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PENELITIAN INVENSI UDAYANA 2019. Control of Bionic Robot Leg Performance with Proportional Integral and Derivative Controller I Wayan Widhiada, ST, MSc, PhD Prof. Dr.T.G.Tirta Nindhia, S.T., MT I.M.Widiyarta, ST, MSc, PhD Ir. I.N Budiarsa, MT, PhD.

OUTLINE. Introduction Background, Problems. Methodology of Research. Description, Research Procedure and Control Strategy. Result of Research Experiment, Analyze, Discussion. Closing. Conclusion and Massages.

INTRODUCTION.

Introduction. Background. ▸ ▸ ▸. Disability is a general term, which encompasses disruption, activity limitations and restrictions on participation. One example of disability is lower limb disability. in Indonesia, there were 1,167,111 people with disabilities. Prosthetic limbs in Indonesia is still conventional, so users have difficulty and spend a lot of energy to move it. Bionic Robot Leg is an alternative that can be used to replace the anatomic structure of the lower limb with electronic and mechanical components..

Introduction. Background.

Introduction. Formulation of Problems How to design of the Intelligent Control of the Bionic Robot Leg to achieve:. Error ≤ 5% Maximum overshoot ≤ 5% Quickly Response or settling time.

METHODOLOGY OF RESEARCH.

Methodology of Research. Flowchart Diagram Start. Modelling of Hybrid Control Setting Program to Mikrokontroler. 3DDesign Model for Bionic Robot Leg. Export 3D to xml.file in Multybody/Simulnk?. yes Build Prototype. Testing of Motion. No Error ≤ 5% Mp ≤ 5% Ts ≤ 15 dt, SUCSESSl?. yes Taking Eksperiment data. Analyze of Data End. NO.

Methodology of Research. Tools and Materials. Software MATLAB dan Inventor. Arduino Mega 2560. Power Supply. Motor DC.

Methodology of Research Tools and Materials. L298N Motor Driver. Relay. Myoware Muscle Sensor. Potensiometer.

Methodology of Research Procedure of Research 1. Drawing of Bionic Robot Leg in Inventor sotware.

Methodology of Research Procedure of Research 2. Design of Bionic Robot Leg.

Methodology of Research Procedure of Research 3. Electronic Circuit.

Methodology of Research Modelling of Control 4. The Modelling of Control Systems. Simple Control system PID Control System Fuzzy Logic Control System Hybrid Control System Hybrid Control System(Myoware).

Methodology of Research Modelling of Control. Input reference +. CONTROLLER. SERVO MOTOR DC. -. Potensiometer. PLANT BIONIK LEG. Actual Motion.

Methodology of Research Modelling of Control Diagram Blok of a Simple Control.

Methodology of Research. Procedure of Research Auto Tuning of PID control. Parameter Kp = 2 KP Ki = 18 KI Kd = 0.5 KD.

Methodology of Research Procedure of Research Diagram Block of PID control.

Methodology of Research Procedure of Research Diagram Block of Fuzzy Logic control Parameter INPUT :. Parameter OUTPUT :. - nol - Small - Med - Large - XLarge. - nol - Small - Med - Large - XLarge. : [0 0 0] : [0 0,4 0,8 1,2] : [0,6 1,4 2,2] : [1,4 2 2,3] : [2,5 3 5 10]. Rule / aturan : IF (error is nol) then (volt is nol) (1) IF (error is s) then (volt is s) (1) IF (error is m) then (volt is m) (1) IF (error is xl) then (volt is xl) (1). : [10 10 10] : [10 10,5 10,89 11,5] : [10,8 11,6 12,4] : [11,6 12,6 13,3] : [12,75 14 15,5 17].

Methodology of Research Procedure of Research Diagram Block Sistem of Fuzzy Logic control.

Methodology of Research Procedure of Research Diagram Block of Hybrid control. Parameter PID Kp = 2 KP Ki = 18 KI Kd = 0,5 KD. Parameter Fuzzy Logic Parameter INPUT(PID) : - nol : [0 0 0] - Small : [0 45,5 91] - Med : [45,5 91 136,5] - Large : [91 182 273] - XLarge : [227,5 273 364]. Parameter Output(volt) : - nol : [10 10 10] - Small : [10,5 10,8 11 11,5] - Med : [11 11,5 11,9] - Large : [11,6 12,1 12,8] - XLarge : [12,1 12,5 13 14]. Parameter INPUT(error) : - nol : [0 0 0] - Small : [0 0,25 0,5 0,75] - Med : [0,25 0,5 0,75] - Large : [0,5 1 1,5] - XLarge : [1,25 1,5 2 4] Rule / aturan: IF (error is nol) and (PID is nol) then (volt is nol) (1) IF (error is s) and (PID is s) then (volt is s) (1) IF (error is m) and (PID is m) then (volt is m) (1) IF (error is l) and (PID is l) then (volt is l) (1) IF (error is xl) and (PID is xl) then (volt is xl) (1).

