scholarly journals Modal Decoupled Dynamics Feed-Forward Active Force Control of Spatial Multi-DOF Parallel Robotic Manipulator

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Xinjian Niu ◽  
Chifu Yang ◽  
Bowen Tian ◽  
Xiang Li ◽  
Junwei Han
Keyword(s):  
Control Strategy ◽  
Force Control ◽  
Parallel Mechanism ◽  
Control Method ◽  
Intelligent System ◽  
Joint Space ◽  
Active Force ◽  
Feed Forward ◽  
Electric Actuator ◽  
Active Force Control

According to the parallel mechanism theory, this paper proposes a novel intelligent robotic spine brace for the treatment of scoliosis. Nevertheless, this type of parallel mechanism has the following disadvantages: strong dynamic coupling in task space or joint space, adverse effect of system’s gravity, and lower response frequency in roll and pitch orientations, which seriously affect the performance of the system. In order to solve those boring problems, this paper presents a novel active force control structure, modal space dynamic feed-forward (MSDF) force control strategy. Besides, this paper expresses the intelligent robotic brace system model including the dynamic and kinematic models and the electric actuator model with Kane strategy. The stability of the intelligent system with the novel control strategy is proved. In order to evaluate the performance of the presented MSDF force control method, this paper builds the parallel mechanism experimental platform. It can be seen from experimental results that the proposed motion control method solves these boring problems well.

Hardware-in-the-Loop Simulation for Active Force Control with Iterative Learning Applied to an Active Vehicle Suspension System

2013 ◽  
Vol 465-466 ◽  
pp. 801-805
Author(s):  
Rosmazi Rosli ◽  
Musa Mailah ◽  
Gigih Priyandoko
Keyword(s):  
Force Control ◽  
Control Method ◽  
Learning Algorithm ◽  
Suspension System ◽  
Iterative Learning ◽  
Practical Implementation ◽  
Hardware In The Loop ◽  
Active Force ◽  
Physical Test ◽  
Active Force Control

The paper focuses on the practical implementation of a novel control method to an automotive suspension system using active force control (AFC) with iterative learning algorithm (ILA) and proportional-integral-derivative (PID) control strategy. The overall control system to be known as AFC-IL scheme essentially comprises three feedback control loops to cater for a number of specific tasks, namely, the innermost loop for the force tracking of the pneumatic actuator using PI controller, intermediate loops applying AFC with ILA strategy for the compensation of the disturbances and the outermost loop using PID controller for the computation of the desired force. A number of experiments were carried out on a physical test rig with hardware-in-the-loop simulation (HILS) feature that fully incorporates the theoretical elements. The performance of the proposed control method was evaluated and benchmarked to examine the effectiveness of the system in suppressing the vibration effect of the suspension system. It was found that the experimental results demonstrate the superiority of the active suspension system with proposed AFC-IL scheme compared to the PID and passive counterparts.

scholarly journals Control of Liquid Sloshing Container using Active Force Control Method

2017 ◽  
Vol 190 ◽  
pp. 012007 ◽  
Author(s):  
Didik Setyo Purnomo ◽  
Adnan Rachmad Anom Besari ◽  
Zaqiatud Darojah
Keyword(s):  
Force Control ◽  
Control Method ◽  
Liquid Sloshing ◽  
Active Force ◽  
Active Force Control

A hybrid active force control of a lower limb exoskeleton for gait rehabilitation

2018 ◽  
Vol 63 (4) ◽  
pp. 491-500 ◽  
Author(s):  
Zahari Taha ◽  
Anwar P.P. Abdul Majeed ◽  
Amar Faiz Zainal Abidin ◽  
Mohammed A. Hashem Ali ◽  
Ismail Mohd Khairuddin ◽  
...  
Keyword(s):  
Force Control ◽  
Lower Limb ◽  
Sagittal Plane ◽  
Joint Space ◽  
Gait Rehabilitation ◽  
Active Force ◽  
Lower Limb Exoskeleton ◽  
Active Force Control ◽  
Increasing Demand ◽  
And Control

