Hybrid fuzzy- proportionl integral derivative controller (F-PID-C) for control of speed brushless direct curren motor (BLDCM)

Hybrid Fuzzy proportional-integral-derivative (PID) controllers (F-PID-C) is designed and analyzed for controlling speed of brushless DC (BLDC) motor. A simulation investigation of the controller for controlling the speed of BLDC motors is performed to beat the presence of nonlinearities and uncertainties in the system. The fuzzy logic controller (FLC) is designed according to fuzzy rules so that the systems are fundamentally robust. There are 49 fuzzy rules for each parameter of FUZZY-PID controller. Fuzzy Logic is used to tune each parameter of the proportional, integral and derivative ( kp,ki,kd) gains, respectively of the PID controller. The FLC has two inputs i.e., i) the motor speed error between the reference and actual speed and ii) the change in speed of error (rate of change error). The three outputs of the FLC are the proportional gain, kp, integral gain ki and derivative gain kd, gains to be used as the parameters of PID controller in order to control the speed of the BLDC motor. Various types of membership functions have been used in this project i.e., gaussian, trapezoidal and triangular are assessed in the fuzzy control and these membership functions are used in FUZZY PID for comparative analysis. The membership functions and the rules have been defined using fuzzy system editor given in MATLAB. Two distinct situations are simulated, which are start response, step response with load and without load. The FUZZY-PID controller has been tuned by trial and error and performance parameters are rise time, settling time and overshoot. The findings show that the trapezoidal membership function give good results of short rise time, fast settling time and minimum overshoot compared to others for speed control of the BLDC motor

SISTEM KENDALI ADAPTIF NEURO-FUZZY PID PADA KAPAL KATAMARAN TANPA AWAK

Kendali otomatis dibutuhkan oleh kapal katamaran tanpa awak dalam menavigasi menuju arah tertentu dan dapat menangani gangguan serta perubahan kondisi dengan efektif dan optimal. Kendali PID cocok untuk pengendalian kapal, namun mempunyai kelemahan dalam pencarian gain PID optimal untuk setiap kondisi. Fuzzy mampu menangani penjadawalan gain PID untuk setiap kondisi dan neural network mampu mengoptimasi desain fuzzy, sehinggadilakukan penggabungan menjadi kendali adaptif neuro fuzzy PID (N-F PID). N-F PID merupakan kendali PID dengan penjadawalan gain PID (Kp, Ki dan Kd) yang dinamis berdasarkan besarnya nilai error dan delta error oleh neuro fuzzy. Neuro fuzzy yang digunakan adalah adaptif neuro fuzzy inference system (ANFIS). ANFIS mampu melakukan pembelajaran dengan training data baru untuk memperbaiki performa. Training data baru didapatkan dari proses tuning dengan mengalikan output masing-masing fuzzy yang belum terlatih dengan konstanta tertentu hingga didapatkan settling time cepat dan persentase overshoot maksimum kecil.Simulasi N-F PID dengan Matlab dan ekperimen kapal katamaran menunjukkan N-F PID mempunyai performa yang lebih baik dari pada kendali fuzzy PID dan kendali PID, dilihat dari settling time dan persentase overshoot maksimum. N-F PID mempunyai tingkat presisi pengendalian yang lebih rendah daripada kendali fuzzy PID dan PID berdasarkan data eksperimen

Semi-active vibration control using experimental model of magnetorheological damper with adaptive F-PID controller

The aim of this research is to develop a new method to use magnetorheological (MR) damper for vibration control. It is a new way to achieve the MR damper response without the need to have detailed constant parameters estimations. The methodology adopted in designing the control structure in this work is based on the experimental results. In order to investigate and understand the behaviour of an MR damper, an experiment is first conducted. Force-displacement and force-velocity responses with varying current have been established to model the MR damper. The force for upward and downward motions of the damper piston is found to be increasing with current and velocity. In cyclic motion, which is the combination of upward and downward motions of the piston, the force with hysteresis behaviour is seen to be increasing with current. In addition, the energy dissipated is also found to be linear with current. A proportional-integral-derivative (PID) controller, based on the established characteristics for a quarter car suspension model, has been adapted in this study. A fuzzy rule based PID controller (F-PID) is opted to achieve better response for a varying frequency input. The outcome of this study can be used in the modelling of MR damper and applied to control engineering. Moreover, the identified behaviour can help in further development of the MR damper technology

Analisis Kinerja Penggabungan Logika Fuzzy dan PID pada Penjejak Matahari Dua Sumbu

Utilization of renewable energy from solar panel systems is increasingly being applied, but until now its utilization has not been maximized. The movement of the sun caused by rotation of the earth and cloudy condition should be taken into account to maximize the electrical energy in solar panels. In this study, a concept to calculate the movement of a two-axis sun tracker is proposed by using a combination of two controller methods, i.e. Proportional Integral Derivative (PID) and Fuzzy logic known as Fuzzy-PID (F-PID). To follow the movement of the sun, the LDR sensor is used as an input to light as well as output used to drive 2 units servo for x-axis and y-axis. Sun tracker that is used is based on tetrahedron geometry and uses three Light Dependent Resistor (LDR) sensors as input. Input and output components are connected to the Atmega 328P by using a combination of Fuzzy logic and PID programs (F-PID). Fuzzy logic programming is first performed on the Matlab application using Fuzzy Inference System (FIS), then converted into an Arduino-based programming language. The sun tracker movement and the voltage received by the solar panel will be stored into the SD card using a data logging module. Adjusting the sun tracker movement using the combined Fuzzy logic and PID method intends to maximize the electrical energy received by the solar panel. The results showed that the F-PID method obtained the maximum voltage of 5.3 V, a maximum current of 0.11 A, and a maximum power of 0.61 W

