Iyad Hashlamon

• Ph.D Mechatronics Engineering
• Professor (Assistant) at Palestine Polytechnic University

This paper introduces a two-layer linear control approach to control highly nonlinear robots for high speed and adaptive tracking. The design of the control approach was based on the combination between the most common linear controllers (PID, Linear Quadratic Tracker, and State Feedback) and the principle of online disturbance estimation and rejec...

Abstract: This paper investigates two real-time vision-based control algorithms for delta robots. The first one aims to enable the robot to track different objects based on their colours and shapes. This algorithm does not need any initial calibration. Instead, it depends on the least squares algorithm (LSA) to generate the required transformation...

This paper introduces an adaptive disturbance estimation and compensation approach for delta parallel robots using three methods. The first method is based on the adaptive Kalman filter (AKF), the second method uses the Low pass filtered robot dynamic model (LFDM) while the third method is acceleration measurement based (AMB) method which utilizes...

This paper investigates a real time distributed controller for a 3 DOF delta robot using low-cost educational simple microcontrollers. The parallel computing technique is used were the computational load is divided among several microcontrollers networked to each other to implement control methods. More specifically, the computation is distributed...

This paper investigates a real time distributed controller for a 3 DOF delta robot. This robot is equipped with 3 servo motors, each motor has an attached encoder. The approach aims to use parallel computing to implement control methods. Hence, the computation is distributed among 4 microcontrollers (MCU's), these MCU's are connected to each other...

This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, the...

Abstract―This paper proposes a new method for sensorless position control for a mass which is connected with a servo motor through an elastic element. The system was assumed to have unknown parameters, so recursive least square (RLS) method was used to estimate these parameters depending on the reflected torque on the motor’s shaft. Kalman filter (...

Computer control labs at Palestine Polytechnic university consists of different control plants including 3DOF linear systems, also single, and double inverted pendulums. For the educational need of applying control techniques on parallel robots; Delta robot is to be implemented. A 3DOF Delta robot is implemented to provide 3 translational motions i...

The present paper presents a novel method for estimating the joint friction of walking bipeds. It combines a measurement-based method with an adaptive model-based method to estimate the joint friction. The former is used when the feet is in contact, while the latter is used when the leg is swinging. The measurements are the feet forces and the read...

This paper proposes a new approach for slip prediction of walking biped robots. The slip prediction is a measurement-based and friction behavior-inspired approach. A measurement-based online algorithm is designed to estimate the Coulomb friction which is regarded as a slip threshold. To predict the slip, a safety margin is introduced in the negativ...

This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a frictio...

The motion of a walking biped has rich information about the contacts with the environment. This paper presents an optimal estimation method of the distributed normal reaction forces at the contact points on the feet soles of walking bipeds. The motion is acquired by employing the inertial measurement unit (IMU) and the joint-encoder readings into...

This paper presents a novel method for joint sensor faults detection and faulty signal reconstruction. It uses the Virtual Joint Sensor (VJS). The model structure of the VJS consists of two interconnected models: The simple Linear Inverted Pendulum Model (LIPM) and the robot leg kinematics model (LKM). Kalman filter based on LIPM estimates the Cent...

Kalman filter (KF) is used extensively for state estimation. Among its requirements are the process and observation noise covariances which are unknown or partially known in real life applications. Uncertain and biased values of the covariances result in KF performance degradation or divergence. Unlike previous methods, we are using the idea of the...

This paper presents a novel simple Virtual Slip Force Sensor (VSFS) for a walking biped. Bipeds walking stability is critical and they tend to lose it easily in real environments. Among the significant aspects that affect the stability is the availability of the required friction force which is necessary for the robot not to slip. In this paper we...

This paper presents a novel method for ground force sensor faults detection and faulty signal reconstruction using Virtual force Sensor (VFS) for slow walking bipeds. The design structure of the VFS consists of two steps, the total ground reaction force (GRF) and its location estimation for each leg based on the center of mass (CoM) position, the l...

An on-line assessment of the balance of the robot requires information of the state variables of the robot dynamics and measurement data about the environmental interaction forces. However, modeling errors, external forces and hard to measure states pose difficulties to the control systems. This paper presents a method of using the motion informati...