Methodology of Research Procedure of Research Diagram Block of Hybrid control.

Methodology of Research Procedure of Research Diagram Block of Hybrid contol using Input from Myoware sensor.

Methodology of Research Procedure of Research 5. Implementation of control system into Microcontroler Arduino AT Mega 2560.

Step Response Curve Setting of Transient-Response. Mp = Maximum Overshoot ts = Settling Time td= delay time Tr= rise time tp=peak time. Error signal= diffrence of input and output. Methodology of Research Analyze of Data.

RESULTS AND DISCUSSION.

Results of Research Experiment A SYMPLE CONTROL Error Signal. Response Transient. Maximum Overshoot. 98,04. Error Mean. 6,606. Mp(%). 17,31. Error Max. 91,07. Settle time (s). 0,714. Error %. 7,25.

Results of Research Experiment PID Control System Error Signal. Response Transient. Maximum Overshoot. 95,36. Error Mean. 3,341. Mp(%). 6,90. Error Max. 90,54. Settle time (s). 0,877. Error %. 3,69.

Results of Research Experiment Fuzzy Logic Control Error Signal. Response Transient. Maximum Overshoot. 91,88. Error Mean. 3,13. Mp(%). 3,31. Error Max. 90,27. Settle time (s). 0,610. Error %. 3,46.

Results of Research Experiment Hybrid Control Error Signal. Response Transient. Maximum Overshoot. 92,14. Error Mean. 2,902. Mp(%). 2,68. Error Max. 91,34. Settle time (s). 0,419. Error %. 3,17.

Results of Research. Analyze and Disscusion. Mp(%). 2 3. Error (%) ts (s). PID. 1. kp ki kd. Simple control. PID. Fuzzy Logic. Hybrid. 17,31 7,25 0,714. 6,90 3,69 0,877. 3,31 3,46 0,610. 2,68 3,17 0,419. Decision maker. Hybrid. Parameter. Fuzzy. No. Combine Mechanism.

Results of Research Experiment System of Hybrid Control with Input Myoware Error Signal. Response Transient. Maximum Overshoot. 92,41. Error Mean. 1,103. Mp(%). 1,47. Error Max. 90,80. Settle time (s). 0,305. Error %. 1,21. Error Mp ts. ≤ 5% ≤ 5% ≤ 0,5.



CLOSING.

Closing. Conclusion. ▸ ▸ ▸. The hybrid control system on the prototype bionic foot was designed with a combination of PID control system and fuzzy logic PID parameters obtained are 2KP, 18KI and 0.5 KD. Fuzzy logic parameters used are input from PID and error with DC motor voltage output In comparative testing, the hybrid control system obtained an error percentage of 3.17%, a maximum overshoot of 2.68%, and a settle time of 0.419s. The parameter values obtained in the hybrid control system testing have met the specified benchmarks.

Closing. Conclusion. ▸. ▸. Prototype performance with a hybrid control system is more accurate, the time needed to reach a reference angle is better and has the most optimal motion compared to other control systems. This is due to the incorporation mechanism as a determinant of the dominant variable to determine the best control signal output The design and implementation of the Hybrid control system on a prototype bionic foot with Myoware input produces optimal motion performance and meets the benchmarks determined with maximum overshoot and error values below 5%, namely 1.47% and 1.21% respectively. The average time needed to reach a stable (settle time) is 0.305s and is a relatively fast time..

Closing Suggestion. ▸ ▸ ▸ ▸. Material selection is recommended to use lighter materials, such as aluminum to reduce the DC motor load. High load DC motors produce L298N components that are easily overheated, so we need components that can withstand DC motor loads. Alternative actuators that can be used are hydraulic actuators to produce a large force or torque and have a high response. Collaboration with physiologists to determine the location of myoware sensors.

Thank You.

39. Outcomes of Research 1. Prototype.

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