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Maximizing the utility of human-robot teams in disaster response and search and rescue (SAR) missions remains to be a challenging problem. This is due to the dynamic, uncertain nature of the environment and the variability in cognitive…
Predictive Stator Current Control (PSCC) has been proposed for control of multi-phase drives. The flexibility offered by the use of a Cost Function has been used to deal with the increased number of phases. However, tuning of the Weighting…
Tendon-Driven Continuum Robots (TDCRs) have the potential to be used in minimally invasive surgery and industrial inspection, where the robot must enter narrow and confined spaces. We propose a Model Predictive Control (MPC) approach to…
In this article, we address the problem of computing adaptive sensorimotor models that can be used for guiding the motion of robotic systems with uncertain action-to-perception relations. The formulation of the uncalibrated sensor-based…
Most robotic hands and grippers rely on actuators with large gearboxes and force sensors for controlling gripping force. However, this might not be ideal for tasks which require the robot to interact with an unstructured and/or unknown…
This paper presents methods for finding optimal configurations and actuator forces/torques to maximise contact wrenches in a desired direction for Underwater Vehicles Manipulator Systems (UVMS). The wrench maximisation problem is formulated…
In this study, a new approach based on adaptive dynamic programming (ADP) is proposed to control permanent magnet synchronous motors (PMSMs). The objective of this paper is to control the torque and consequently the speed of a PMSM when an…
We propose a general model-free strategy for feedback control design of turbulent flows. This strategy called 'machine learning control' (MLC) is capable of exploiting nonlinear mechanisms in a systematic unsupervised manner. It relies on…
This paper introduces a novel model-free control strategy for a complex multi-stage gearbox electromechanical linear actuator (EMLA) system, driven by a permanent magnet synchronous motor (PMSM) with non-ideal ball screw characteristics.…
In this paper we propose an Intelligent Management System which is capable of managing the automobile functions using the rigorous real-time principles and a multicore processor in order to realize higher efficiency and safety for the…
Soft robots can execute tasks with safer interactions. However, control techniques that can effectively exploit the systems' capabilities are still missing. Differential dynamic programming (DDP) has emerged as a promising tool for…
High-performance closed-loop control of truly soft continuum manipulators has remained elusive. Experimental demonstrations have largely relied on sufficiently stiff, piecewise architectures in which each actuated segment behaves as a…
We develop a hybrid control approach for robot learning based on combining learned predictive models with experience-based state-action policy mappings to improve the learning capabilities of robotic systems. Predictive models provide an…
Robot arms have been using in different systems, which the control of designed in desired trajectory is the main task. Also, it is anticipated that while in operation the developed 2DoF robot arm will be constantly encountered with noises…
This paper deals with sliding mode control for multivariable polytopic uncertain systems. We provide systematic procedures to design variable structure controllers (VSCs) and unit-vector controllers (UVCs). Based on suitable representations…
In this paper, the D2-IBC (Data-Driven Inversion Based Control) approach for nonlinear control is introduced and analyzed. The method does not require any a-priori knowledge of the system dynamics and relies on a two degrees of freedom…
Control systems are critical to modern technological infrastructure, spanning industries from aerospace to healthcare. This survey explores the landscape of safe robot learning, investigating methods that balance high-performance control…
In this paper, a novel robust tracking control law is proposed for constrained robots under unknown stiffness environment. The stability and the robustness of the controller are proved using a Lyapunov-based approach where the relationship…
Optimal control of a mobile robot system is formulated. Multiobjective criteria of time and energy is employed. The optimal control problem is formulated as a nonlinear programming problem (NLP). The problem is solved using the direct…
Dynamic motions are a key feature of robotic arms, enabling them to perform tasks quickly and efficiently. Soft continuum manipulators do not currently consider dynamic parameters when operating in task space. This shortcoming makes…