Abstract Owing to the increasing demand for rehabilitation services, robotics have been engaged in addressing the drawbacks of conventional rehabilitation therapy. This paper focuses on the modelling and control of a three-link lower limb exoskeleton for gait rehabilitation that is restricted to the sagittal plane. The exoskeleton that is modelled together with a human lower limb model is subjected to a number of excitations at its joints while performing a joint space trajectory tracking, to investigate the effectiveness of the proposed controller in compensating disturbances. A particle swarm optimised active force control strategy is proposed to facilitate disturbance rejection of a conventional proportional-derivative (PD) control algorithm. The simulation study provides considerable insight into the robustness of the proposed method in attenuating the disturbance effect as compared to the conventional PD counterpart without compromising its tracking performance. The findings from the study further suggest its potential employment on a lower limb exoskeleton.

Constant force control for aluminum wheel hub grinding based on ESO + backstepping

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shijie Dai ◽  
Yufeng Zhao ◽  
Wenbin Ji ◽  
Jiaheng Mu ◽  
Fengbao Hu
Keyword(s):  
Control Strategy ◽  
Force Control ◽  
Control Method ◽  
Response Speed ◽  
Backstepping Control ◽  
Constant Force ◽  
Content Type ◽  
Disturbance Rejection Control ◽  
The Stability ◽  
Differential Control

Purpose This paper aims to present a control method to realize the constant force grinding of automobile wheel hub. Design/methodology/approach A constant force control strategy combined by extended state observer (ESO) and backstepping control is proposed. ESO is used to estimate the total disturbance to improve the anti-interference and stability of the system and Backstepping control is used to improve the response speed of the system. Findings The simulation and grinding experimental results show that, compared with the proportional integral differential control and active disturbance rejection control, the designed controller can improve the dynamic response performance and anti-interference ability of the system and can quickly track the expected force and improve the grinding quality of the hub surface. Originality/value The main contribution of this paper lies in the proposed of a new constant force control strategy, which significantly improved the stability and precision of grinding force.

scholarly journals Knowledge-Based Trajectory Error Pattern Method Applied to an Active Force Control Scheme

1970 ◽  
Vol 3 (1) ◽  
Author(s):  
Endra Pitowarno, Musa Mailah, Hishamuddin Jamaluddin
Keyword(s):  
Force Control ◽  
Error Pattern ◽  
Robot Arm ◽  
Active Force ◽  
Trajectory Error ◽  
Track Error ◽  
Knowledge Based ◽  
Inertia Matrix ◽  
Active Force Control ◽  
Control Scheme

The active force control (AFC) method is known as a robust control scheme that dramatically enhances the performance of a robot arm particularly in compensating the disturbance effects. The main task of the AFC method is to estimate the inertia matrix in the feedback loop to provide the correct (motor) torque required to cancel out these disturbances. Several intelligent control schemes have already been introduced to enhance the estimation methods of acquiring the inertia matrix such as those using neural network, iterative learning and fuzzy logic. In this paper, we propose an alternative scheme called Knowledge-Based Trajectory Error Pattern Method (KBTEPM) to suppress the trajectory track error of the AFC scheme. The knowledge is developed from the trajectory track error characteristic based on the previous experimental results of the crude approximation method. It produces a unique, new and desirable error pattern when a trajectory command is forced. An experimental study was performed using simulation work on the AFC scheme with KBTEPM applied to a two-planar manipulator in which a set of rule-based algorithm is derived. A number of previous AFC schemes are also reviewed as benchmark. The simulation results show that the AFC-KBTEPM scheme successfully reduces the trajectory track error significantly even in the presence of the introduced disturbances.Key Words:  Active force control, estimated inertia matrix, robot arm, trajectory error pattern, knowledge-based.

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