This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

Modern, torque-controlled service robots can regulate contact forces when interacting with their environment. Model Predictive Control (MPC) is a powerful method to solve the underlying control problem, allowing to plan for whole-body motions while including different constraints imposed by the robot dynamics or its environment. However, an accurate model of the robot-environment is needed to achieve a satisfying closed-loop performance. Currently, this necessity undermines the performance and generality of MPC in manipulation tasks. In this work, we combine an MPC-based whole-body controller with two adaptive schemes, derived from online system identification and adaptive control. As a result, we enable a general mobile manipulator to interact with unknown environments, without any need for re-tuning parameters or pre-modeling the interacting objects. In combination with the MPC controller, the two adaptive approaches are validated and benchmarked with a ball-balancing manipulator in door opening and object lifting tasks.

/pdf/model-predictive-robot-environment-interaction-control-for-2m5taeuir2.pdf

Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks

https://www.techscience.com/cmc/v70n3/44994/pdf

Position Control of Flexible Joint Carts Using Adaptive Generalized Dynamics Inversion

With the proliferation of modular Unmanned Aerial Vehicles (UAVs) cheap and scalable control methods are needed to ensure operability. Using adaptive control it seems that these requirements could be met. In this paper applicability of parameter adaptation and control methods are demonstrated within the model identification adaptive control framework, implementing several methods and evaluating their performance. As a plant a non-linear simulation model of an F-16 aircraft is used.

/pdf/model-identification-adaptive-control-implementation-case-3dktwvnaxo.pdf

Zsombor Oreg

Papers

Model identification adaptive control - implementation case studies for a high manoeuvrability aircraft