Adha Imam Cahyadi

Bio: Adha Imam Cahyadi is an academic researcher from Gadjah Mada University. The author has contributed to research in topics: Battery (electricity) & Control theory. The author has an hindex of 13, co-authored 113 publications receiving 607 citations. Previous affiliations of Adha Imam Cahyadi include Tokai University & Information Technology University.

State of Charge (SOC) and State of Health (SOH) estimation on lithium polymer battery via Kalman filter

Abstract: To avoid battery failure and keep the battery lifetime, a system needs control its use by considering two of several parameters of Battery Management System (BMS) such as State of Charge (SOH) and State of Health (SOH). The State of Charge in Battery Management System provides the percentage of battery capacity, while the State Of Health measures the battery health. The Thevenin battery model is used to describe polarization characteristic and dynamic behavior of the battery and estimared using KalmanFilter(KF). Parameters in the model were estimated using Recursive Least Square. As the results, KF is better then RLS to estimate SOH with a mean relative error as much as 5.26% while RLS has 7.08%.

UAV obstacle avoidance using potential field under dynamic environment

Abstract: In this paper, the potential field principle is applied to several UAVs (Unmanned Aerial Vehicles) for optimal path planning. Each UAV has its own goals and it is used the attractive potential field to reach the goals. On the contrary, each UAV is considered as obstacle for other UAVs that must be avoided. In this research, there are two types of obstacles, i.e the static and dynamic. The repulsive potential field principle is used to avoid for both static and dynamic obstacles. The whole method is implemented into Parrot AR Drone 2.0 Quadcopter model of UAV and simulated in Gazebo Simulator by Robot Operating System (ROS). The results of this research are to control the thrust of quadcopter so that it is in flying position, the value of value of roll (α) or pitch (β) must set to not equal or approaching 90° or −90° and not between −180° and 180° or between −90° and 90°. Based on the dynamic obstacle performance test with parameter tuning, the optimal avoidance is when the η value is 7.8 while when in static and dynamic test with parameter tuning, the optimal avoidance is when the η value is 7.9 noted by the fastest time and the shortest path.

Comparison of State-of-Charge (SOC) estimation performance based on three popular methods: Coulomb counting, open circuit voltage, and Kalman filter

Abstract: In this research, three battery models are proposed, i.e., simple battery model, Thevenin battery model, and modified Thevenin battery model. State-of-Charge (SOC) estimation based on those battery models are conducted with coulomb counting, open circuit voltage, and Kalman Filter. Simulation about false on battery capacity initialization is tested over the battery. The results show that the proposed battery modeling can accurately provide SOC estimation. On the simulation of false initialization, SOC estimation method with coulomb counting, open circuit voltage model 1 and 2 methods cannot track the true value, while Kalman Filter method can accurately provide SOC estimation and is able to correct false SOC initialization in short time.

Controllability and observability analysis of the gain scheduling based linearization for UAV quadrotor

Abstract: This paper presents the gain scheduling based linearization of simplified quadrotor non-linear model as well as the test for the system controllability and observability for various equilibrium point. The simplified non-linear model of quadrotor is linearized at some equilibrium points to get the linear state equation. Then, the controllability and observability test is done to the linearized model for various equilibrium points. The system behavior is then tested by using the state feedback controller to confirm the result.

Quadrotor Path Planning Based on Modified Fuzzy Cell Decomposition Algorithm

Abstract: The purpose of this paper is to present an algorithm to determine the shortest path for quadrotor to be able to navigate in an unknown area. The problem in robot navigation is that a robot has incapability of finding the shortest path while moving to the goal position and avoiding obstacles. Hence, a modification of several algorithms are proposed to enable the robot to reach the goal position through the shortest path. The algorithms used are fuzzy logic and cell decomposition algorithms, in which the fuzzy algorithm which is an artificial intelligence algorithm is used for robot path planning and cell decomposition algorithm is used to create a map for the robot path, but the merger of these two algorithms is still incapable of finding the shortest distance. Therefore, this paper describes a modification of the both algorithms by adding potential field algorithm that is used to provide weight values on the map in order for the quadrotor to move to its goal position and find the shortest path. The modification of the algorithms have shown that quadrotor is able to avoid various obstacles and find the shortest path so that the time required to get to the goal position is more rapid.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Coverage control for mobile sensing networks

Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Numerical methods for engineers

Abstract: The fifth edition of "Numerical Methods for Engineers" continues its tradition of excellence. Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clear explanations and examples throughout. The text features a broad array of applications, including all engineering disciplines. The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containing sections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Approximately 80% of the end-of-chapter problems are revised or new to this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering. Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros.

Adaptive Sliding-Mode Control for NonlinearSystems With Uncertain Parameters

Abstract: This correspondence proposes a systematic adaptive sliding- mode controller design for the robust control of nonlinear systems with uncertain parameters. An adaptation tuning approach without high- frequency switching is developed to deal with unknown but bounded system uncertainties. Tracking performance is guaranteed. System robustness, as well as stability, is proven by using the Lyapunov theory. The upper bounds of uncertainties are not required to be known in advance. Therefore, the proposed method can be effectively implemented. Experimental results demonstrate the effectiveness of the proposed control method.