Tóm tắt nghiên cứu điều khiển robot phục hồi chức năng chi dưới sử dụng cơ nhân tạo

Tóm tắt nghiên cứu điều khiển robot phục hồi chức năng chi dưới sử dụng cơ nhân tạo Tóm tắt nghiên cứu điều khiển robot phục hồi chức năng chi dưới sử dụng cơ nhân tạo Tóm tắt nghiên cứu điều khiển robot phục hồi chức năng chi dưới sử dụng cơ nhân tạo Tóm tắt nghiên cứu điều khiển robot phục hồi chức năng chi dưới sử dụng cơ nhân tạo Tóm tắt nghiên cứu điều khiển robot phục hồi chức năng chi dưới sử dụng cơ nhân tạo

MINISTRY OF EDUCATION AND TRAINING

HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY

Dinh Van Vuong

STUDY ON CONTROL OF A PAM-BASED

LOWER-LIMB REHABILITATION ROBOT

Majors: Control Engineering And Automation

Code: 9520216

SUMMARY OF DOCTOR DISSERTATION ON CONTROL

ENGINEERING AND AUTOMATION

Ha Noi - 2024

The Dissertation was completed at:

Hanoi University Of Science And Technology

SUPERVISOR

1 Assoc.Prof.Dr Duong Minh Duc

2 Dr Dao Quy Thinh

At …… hour, day … month … year ………

The Dissertation can be found at the library:

1 Ta Quang Buu Library - Hanoi University of Science and Technology

2 Vietnam National Library

Abstract

1 The necessity of the Dissertation

Nowadays, rehabilitation robot systems are being researched and developed worldwide to replace physical therapists gradually Robots can assist patients systematically in performing preprogrammed rehabilitation exercises At the same time, robots can assist with long-term training without getting tired However, as robots interact directly with humans, safety is always a top priority in designing and controlling rehabilitation robots In addition, the robot's actuators must also be flexibly controlled to make patients feel most comfortable during training and avoid causing injury to the patient Recently, the rehabilitation system using pneumatic artificial muscles has attracted much attention from researchers due to the similarity between PAM and human muscles The PAM is lightweight and has a higher power-to-weight ratio than motorized transmission devices Moreover, PAM is quite flexible and suitable for robots that interact with humans, such as rehabilitation robots Several prototype systems of rehabilitation robots have been developed at research centres worldwide But, most of the above systems are still in the early stages of development In summary, all rehabilitation robot systems that use pneumatic artificial muscles domestically and internationally are only currently in the laboratory and have not been commercialized So, the potential for research and development is enormous Based on this reality, we have chosen the

topic of "Study on Control of a PAM-based Lower-limb Rehabilitation

Robot"

2 Purpose of the research

The purpose of this Dissertation focuses on control lower-limb robotic orthosis:

3 Objectives and scope of research

a Research objective

The research objective is the BK-Gait 2-DOF robotic orthosis that covers hip and knee joints The robotic orthosis is actuated by pneumatic artificial muscles in an antagonistic configuration

b Scope of research

The research scope of this Dissertation focuses only on the study of controlled lower-limb robotic orthosis Therefore, the research project will be performed based on theoretical foundations and experiments:

• The model parameters are collected based on the pneumatic artificial muscle (PAM) with the antagonistic configuration of the BK-Gait 2-DOF robotic orthosis

• All measurements, control algorithms, and experimental results are performed and verified by experiments on the lower-limb rehabilitation robot model (BK-Gait) at Hanoi University of Science and Technology

• Control algorithms will be applied to build trajectory-tracking and impedance controllers for all actuators and robots Then, it will be programmed on suitable controllers such as National Instrument's MyRio The control performance will be verified through experimental results

The proposed controllers will be performed through experiments with the fabricated robot

5 The scientific and practical significance of the Dissertation

a Scientific significance

The scientific significance of this Dissertation is to build tracking control and impedance control algorithms for actuators and robot systems using PAM-based actuators that are accurate and suitable for rehabilitation applications

trajectory-b Practical significance

The practical significance of this Dissertation is to build a rehabilitation system for the human lower limb with trajectory tracking and impedance control functions with good precision and applicability

to rehabilitation systems in practice

6 Structure of the Dissertation

The Dissertation is structured into Chapters and a conclusion as follows:

• Chapter 1 Overview of the Rehabilitation Systems: This

Chapter provides an overview of the rehabilitation robot system

It highlights that the global research and development efforts in rehabilitation robots are substantial due to their notable advantages over traditional rehabilitation methods However, most research on robotic rehabilitation systems using artificial muscles is limited to the laboratory and has not been commercialized This indicates a significant potential for further research and development in the field

• Chapter 2 Modeling and Control of PAMs: This Chapter

overviews pneumatic artificial muscles and the popular methods for modeling artificial muscles After that, we built a mathematical model for a PAM-based actuator Finally, we will apply advanced control algorithms to build a trajectory-tracking controller for a PAM-based actuator Multiple experiment scenarios will be performed to verify the effectiveness of these controllers

