Models of a hybrid wheeled hopping self-balanced robot

2021 ◽  
pp. 095440622098419
Author(s):  
Qimin Li ◽  
Haibing Zeng ◽  
Long Bai ◽  
Zijian An
Keyword(s):  
Pid Control ◽  
Motion Pattern ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Swarm Optimization ◽  
Hopping Robot ◽  
Control Scheme ◽  
Hopping Robots ◽  
Hybrid Motion ◽  
Classical Control

Combining wheeled structure with hopping mechanism, this paper purposes a self-balanced hopping robot with hybrid motion pattern. The main actuator which is the cylindrical cam, optimized by particle swarm optimization (PSO), is equipped with the motor to control the hopping motion. Robotic system dynamics model is established and solved by Lagrangian method. After linearization, control characteristics of the system is obtained by classical control theory based on dynamics equations. By applying Adams and Matlab to simulate the system, hopping locomotion and self-balanced capability are validated respectively, and result shows that jump height can reach 750 mm theoretically. Then PID control scheme is developed and specific models of hardware and software are settled down accordingly. Finally, prototype is implemented and series of hopping experiments are conducted, showing that with different projectile angle, prototype can jump 550 mm in height and 460 mm in length, transcending majority of other existing hopping robots.

PID PARAMETERS OPTIMIZATION USING PSO TECHNIQUE FOR NONLINEAR ELECTRO HYDRAULIC ACTUATOR

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Siti Marhainis Othman ◽  
Mohd Fua’ad Rahmat ◽  
Sahazati Md. Rozali ◽  
Sazilah Salleh
Keyword(s):  
Particle Swarm Optimization ◽  
Simulation Study ◽  
Pid Control ◽  
Parameters Optimization ◽  
Model Parameters ◽  
Time Varying ◽  
Proportional Integral Derivative ◽  
Hydraulic Actuator ◽  
Swarm Optimization ◽  
Control Scheme

Electro-hydraulic actuator (EHA) system inherently suffers from uncertainties, nonlinearities and time- varying in its model parameters which cause the modeling and controller designs are more complicated. Proportional Integral Derivative (PID) control scheme has been proposed and the main problem with its application is to tune the parameters to its optimum values. This study will look into an optimization of PID parameters using particle swarm optimization (PSO). Simulation study has been done in Matlab and Simulink. 

scholarly journals PID speed control of DC motor using meta-heuristic algorithms

2021 ◽  
Vol 12 (2) ◽  
pp. 822
Author(s):  
Bishwa Babu Acharya ◽  
Sandeep Dhakal ◽  
Aayush Bhattarai ◽  
Nawraj Bhattarai
Keyword(s):  
Particle Swarm Optimization ◽  
Transient Response ◽  
Pid Control ◽  
Heuristic Algorithms ◽  
Fitness Function ◽  
Optimal Solution ◽  
Absolute Error ◽  
Swarm Optimization ◽  
Unit Step ◽  
Control Scheme

This paper presents archimedes optimization algorithm(AOA) and dispersive flies optimization(DFO) to optimally tune gain parameters of PID control scheme in order to regulate DC motor’s speed. These suggested techniques tune the controller by the minimization of the fitness function represented by the integral of time multiplied by absolute error (ITAE). The modelling and simulation are carried out in MATLAB/Simulink. The transient response of unit step input obtained from AOA-PID-ITAE andDFO-PID-ITAE controllers were compared to those obtained from Ziegler-Nichols (ZN) method and particle swarm optimization(PSO). The results indicate that AOA-PID-ITAE and DFO-PID-ITAE are more efficient than ZN method and PSO in reducing rise time and settling time. Likewise, DFOconverge faster to the optimal solution with lower overshoot than AOA and PSO.

A System Dynamics Model of Health Insurance Financing in Austria

2010 ◽  
Vol 20 (2) ◽  
pp. 59-62
Author(s):  
Patrick Einzinger ◽  
Günther Zauner ◽  
G. Ganjeizadeh-Rouhani
Keyword(s):  
Health Insurance ◽  
System Dynamics ◽  
System Dynamics Model ◽  
Dynamics Model

scholarly journals Transforming a Liability into an Asset: A System Dynamics Model for Free-Ranging Dog Population Management

Systems ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 56
Author(s):  
Urmila Basu Mallick ◽  
Marja H. Bakermans ◽  
Khalid Saeed
Keyword(s):  
System Dynamics ◽  
Social Integration ◽  
Unintended Consequences ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Innovative Strategies ◽  
Management Context ◽  
Free Ranging ◽  
Social Rewards

Using Indian free-ranging dogs (FRD) as a case study, we propose a novel intervention of social integration alongside previously proposed methods for dealing with FRD populations. Our study subsumes population dynamics, funding avenues, and innovative strategies to maintain FRD welfare and provide societal benefits. We develop a comprehensive system dynamics model, featuring identifiable parameters customizable for any management context and imperative for successfully planning a widescale FRD population intervention. We examine policy resistance and simulate conventional interventions alongside the proposed social integration effort to compare monetary and social rewards, as well as costs and unintended consequences. For challenging socioeconomic ecological contexts, policy resistance is best overcome by shifting priority strategically between social integration and conventional techniques. The results suggest that social integration can financially support a long-term FRD intervention, while transforming a “pest” population into a resource for animal-assisted health interventions, law enforcement, and conservation efforts.

scholarly journals A System Dynamics Model to Facilitate the Development of Policy for Urban Heat Island Mitigation

Urban Science ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 19
Author(s):  
Robert Dare
Keyword(s):  
Climate Change ◽  
System Dynamics ◽  
Urban Heat Island ◽  
Future Climate Change ◽  
Specific Information ◽  
Heat Island ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Urban Heat ◽  
Related Mortality

This article presents a customized system dynamics model to facilitate the informed development of policy for urban heat island mitigation within the context of future climate change, and with special emphasis on the reduction of heat-related mortality. The model incorporates a variety of components (incl.: the urban heat island effect; population dynamics; climate change impacts on temperature; and heat-related mortality) and is intended to provide urban planning and related professionals with: a facilitated means of understanding the risk of heat-related mortality within the urban heat island; and location-specific information to support the development of reasoned and targeted urban heat island mitigation policy.

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