Fuzzy tuned PID controller for envisioned agricultural manipulator

The implementation of image-based phenotyping systems has become an important aspect of crop and plant science research which has shown tremendous growth over the years. Accurate determination of features using images requires stable imaging and very precise processing. By installing a camera on a mechanical arm driven by motor, the maintenance of accuracy and stability becomes non-trivial. As per the state-of-the-art, the issue of external camera shake incurred due to vibration is a great concern in capturing accurate images, which may be induced by the driving motor of the manipulator. So, there is a requirement for a stable active controller for sufficient vibration attenuation of the manipulator. However, there are very few reports in agricultural practices which use control algorithms. Although, many control strategies have been utilized to control the vibration in manipulators associated to various applications, no control strategy with validated stability has been provided to control the vibration in such envisioned agricultural manipulator with simple low-cost hardware devices with the compensation of non-linearities. So, in this work, the combination of proportional-integral-differential (PID) control with type-2 fuzzy logic (T2-F-PID) is implemented for vibration control. The validation of the controller stability using Lyapunov analysis is established. A torsional actuator (TA) is applied for mitigating torsional vibration, which is a new contribution in the area of agricultural manipulators. Also, to prove the effectiveness of the controller, the vibration attenuation results with T2-F-PID is compared with conventional PD/PID controllers, and a type-1 fuzzy PID (T1-F-PID) controller

Intelligent approach to Force/Position Control of Ultrasound-Guided Breast Biopsy Robotic System

Large deformations occur inside the breast whenever the biopsy needle is inserted during conventional ultrasound-guided breast biopsy procedure. Inconsistent force from manual handling of the ultrasound transducer makes maintaining the suspected lump in the ultrasound-imaging region challenging and further position the patient at discomfort. Hence, this research presents the development of force controller for an ultrasound-guided breast biopsy (UGBB) robotic system in the aims to alleviate said issues by maintaining low contact force on the breast. A variant of force controllers has been studied; proportional (P), proportional and integral (PI), PID, PI-Fuzzy, Fuzzy-PID (F-PID), and Fuzzy-PID using Lookup Table (F-LUT) controllers. Effect of external disturbance such as subject respiration is considered to see the reliability of each developed force/position control system. Based on the simulation results, F-PID force controller shows promising outcome with a marginal error of 0.33% during the disturbance period and no error when the disturbance is absent

Hybrid fuzzy-proportionl integral derivative controller (F-PID-C) for control of speed brushless direct current motor (BLDCM)

Hybrid Fuzzy proportional-integral-derivative (PID) controllers (F-PID-C) is designed and analyzed for controlling speed of brushless DC (BLDC) motor. A simulation investigation of the controller for controlling the speed of BLDC motors is performed to beat the presence of nonlinearities and uncertainties in the system. The fuzzy logic controller (FLC) is designed according to fuzzy rules so that the systems are fundamentally robust. There are 49 fuzzy rules for each parameter of FUZZY-PID controller. Fuzzy Logic is used to tune each parameter of the proportional, integral and derivative ( kp,ki,kd) gains, respectively of the PID controller. The FLC has two inputs i.e., i) the motor speed error between the reference and actual speed and ii) the change in speed of error (rate of change error). The three outputs of the FLC are the proportional gain, kp, integral gain ki and derivative gain kd, gains to be used as the parameters of PID controller in order to control the speed of the BLDC motor. Various types of membership functions have been used in this project i.e., gaussian, trapezoidal and triangular are assessed in the fuzzy control and these membership functions are used in FUZZY PID for comparative analysis. The membership functions and the rules have been defined using fuzzy system editor given in MATLAB. Two distinct situations are simulated, which are start response, step response with load and without load. The FUZZY-PID controller has been tuned by trial and error and performance parameters are rise time, settling time and overshoot. The findings show that the trapezoidal membership function give good results of short rise time, fast settling time and minimum overshoot compared to others for speed control of the BLDC motor

Penguin diagrams for the HYP staggered fermions

We present results of the one-loop corrections originating from the penguin diagrams for the improved staggered fermion operators constructed using various fat links such as Fat7, Fat7+Lepage, $\bar{\rm Fat7}$, HYP (I) and HYP (II). The main results include the diagonal/off-diagonal mixing coefficients and the matching formula between the continuum and lattice operators.Comment: 4 figures, Contribution to Lattice 200

Migration, labor tasks and production structure

We assess the effect of migrants’ stock on the production structure of the Italian provinces (NUTS3) in 1995–2006. Although the investigated time span is very short, the effect is small but statistically significant: a doubling in the ratio of foreign-born residents to the province population induces a significant increase in manufactures’ value added with respect to services’ value added between 12 and 21 per cent. These effects are more intense when considering an increase in foreign-born populations drawn from countries more different to Italy (in terms of GDP per capita and educational attainment). These results are compatible with the reduced form of a two-sector model where we assume that production is performed with one mobile factor and two sector-specific CES labor composites of simple and complex tasks. If migrants and natives have different productivity when performing simple or complex tasks, an inflow of migrants induces production restructuring in favor of the simple-task intensive sector