• Chapter 3 Trajectory Tracking Control of the BK-Gait

Orthosis: This Chapter focuses on improving the control system

for the BK-Gait lower limb robotic orthosis Firstly, we will build a mathematical model for the BK-Gait lower limb robotic orthosis Next, we will apply advanced control algorithms to build a trajectory-tracking controller for BK-Gait lower limb robotic orthosis Finally, multiple experiment scenarios will be performed to verify the effectiveness of the built controller

• Chapter 4 Impedance Control of the BK-Gait Orthosis: In this

Chapter, a neural network-based method is chosen to estimate the patient's recovery, an essential factor for a gait training robot system powered by pneumatic artificial muscles The estimated patient recovery will be used as the control signal for the impedance controller to improve joint compliance coefficients

• Conclusions and Recommendations: This section summarizes

the results achieved in the thesis, the main contributions, and proposes future research directions

7 The Contributions of the Dissertation

This study mainly presents the control algorithms for a low-limb rehabilitation system by combining theoretical research and experimental verification The main contributions of the Dissertation:

• Building a two-degree-of-freedom pneumatic artificial based exoskeleton robot for the human's lower-limb rehabilitation

muscle-• Developing trajectory tracking control function for a prototype robot by employing some advanced control strategies

• Integrating an impedance control function into a robot by using neural networks to approximate the interaction force of humans

to the robot

Chapter 1 Overview of the Rehabilitation Systems

1.1 Motorized Lower-Limb Rehabilitation Orthosis Systems

The Driven Gait Orthosis (DGO), also known as LOKOMAT (Hocoma

AG, Volketswill Switzerland), is currently available in the market and is extensively researched in many rehabilitation centres as one of the best examples for gait orthosis that can be used for lower-limb disabilities This orthosis system is shown in Figure 1.1a It consists of three main parts: body weight support, treadmill, and powered leg orthosis Considerable control algorithms have been implemented into this system to improve its performance, such as position, adaptability,

impedance controllers, etc Figure 1.1b shows the treadmill gait trainer system, which incorporated the electromechanical gait device with the treadmill/gait training, known as the LokoHelp (LokoHelp Group, Germany) The LokoHelp used a different mechanical system than the LOKOMAT, which implemented the powered leg orthosis The foot-powered orthosis, "Pedago'', used an electromechanical gait device to provide a gait motion during training sessions The control device helps move the patients' foot trajectory with a fixed step length of 400 mm, in which the gait cycle (GC) speed can be varied from 0 to 5 km/h The ReoAmbulator robotic system (Motorika Ltd, USA), which is also known as "AutoAmbulato'', is another example of existing treadmill gait trainers for lower-limb rehabilitation therapy, as shown in Figure 1.1c This system has been used in research centers and medical hospitals for rehabilitation therapies and educational research studies

Figure 1.1 (a) LOKOMAT, (b) LokoHelp, (c) ReoAmbulator

The evaluated motorized lower-limb gait rehabilitation orthosis systems mentioned above represent only a fraction of the existing rehabilitation orthoses However, it could be summarized from these examples that its development has advanced, whereby many lower-limb gait rehabilitation orthoses based on electrical motors have already been commercialized With its growth speed in mechanical design and the implementation of advanced control schemes and strategies, the space available for enhancements might closely reach its peak

1.2 Pneumatic Muscle Actuated Lower-limb Rehabilitation Orthosis Systems

Figure 1.4 (a) The hip orthosis, (b) The ankle orthosis, (c) The ankle

orthosis AFO

Recently, a natural and low-cost actuator PAM has been widely implemented in developing rehabilitation systems Compared with conventional actuators such as electrical motors, series elastic actuators (SEA), and brushless DC motors, PAM has many advantages, including being naturally compliant, lightweight, and having a high weight ratio to power Despite inherent drawbacks such as very high nonlinear and uncertain characteristics and slow response in force generation, the applications of PAM in robotic rehabilitation fields are exponentially growing due to the demand on much high compliant human-robotic systems The first robotic orthosis actuated by PAM was developed by Claysson B Vimieiro et al in 2004 for supporting the hip flexion movement of patients As shown in Figure 1.4, this exoskeleton is designed with two main parts: the first one is a pelvic brace to provide the stability of the robot, and the second one is support for the thigh The clinical results showed that the exoskeleton was able to provide not only more stabilization but also a better condition for the patients during walking activity

In summary, it can be seen that the rehabilitation robot system is being heavily researched and developed worldwide because of its outstanding advantages compared to traditional rehabilitation methods Robots can

assist patients systematically in performing rehabilitation exercises that have been preprogrammed Several prototype systems of rehabilitation robots have been developed at research centers worldwide However, most of the above systems are still in the early stages of development The "assist-as-needed'' (AAN) function is indispensable for a rehabilitation robot to restore patient function Therefore, a rehabilitation robot must have sufficient rigidity to guide the patient's limb along the designated trajectory and estimate the patient's level of disability to provide the necessary support

