Trajectory Control Based on Discrete Full-Range Dynamics

2012 ◽  
Vol 24 (4) ◽  
pp. 612-619
Author(s):  
Nandan Maheshwari ◽  
◽  
Keith Gunura ◽  
Fumiya Iida
Keyword(s):  
Control Strategies ◽  
Full Range ◽  
Dynamics Simulation ◽  
Robotic Systems ◽  
Complex Environments ◽  
Joint Torques ◽  
Dynamic Switching ◽  
Novel Approach ◽  
Clutch Mechanism ◽  
Mechanical Dynamics

There has been an increasing interest in the use of mechanical dynamics, (e.g., passive, elastic, and viscous dynamics) for energy efficient and agile control of robotic systems. Despite the impressive demonstrations of behavioural performance, the mechanical dynamics of this class of robotic systems is still very limited as compared to those of biological systems. For example, passive dynamic walkers are not capable of generating joint torques to compensate for disturbances from complex environments. In order to tackle such a discrepancy between biological and artificial systems, we present the concept and design of an adaptive clutch mechanism that discretely covers the full-range of dynamics. As a result, the system is capable of a large variety of joint operations, including dynamic switching among passive, actuated and rigid modes. The main innovation of this paper is the framework and algorithm developed for controlling the trajectory of such joint. We present different control strategies that exploit passive dynamics. Simulation results demonstrate a significant improvement in motion control with respect to the speed of motion and energy efficiency. The actuator is implemented in a simple pendulum platform to quantitatively evaluate this novel approach.

Effects of active crowder size and activity-crowding coupling on polymer translocation

Soft Matter ◽  
2020 ◽  
Author(s):  
Fei Tan ◽  
Ying Chen ◽  
Nanrong Zhao
Keyword(s):  
Langevin Dynamics ◽  
Dynamics Simulation ◽  
Biological Processes ◽  
Two Dimensional ◽  
Complex Environments ◽  
Polymer Translocation ◽  
Langevin Dynamics Simulation

Polymer translocation in complex environments is crucially important to many biological processes in life. In the present work, we adopted two-dimensional Langevin dynamics simulation to study the forced and unbiased...

Mechanical Performance Simulation Model Based on PDM

2013 ◽  
Vol 300-301 ◽  
pp. 32-35
Author(s):  
Xiao Wen Zeng ◽  
Cheng Zeng ◽  
Bing Han
Keyword(s):  
Simulation Model ◽  
Mechanical Performance ◽  
Product Structure ◽  
Dynamics Simulation ◽  
Simulation Data ◽  
Performance Simulation ◽  
Collaborative Simulation ◽  
Complex Simulation ◽  
Mechanical Dynamics ◽  
Relationship Of

In order to manage the complex simulation data management in the process of mechanical dynamics simulation, a new management model was presented which is Performance Simulation Model(PSM). The model was based on PDM product structure and the concepts and elements of PSM were defined in this paper. Furthermore, the functional framework of PSM was proposed which based on the hierarchical relationship of product structure and the data stream relationship of data structure matrix. Finally, PSM was applied on ship planetary reducer collaborative simulation platform. The result indicates that the simulation data in mechanical collaborative simulation are managed by PSM, and the problem of interaction between collaborative simulation and PDM is solved.

A Comprehensive Study on Internet of Things Based on Key Artificial Intelligence Technologies and Industry 4.0

2021 ◽  
pp. 171-191
Author(s):  
Banu Çalış Uslu ◽  
Seniye Ümit Oktay Fırat
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Information Exchange ◽  
Industry 4.0 ◽  
New Technology ◽  
Smart Devices ◽  
Complex Environments ◽  
Novel Approach ◽  
Key Technologies ◽  
Shed Light

Under uncertainty, understanding and controlling complex environments is only possible with an ability to use distributed computing by the way of information exchange between devices to be able to understand the response of the system to a particular problem. From transformation of raw data in a huge distribution of network into the meaningful information, to use the understood knowledge to make rapid decisions needs to have a network composed of smart devices. Internet of things (IoT) is a novel approach, where these smart devices can communicate with each other by using key technologies of artificial intelligence (AI) in order to make timely autonomous decisions. This emerging technical advancement and realization of horizontal and vertical integration caused the fourth stage of industrialization (Industry 4.0). The objective of this chapter is to give detailed information on both IoT based on key AI technologies and Industry 4.0. It is expected to shed light on new work to be done by providing explanations about the new areas that will emerge with this new technology.

scholarly journals Some Problems of Feedback Control Strategies and It’s Treatment

2017 ◽  
Vol 9 (1) ◽  
pp. 39 ◽  
Author(s):  
Maysoon M. Aziz ◽  
Saad Fawzi AL-Azzawi
Keyword(s):  
Dynamical Systems ◽  
Feedback Control ◽  
Numerical Simulations ◽  
Positive Feedback ◽  
Control Strategies ◽  
Novel Approach

This paper extends and improves the feedback control strategies. In detailed, the ordinary feedback, dislocated feedback, speed feedback and enhancing feedback control for a several dynamical systems are discussed here. It is noticed that there some problems by these strategies. For this reason, this Letter proposes a novel approach for treating these problems. The results obtained in this paper show that the strategies with positive feedback coefficients can be controlled in two cases and failed in another two cases. Theoretical and numerical simulations are given to illustrate and verify the results.

