tracking Control

1997 ◽  
Vol 122 (2) ◽  
pp. 332-335 ◽  
Author(s):  
Chia-Shang Liu ◽  
Huei Peng
Keyword(s):  
Tracking Control ◽  
Disturbance Observer ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Correction Term ◽  
Superior Performance ◽  
Robot Arm ◽  
Disturbance Estimation ◽  
Control Scheme ◽  
Disturbance Term

A disturbance observer based tracking control algorithm is presented in this paper. The key idea of the proposed method is that the plant nonlinearities and parameter variations can be lumped into a disturbance term. The lumped disturbance signal is estimated based on a plant dynamic observer. A state observer then corrects the disturbance estimation in a two-step design. First, a Lyapunov-based feedback estimation law is used. The estimation is then improved by using a feedforward correction term. The control of a telescopic robot arm is used as an example system for the proposed algorithm. Simulation results comparing the proposed algorithm against a standard adaptive control scheme and a sliding mode control algorithm show that the proposed scheme achieves superior performance, especially when large external disturbances are present. [S0022-0434(00)00802-9]

scholarly journals Optimal Coronavirus Optimization Algorithm Based PID Controller for High Performance Brushless DC Motor

Algorithms ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 193
Author(s):  
Mohamed A. Shamseldin
Keyword(s):  
Optimization Algorithm ◽  
Rise Time ◽  
Pid Controller ◽  
High Performance ◽  
Harmony Search ◽  
Settling Time ◽  
Optimization Techniques ◽  
Bldc Motor ◽  
Brushless Dc ◽  
The Third

This paper presents an efficient coronavirus optimization algorithm (CVOA) to find the optimal values of the PID controller to track a preselected reference speed of a brushless DC (BLDC) motor under several types of disturbances. This work simulates how the coronavirus (COVID-19) spreads and infects healthy people. The initial values of PID controller parameters consider the zero patient, who infects new patients (other values of PID controller parameters). The model aims to simulate as accurately as possible the coronavirus activity. The CVOA has two major advantages compared to other similar strategies. First, the CVOA parameters are already adjusted according to disease statistics to prevent designers from initializing them with arbitrary values. Second, the approach has the ability to finish after several iterations where the infected population initially grows at an exponential rate. The proposed CVOA was investigated with well-known optimization techniques such as the genetic algorithm (GA) and Harmony Search (HS) optimization. A multi-objective function was used to allow the designer to select the desired rise time, the desired settling time, the desired overshoot, and the desired steady-state error. Several tests were performed to investigate the obtained proper values of PID controller parameters. In the first test, the BLDC motor was exposed to sudden load at a steady speed. In the second test, the continuous sinusoidal load was applied to the rotor of the BLDC motor. In the third test, different operating points of reference speed were selected to the rotor of the BLDC motor. The results proved that the CVOA-based PID controller has the best performance among the techniques. In the first test, the CVOA-based PID controller has a minimum rise time (0.0042 s), minimum settling time (0.0079 s), and acceptable overshoot (0.0511%). In the second test, the CVOA-based PID controller has the minimum deviation about the reference speed (±4 RPM). In the third test, the CVOA-based PID controller can accurately track the reference speed among other techniques.

Velocity Tracking Control for Hydraulic Lifting System Based on Adaptive PSD Controller

2013 ◽  
Vol 394 ◽  
pp. 398-403
Author(s):  
Chang Lin Ma ◽  
Lin Hao ◽  
Feng Li
Keyword(s):  
Tracking Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Single Neuron ◽  
Control Method ◽  
Single Neutron ◽  
Single Neuron Pid ◽  
Lifting System ◽  
Adaptive Pid Control ◽  
Velocity Tracking

The single neutron adaptive PID controller is applied to the angular velocity tracking control of the hydraulic lifting system. The angle velocity tracking control strategy of the lifting process is proposed, and the lifting angle velocity is designed based on the sine acceleration function, and the lifting angle velocity dynamic programming based on the real-time angle is proposed. The single neutron adaptive PID control method is studied, and in order to improve its performance, a method utilizing genetic algorithm to optimize these parameters of single neuron PID controller is presented. The control algorithm is applied to the large mechanical lifting process successfully, and the simulation results show that the control performance of the Adaptive PSD Controller is more effective.