1.3 The BK-Gait lower-limb rehabilitation system

Figure 1.9 The BK-Gait lower-limb rehabilitation system

Figure 1.9 demonstrate the schematic diagram of the BK-Gait rehabilitation system The overall rehabilitation system includes the following parts:

• Part 1 is the Body Weight Support

• Part 2 is a treadmill (walking assist device)

• Part 3 is the development of sample physical therapy exercises

• Part 4 is the Robot Orthosis

The research scope of this Dissertation only focuses on the study of control lower-limb robotic orthosis Therefore, the research project will

be performed based on theoretical foundations and experiments However, there are two control problems for lower limb rehabilitation robots: trajectory tracking and impedance control problems The aim of the Dissertation is to apply some advanced control algorithms to build controllers to solve the above two control problems

1.4 The experimental system

The experimental models built within the research scope of this Dissertation all use pneumatic artificial muscles (PAM) as actuators There are many types of artificial muscles, as shown in Figure 2.1 of Section 2.1.1 However, this study will use the McKibben muscle due to lightweight, easy to fabricate with low cost, high power/weight ratio, and similar to the behavior of human muscle Although the McKibben mechanism is also commercialized on the market But it is very expensive Therefore, in this study, the McKibben muscles will be made manually with available materials and low cost

1.4.1 The experimental model for a PAM-based actuator

Figure 1.16 The experimental model for a PAM-based actuator

The experimental platform consists of two self-made PAMs, as shown

in Figure 1.16, each 25 mm in diameter and 400 mm in length, arranged

in an antagonistic configuration Two proportional electric control valves regulate the internal pressure of the PAMs The deflection angle

of the pulley is measured using an angle sensor (WDD35D5T) with a precision of 1% The control platform comprises an embedded controller (National Instrument myRIO-1900) that can be monitored and interact with the field devices using LabVIEW software This experimental model will verify the control performance of the algorithms implemented in Chapter 2

1.4.2 The experimental model for the BK-Gait lower-limb robotic orthosis

This research considers a BK-Gait-based lower limb rehabilitation system for the experimental works The system's main advantage is the suspension frame's direct attachment to the pre-shaped aluminum, which

fixes the robot and lifts the patient to the desired height The prototype robot is a 2-DOF robot, which drives the lower limb of the subject with the help of two aluminum braces attached to the thigh and shank parts The length of the robot's links can be adjusted based on the subject's body using the slider between the hip and knee joints The hip and knee joints can flex/extend to a maximum angle of −450/ + 450 and 00/900, respectively The system's design allows for a customizable and effective rehabilitation experience for lower limb patients The developed robotic exoskeleton system is depicted in the actual image shown in Figure 1.17 This experimental model will verify the control performance of the algorithms implemented in Chapter 3, 4

Figure 1.17 The experimental model for the BK-Gait lower-limb robotic

orthosis

Chapter 2 Modeling and Control of PAMs

2.1 The mathematical model for a pair of pneumatic artificial muscles with an antagonistic configuration

To construct the mathematical of model two PAMs in an antagonistic,

as shown in Figure 1.16 we start by analyzing the mathematical model

of a single muscle, as in reference [73] Figure 2.8 illustrates the working principle of the configuration Initially, both PAMs have equal pressure, resulting in the same level of contraction x0 and the initial angle of the pulley as θ0 = 00 By applying a pressure difference ΔP, where one PAM is pressurized while the other is depressurized, the

lengths of the two PAMs will differ, causing the pulley to rotate and resulting in a change in joint angle θ The following equation can determine the pressures applied to the PAMs:

Figure 2.8 The working principle of an antagonistic configuration

0 0

Consequently, the system's dynamic behavior can be characterized by the following equation:

In this subsection, the design of the ASMC is described Firstly, the SMC controller is designed based on the sliding surface theory The system's uncertainty disturbance component is then estimated using an adaptive law-based noise observer Figure 2.11 illustrates the block diagram of the overall system

Figure 2.11 Block diagram of proposed control approach

The control signal 𝑢𝑘 can be follow as:

Component 𝑝𝑘 in 𝑢𝑘 is a variable of the unknown system disturbance

As a result, we propose in this section an observer that uses adaptive law

to estimate that component Thereby improving the efficiency of the sliding mode controller Finally, with the estimated value 𝑝̂𝑘 of 𝑝𝑘, the control signal 𝑢𝑘 is calculated as:

Figure 2.18 RBF Neural network-based control diagram

The control signal is:

1

1( ) d T

Figure 2.19 Diagram of an RBF neural network

From the previous part, the unknown nonlinear function 𝑔𝑥 the RBF neural network has represented The control signal is:

1

1ˆ( ) T

d

u g x y