Saturated RISE Feedback Control for Uncertain Nonlinear MacPherson Active Suspension System to Improve Ride Comfort

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Huyen T. Dinh ◽  
Tuan-Duong Trinh ◽  
Van-Nhu Tran
Keyword(s):  
Ride Comfort ◽  
Control Strategies ◽  
Gain Control ◽  
Active Suspension ◽  
High Gain ◽  
Suspension System ◽  
Dynamics Simulation ◽  
Control Technique ◽  
Nonlinear Uncertainties ◽  
Bounded Disturbances

Abstract A continuous saturated controller using smooth saturation functions is established for MacPherson active suspension system which includes nonlinear uncertainties, unknown road excitations, and bounded disturbances. The developed controller exploits the properties of the hyperbolic functions to guarantee saturation limits are not exceeded, while stability analysis procedures of the robust integral of the sign of the error (RISE) control technique utilize the advantages of high gain control strategies in compensating for unknown uncertainties. The saturated controller guarantees asymptotic regulation of the sprung mass acceleration to improve the ride comfort despite model uncertainties and additive disturbances in the dynamics. Simulation results demonstrate the improvement in the ride comfort while tire deflection and the suspension deflection are within admissible range in comparison with three other suspensions.

B-Spline Based Adaptive Control of Shape Memory Alloy Actuated Robotic Systems

2002 ◽  
Author(s):  
Yavuz Eren ◽  
Constantinos Mavroidis ◽  
Jason Nikitczuk
Keyword(s):  
Adaptive Control ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Large Scale ◽  
Full Range ◽  
Spline Approximation ◽  
Variable Structure ◽  
Robotic Systems ◽  
Integral Control ◽  
B Spline

In this paper we present a novel controller for Shape Memory Alloy (SMA) actuated robotic systems. The new controller, called BAC (B-spline based Adaptive Control), is based on a hybrid combination of gain scheduling, B-spline approximation, variable structure control and integral control. The proposed controller shows excellent positioning accuracy and speed throughout the full range of motion of a SMA actuated robotic system in large-scale applications. To demonstrate the validity of BAC, a novel anthropomorphic SMA Actuated forearm/wrist mechanism is utilized in real-time PC based control experiments. BAC is experimentally compared to PID and integral variable structure controllers and it is shown that its performance is superior.

scholarly journals MPPT Control Strategy of PV Based on Improved Shuffled Frog Leaping Algorithm under Complex Environments

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaohua Nie ◽  
Haoyao Nie
Keyword(s):  
Control Strategy ◽  
Control Strategies ◽  
Least Square ◽  
Measurement Noise ◽  
Complex Environments ◽  
Recursive Least Square ◽  
Shuffled Frog Leaping Algorithm ◽  
Noise Effects ◽  
Pv Array ◽  
Shuffled Frog Leaping

This work presents a maximum power point tracking (MPPT) based on the particle swarm optimization (PSO) improved shuffled frog leaping algorithm (PSFLA). The swarm intelligence algorithm (SIA) has vast computing ability. The MPPT control strategies of PV array based on SIA are attracting considerable interests. Firstly, the PSFLA was proposed by adding the inertia weight factor w of PSO in standard SFLA to overcome the defect of falling into the partial optimal solutions and slow convergence speed. The proposed PSFLA algorithm increased calculation speed and excellent global search capability of MPPT. Then, the PSFLA was applied to MPPT to solve the multiple extreme point problems of nonlinear optimization. Secondly, for the problems of MPPT under complex environments, a new MPPT strategy of the PSFLA combined with recursive least square filtering was proposed to overcome the measurement noise effects on MPPT accuracy. Finally, the simulation comparisons between PSFLA and SFLA algorithm were developed. The experiment and comparison between PSLFA and PSO algorithm under complex environment were executed. The simulation and experiment results indicate that the proposed MPPT control strategy based on PSFLA can suppress the measurement noise effects effectively and improve the PV array efficiency.

Validation of a non-linear vehicle dynamics simulation for limit handling

2002 ◽  
Vol 216 (4) ◽  
pp. 319-327 ◽  
Author(s):  
R Wade-Allen ◽  
J P Chrstos ◽  
G Howe ◽  
D H Klyde ◽  
T J Rosenthal
Keyword(s):  
Vehicle Dynamics ◽  
Normal Load ◽  
Full Range ◽  
Operating Regime ◽  
Operating Conditions ◽  
Dynamics Simulation ◽  
Passenger Cars ◽  
Power Train ◽  
Ground Vehicle ◽  
Dynamic Operating

This paper discusses the validation of a ground vehicle dynamics computer simulation that includes complete models for sprung and unsprung masses, tyres, suspension, steering and brake systems, and power train including engine, transmission and differentials. The models have been developed over the last decade and have been applied to single-unit passenger cars, trucks and buses, and articulated tractor/trailer vehicles up to limit performance operating conditions. The tyre and vehicle models use composite parameters that are relatively easy to measure. However, the measurements must cover the key operating regime where the simulation is expected to be applied. For example, limit performance manoeuvring conditions require tyre data over large slip conditions and high normal load (beyond the design load) to cover the full range of dynamic operating conditions. Spring and damper response should also take into account large deflections and high velocities respectively to cover relevant non-linearities.

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