Optimal tuning of PID controller in time delay system: a review on various optimization techniques

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Thomas George ◽  
V. Ganesan
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Pid Controller ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Delay Systems ◽  
Pid Controllers ◽  
Time Delay Systems ◽  
Process Industries ◽  
First Order

AbstractThe processes which contain at least one pole at the origin are known as integrating systems. The process output varies continuously with time at certain speed when they are disturbed from the equilibrium operating point by any environment disturbance/change in input conditions and thus they are considered as non-self-regulating. In most occasions this phenomenon is very disadvantageous and dangerous. Therefore it is always a challenging task to efficient control such kind of processes. Depending upon the number of poles present at the origin and also on the location of other poles in transfer function different types of integrating systems exist. Stable first order plus time delay systems with an integrator (FOPTDI), unstable first order plus time delay systems with an integrator (UFOPTDI), pure integrating plus time delay (PIPTD) systems and double integrating plus time delay (DIPTD) systems are the classifications of integrating systems. By using a well-controlled positioning stage the advances in micro and nano metrology are inevitable in order satisfy the need to maintain the product quality of miniaturized components. As proportional-integral-derivative (PID) controllers are very simple to tune, easy to understand and robust in control they are widely implemented in many of the chemical process industries. In industries this PID control is the most common control algorithm used and also this has been universally accepted in industrial control. In a wide range of operating conditions the popularity of PID controllers can be attributed partly to their robust performance and partly to their functional simplicity which allows engineers to operate them in a simple, straight forward manner. One of the accepted control algorithms by the process industries is the PID control. However, in order to accomplish high precision positioning performance and to build a robust controller tuning of the key parameters in a PID controller is most inevitable. Therefore, for PID controllers many tuning methods are proposed. the main factors that lead to lifetime reduction in gain loss of PID parameters are described in This paper and also the main methods used for gain tuning based on optimization approach analysis is reviewed. The advantages and disadvantages of each one are outlined and some future directions for research are analyzed.

scholarly journals Optimal Fractional PID Controller for Buck Converter Using Cohort Intelligent Algorithm

2021 ◽  
Vol 4 (3) ◽  
pp. 50
Author(s):  
Preeti Warrier ◽  
Pritesh Shah
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Power Converters ◽  
Buck Converter ◽  
Optimization Techniques ◽  
Superior Performance ◽  
Computational Time ◽  
Optimization Approach ◽  
Response Characteristics ◽  
Fractional Order Controller

The control of power converters is difficult due to their non-linear nature and, hence, the quest for smart and efficient controllers is continuous and ongoing. Fractional-order controllers have demonstrated superior performance in power electronic systems in recent years. However, it is a challenge to attain optimal parameters of the fractional-order controller for such types of systems. This article describes the optimal design of a fractional order PID (FOPID) controller for a buck converter using the cohort intelligence (CI) optimization approach. The CI is an artificial intelligence-based socio-inspired meta-heuristic algorithm, which has been inspired by the behavior of a group of candidates called a cohort. The FOPID controller parameters are designed for the minimization of various performance indices, with more emphasis on the integral squared error (ISE) performance index. The FOPID controller shows faster transient and dynamic response characteristics in comparison to the conventional PID controller. Comparison of the proposed method with different optimization techniques like the GA, PSO, ABC, and SA shows good results in lesser computational time. Hence the CI method can be effectively used for the optimal tuning of FOPID controllers, as it gives comparable results to other optimization algorithms at a much faster rate. Such controllers can be optimized for multiple objectives and used in the control of various power converters giving rise to more efficient systems catering to the Industry 4.0 standards.

Development of Exoskeleton Suit for Rehabilitation

2013 ◽  
Vol 717 ◽  
pp. 592-597
Author(s):  
Surachai Panich
Keyword(s):  
Lower Limb ◽  
Pid Controller ◽  
Control Algorithm ◽  
Passive Mode ◽  
Active Mode

This paper introduced the rehabilitation for leg lower limp with exoskeleton suit. The rehabilitation is mainly classified in three modes, which are active, passive and active - assistive mode. In active mode, it provides appropriate resistance to the muscles to increase endurance and strength, because the patients must lift leg lower limp by their effort. In passive mode, patients cannot participate in process of rehabilitation and no effort is required, because patients leg lower limb will be driven by exoskeleton suit. In the last active-assistive mode is the combination of active and passive mode for patients, who has capability to move their joints but not reached the desired level. The control algorithm is designed to achieve rehabilitation modes by using classical PID controller.

Sign in / Sign up

Export Citation Format

Share Document