Dynamic modelling and control of industrial processes with particle filtering algorithms

2004 ◽  
pp. 721-726 ◽  
Author(s):  
Rubén Morales-Menéndez ◽  
Nando de Freitas ◽  
David Poole ◽  
Jim Mutch ◽  
Federico Guedea-Elizalde
Keyword(s):  
Particle Filtering ◽  
Dynamic Modelling ◽  
Industrial Processes ◽  
Filtering Algorithms ◽  
And Control

Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Nurali Virani ◽  
Devesh K. Jha ◽  
Zhenyuan Yuan ◽  
Ishana Shekhawat ◽  
Asok Ray
Keyword(s):  
Particle Filtering ◽  
Dynamic Models ◽  
Training Data ◽  
Data Driven ◽  
Conditional Density ◽  
Bayesian Filtering ◽  
State Dependent ◽  
State Evolution ◽  
And Control ◽  
Nonparametric Kernel

This paper addresses the problem of learning dynamic models of hybrid systems from demonstrations and then the problem of imitation of those demonstrations by using Bayesian filtering. A linear programming-based approach is used to develop nonparametric kernel-based conditional density estimation technique to infer accurate and concise dynamic models of system evolution from data. The training data for these models have been acquired from demonstrations by teleoperation. The trained data-driven models for mode-dependent state evolution and state-dependent mode evolution are then used online for imitation of demonstrated tasks via particle filtering. The results of simulation and experimental validation with a hexapod robot are reported to establish generalization of the proposed learning and control algorithms.

scholarly journals Advanced powertrain dynamic modelling and control for electrified vehicles

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880560 ◽  
Author(s):  
Xiaoyuan Zhu ◽  
Fei Meng ◽  
Haiping Du ◽  
Hamid Reza Karimi
Keyword(s):  
Dynamic Modelling ◽  
And Control ◽  
Electrified Vehicles

scholarly journals Simultaneous position and stiffness control of a revolute joint using a biphasic media variable stiffness actuator

2019 ◽  
Vol 1 (2) ◽  
pp. 80-97
Author(s):  
Jesus H Lugo
Keyword(s):  
Control Method ◽  
Variable Stiffness ◽  
Industrial Processes ◽  
Revolute Joint ◽  
Additional Information ◽  
Physical Prototype ◽  
Stiffness Control ◽  
Variable Stiffness Actuator ◽  
Control Fluid ◽  
And Control

Safe interactions between humans and robots are needed in several industrial processes and service tasks. Compliance design and control of mechanisms is a way to increase safety. This article presents a compliant revolute joint mechanism using a biphasic media variable stiffness actuator. The actuator has a member configured to transmit motion that is connected to a fluidic circuit, into which a biphasic control fluid circulates. Stiffness is controlled by changing pressure of control fluid into distribution lines. A mathematical model of the actuator is presented, a model-based control method is implemented to track the desired position and stiffness, and equations relating to the dynamics of the mechanism are provided. Results from force loaded and unloaded simulations and experiments with a physical prototype are discussed. The additional information covers a detailed description of the system and its physical implementation.

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