239 citations · 1.1k across the 21 of their papers we have counts for
23 papers
Stability Boundaries and Motor Performance in Delayed Robot-Mediated Dyadic Interactions
Mingtian Du, Suhas Raghavendra Kulkarni, Simone Kager +2
This paper establishes analytical stability boundaries for robot-mediated human-human (dyadic) interaction systems, subject to haptic communication under network-induced time delay…
Data-Based MHE for Agile Quadrotor Flight
Wonoo Choo, Erkan Kayacan
This paper develops a data-based moving horizon estimation (MHE) method for agile quadrotors. Accurate state estimation of the system is paramount for precise trajectory control fo…
Computationally Efficient Data-Driven MPC for Agile Quadrotor Flight
Wonoo Choo, Erkan Kayacan
This paper develops computationally efficient data-driven model predictive control (MPC) for Agile quadrotor flight. Agile quadrotors in high-speed flights can experience high leve…
OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics
N. Passalis, S. Pedrazzi, R. Babuska +15
Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their r…
Concurrent Learning Based Tracking Control of Nonlinear Systems using Gaussian Process
Vedant Bhandari, Erkan Kayacan
This paper demonstrates the applicability of the combination of concurrent learning as a tool for parameter estimation and non-parametric Gaussian Process for online disturbance le…
Distributed nonlinear model predictive control of an autonomous tractor-trailer system
Erkan Kayacan, Erdal Kayacan, Herman Ramon +1
This paper addresses the trajectory tracking problem of an autonomous tractor-trailer system by using a fast distributed nonlinear model predictive control algorithm in combination…
Adaptive Neuro-Fuzzy Control of a Spherical Rolling Robot Using Sliding-Mode-Control-Theory-Based Online Learning Algorithm
Erkan Kayacan, Erdal Kayacan, Herman Ramon +1
As a model is only an abstraction of the real system, unmodeled dynamics, parameter variations, and disturbances can result in poor performance of a conventional controller based o…
Towards agrobots: Identification of the yaw dynamics and trajectory tracking of an autonomous tractor
Erkan Kayacan, Erdal Kayacan, Herman Ramon +1
More efficient agricultural machinery is needed as agricultural areas become more limited and energy and labor costs increase. To increase their efficiency, trajectory tracking pro…
Towards Agrobots: Trajectory Control of an Autonomous Tractor Using Type-2 Fuzzy Logic Controllers
Erdal Kayacan, Erkan Kayacan, Herman Ramon +2
Provision of some autonomous functions to an agricultural vehicle would lighten the job of the operator but in doing so, the accuracy should not be lost to still obtain an optimal…
Robust Tube-Based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System
Erkan Kayacan, Erdal Kayacan, Herman Ramon +1
This paper addresses the trajectory tracking problem of an autonomous tractor-trailer system by using a decentralized control approach. A fully decentralized model predictive contr…
Identification of Nonlinear Dynamic Systems Using Type-2 Fuzzy Neural Networks -- A Novel Learning Algorithm and a Comparative Study
Erkan Kayacan, Erdal Kayacan, Mojtaba Ahmadieh Khanesar
In order to achieve faster and more robust convergence (especially under noisy working environments), a sliding mode theory-based learning algorithm has been proposed to tune both…
Robust Trajectory Tracking Error Model-Based Predictive Control for Unmanned Ground Vehicles
Erkan Kayacan, Herman Ramon, Wouter Saeys
This paper proposes a new robust trajectory tracking error-based control approach for unmanned ground vehicles. A trajectory tracking error-based model is used to design a linear m…
A Self-Learning Disturbance Observer for Nonlinear Systems in Feedback-Error Learning Scheme
Erkan Kayacan, Joshua M. Peschel, Girish Chowdhary
This paper represents a novel online self-learning disturbance observer (SLDO) by benefiting from the combination of a type-2 neuro-fuzzy structure (T2NFS), feedback-error learning…
Multi-Objective Control for String Stability of Cooperative Adaptive Cruise Control Systems
Erkan Kayacan
Autonomous vehicle following systems are playing a decisive role to increase vehicle density on roads by shortening inter-vehicle time gaps. However, disturbance attenuation along…
Experimental Validation of Linear and Nonlinear MPC on an Articulated Unmanned Ground Vehicle
Erkan Kayacan, Wouter Saeys, Herman Ramon +2
This paper focuses on the trajectory tracking control problem for an articulated unmanned ground vehicle. We propose and compare two approaches in terms of performance and computat…
Adaptive and Efficient Model Predictive Control for Booster Reentry
Joseph Chai, Eran Medagoda, Erkan Kayacan
Model predictive control (MPC) is an optimal control strategy where control input calculation is based on minimizing the predicted tracking error over a finite horizon that moves w…
High Precision Control of Tracked Field Robots in the Presence of Unknown Traction Coefficients
Erkan Kayacan, Sierra N. Young, Joshua M. Peschel +1
Accurate steering through crop rows that avoids crop damage is one of the most important tasks for agricultural robots utilized in various field operations, such as monitoring, mec…
Feedback Linearization Control for Systems with Mismatched Uncertainties via Disturbance Observers
Erkan Kayacan, Thor I. Fossen
This paper focuses on a novel feedback linearization control (FLC) law based on a self-learning disturbance observer (SLDO) to counteract mismatched uncertainties. The FLC based on…
Tracking error learning control for precise mobile robot path tracking in outdoor environment
Erkan Kayacan, Girish Chowdhary
This paper presents a Tracking-Error Learning Control (TELC) algorithm for precise mobile robot path tracking in off-road terrain. In traditional tracking error-based control appro…
Sliding Mode Control for Systems with Mismatched Time-Varying Uncertainties via a Self-Learning Disturbance Observer
Erkan Kayacan
This paper presents a novel Sliding Mode Control (SMC) algorithm to handle mismatched uncertainties in systems via a novel Self-Learning Disturbance Observer (SLDO). A computationa…
High precision control and deep learning-based corn stand counting algorithms for agricultural robot
Zhongzhong Zhang, Erkan Kayacan, Benjamin Thompson +1
This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultur…
Sliding Mode Learning Control of Uncertain Nonlinear Systems with Lyapunov Stability Analysis
Erkan Kayacan
This paper addresses to Sliding Mode Learning Control (SMLC) of uncertain nonlinear systems with Lyapunov stability analysis. In the control scheme, a conventional control term is…
Closed-Loop Error Learning Control for Uncertain Nonlinear Systems With Experimental Validation on a Mobile Robot
Erkan Kayacan
This paper develops a Closed-Loop Error Learning Control (CLELC) algorithm for feedback linearizable systems with experimental validation on a mobile robot. Traditional feedback an…