Edi Leksono

Design and Implementation of Paired Pectoral Fins Locomotion of Labriform Fish Applied to a Fish Robot

In present, there are increasing interests in the research on mechanical and control system of underwater vehicles. These ongoing research efforts are motivated by more pervasive applications of such vehicles including seabed oil and gas explorations, scientific deep ocean surveys, military purposes, ecological and water environmental studies, and also entertainments. However, the performance of underwater vehicles with screw type propellers is not prospective in terms of its efficiency and maneuverability. The main weaknesses of this kind of propellers are the production of vortices and sudden generation of thrust forces which make the control of the position and motion difficult.On the other hand, fishes and other aquatic animals are efficient swimmers, posses high maneuverability, are able to follow trajectories, can efficiently stabilize themselves in currents and surges, create less wakes than currently used underwater vehicle, and also have a noiseless propulsion. The fish’s locomotion mechanism is mainly controlled by its caudal fin and paired pectoral fins. They are classified into Body and/or Caudal Fin (BCF) and Median and/or paired Pectoral Fins (MPF). The study of highly efficient swimming mechanisms of fish can inspire a better underwater vehicles thruster design and its mechanism.There are few studies on underwater vehicles or fish robots using paired pectoral fins as thruster. The work presented in this paper represents a contribution in this area covering study, design and implementation of locomotion mechanisms of paired pectoral fins in a fish robot. The performance and viability of the biomimetic method for underwater vehicles are highlighted through in-water experiment of a robotic fish.

Adaptive backstepping for stabilization of switched nonlinear systems

This paper considers the problem of adaptive stabilization of a class of switched nonlinear systems with constant unknown parameters. The proposed method is based on the combination of the nonlinear adaptive stabilization technique and common control Lyapunov function (CCLF) concept. We adopted the adaptive backstepping technique to present the implementation of the proposed method for switched nonlinear system in parametric-strict-feedback form.

Development of battery management system for cell monitoring and protection

Battery has an important role as energy storage in electricity system utilization such as in electric vehicle and in smart microgrid system. Battery Management System (BMS) is needed to treat the dynamics of energy storage process in the battery in order to improve the performance and extend the life time of battery. In this paper, BMS cell monitoring and protection has been designed and tested for Lithium Ferro Phosphate (LFP) battery cells. The BMS cell monitoring function has been able to measure the battery parameters such as the voltage and current dynamics of each cell. The data taken from the BMS cell monitoring experiment is used to estimate the state of charge (SOC) of battery which is based on coulomb counting with coulomb efficiency ratios. The BMS cell monitoring function has successfully demonstrated the presence of unbalanced cell voltages during both processes of charging and discharging as well. From the analysis, the existence of capacity and energy fades was also investigated for every discharging and charging cycles. Based on the BMS cell protection experiment results, overcharged and over discharged protections have successfully been demonstrated for the battery cells. The charging process is disabled when the voltage of the corresponding battery cell exceeds its high limit (HLIM) at 3.65V, and the battery will be available for charging when all of the cell voltages are below their boundary limits (CAVL) at 3.3V. The discharging process will be disabled when the battery cell voltage is lower than the corresponding low limit (LLIM) at 2.5 V. The battery will be available again when all battery cell voltages are above their discharge available (DAVL) voltage at 2.8V. The proposed BMS cell monitoring and protection has shown its function as a data acquisition system, safety protection, ability to determine and predict the state of charge of the battery, and ability to control the battery charging and discharging.

Wireless sensor network for single phase electricity monitoring system via Zigbee protocol

Development of audit and energy management system in the industrial automation and intelligent building installation has been observed over many years. Electrical energy monitoring system is now using real-time measurement facility via wireless network applications. In this paper we consider an application of star topology wireless sensor network for single phase electricity monitoring system based on Energy Meter IC ADE7753. Zigbee is used as wireless protocol. It has many benefits such as low cost, low power, low data rate, and supports on mesh-networking IEEE 802.15.4. For web-server monitoring system, Ext-JS framework is used as client-side programming which is integrated with IDE Arduino. Statistically, for sample of 30 data measurement, it is shown that current measurement gave guarantee of accuracy value until 5.3μArms with average precision error of 0.03%, and voltage measurement gave guarantee of accuracy value until 226.5μVrms with average precision error of 1.23%. Effectively, data measurement occurs in the intervals of 10 seconds and a transmission maximum of 40 meters with barrier and 60 meters without barrier.

Optimization of a grid-tied microgrid configuration using dual storage systems

This paper presents optimization in capacity sizing and operational schedule for a grid-tied microgrid using dual storage systems. Photovoltaic power system is used as a renewable energy source. Pumped-storage hydroelectricity and battery energy storage system are utilized as energy storage systems. The physical models of the photovoltaic system, pumped-storage hydroelectricity, and battery energy storage system are developed. The objective function is formulated to minimize capital and operational costs of grid-tied microgrid system. The constraints for the optimization are formulated based on the system model, operational limitations, and performance requirements. Capacity and operational schedule for the microgrid system is optimized using solar insolation data and load demand data. Performances required for microgrid system are high renewable energy penetration with low curtailed renewable energy. Mixed integer linear programming (MILP) is used to solve the optimization problem. With the proposed method, renewable energy penetration ratio achieves 50%. The curtailed renewable energy ratio of 10.4% is obtained.

Performance analysis of PID controller, fuzzy and ANFIS in pasteurization process

Pasteurization engine uses a heat exchanger to heat the milk up to 71.6 °C. Therefore, the suitable type of controller for pasteurization process must be obtained. In this paper, there are five types of controller to be compared. These controllers are a PID controller tuning Ziegler Nichols, PID tuning Cohen Coon, Cascade PID, Fuzzy Inference System and Adapative Neuro Fuzzy Inference System (ANFIS). The system is also got disturbances that is caused by changes in flow of the product and changes of a step and impulse input for the system. This controller is created in MATLAB, which is connected to the PLC using OPC. The output of MATLAB will determine the control signals which serve as an input for the heater. It is shown from the data that the system that is controlled using ANFIS has an overshoot is only 0.27 percent, which is the smallest overshoot compared to other controllers. The required power for heater is only 0.48 kW which is the smallest one compare to other controllers. The MSE (mean squared error) value after the rise time had been reached is 0.114. The MSE when the system is given the flow disturbance is 1.86. When the systems step input is changed, the system that is controlled by ANFIS has a smaller overshoot and MSE compared to when the system is being controlled by PID cascade. However, when exposed to impulse disturbance ANFIS system controlled is highly reactive and has a lower performance than PID Cascade. Overall, it can be concluded that the performance of the ANFIS controller is better compare to other controllers.

State of charge (SoC) estimation of LiFePO4 battery module using support vector regression

In this research work, we demonstrate state-of-charge (SoC) estimation using support vector regression (SVR) approach for a high capacity Lithium Ferro Phosphate (LiFePO4) battery module. The proposed SoC estimator in this work is extracted from open circuit voltage (OCV)-SoC lookup table which is obtained from the battery module discharging and charging testing cycles, using voltage and current as independent variables. The SoC estimation based on SVR gives a perfectly linear curve fitting with its reference within the range of 37.5% to 90% while the rest hysteresis due to the discharging and charging process is compensated using OCV-SoC curve as the training data set. The SVR estimates the battery module SoC with RMSE of 2.3% over the whole test and the maximum positive and negative error is 4%, which means that it shows good accuracy.