Abstract

A crucial challenge in maintaining formation in an autonomous vehicle platoon rests on designing a suitable control scheme that can tackle external disturbances and uncertain system parameters, especially the friction forces between wheel and ground, which vary with change in road surface, wear in tires and speed of the vehicle. State-of-the-art adaptive controller negotiating such uncertainties can typically handle a priori bounded (or non state-dependent) uncertainties. However, besides the difficulty in accurate modelling and identification of frictional forces, in general, these forces are state-dependent and cannot be a priori bounded (e.g., viscous friction). This paper proposes an adaptive sliding mode controller for nonholonomic wheeled mobile robot based vehicle platoon which can handle unknown complex behaviour of frictional forces without a priori knowledge of its parameters and structures. The effectiveness of the proposed controller is verified in Gazebo simulation in comparison with the state of the art.

Abstract

Long standing challenges in adaptive bipedal walking control (i.e. control taking care of unknown robot parameters) were to unify the control design instead of designing multiple controllers for different walking phases as well as to bypass computing constraint forces, since it often leads to complex designs. A few attempts to design a single controller for all walking phases ignored or oversimplified the constraint forces. However, these forces are state-dependent and may lead to conservative performance or instability if not countered properly. This work proposes an innovative adaptive control method, based on artificial time delay control, which covers the entire bipedal walking phase and provides robustness against state-dependent unmodelled dynamics such as constraint forces and external impulsive forces arising during walking. Studies using a high fidelity simulator under various forms of disturbances show the effectiveness of the proposed design over the state of the art.

Abstract

—Mobile robots play a crucial role in cleaning, maintenance, and surveillance applications. This article advocates for the use of a novel robust output feedback based path following controller, for a class of selfreconfigurable mobile robot under actuator saturation. The reconfigurability property of such platforms is captured via an uncertain Euler–Lagrange dynamics. The proposed control framework estimates the unmeasurable states and the uncertain dynamics terms through two extended high gain observers, whereas the actuator limits are honored via a fast dynamic compensator. The closed-loop stability is analyzed via contraction theory, which, compared to the conventional Lyapunov based approaches, avoids the requirement of arbitrarily large controller and observer gains. Such a feature is of particular interest in view of actuator saturation. The experimental results with PANTHERA self-reconfigurable robot validate the effectiveness of the proposed technique over the state of the art.

Abstract

Construction crane vessels make use of dynamic positioning (DP) systems during the installation and removal of offshore structures to maintain the vessel’s position. Studies have reported cases of instability of DP systems during offshore operation caused by uncertainties, such as mooring forces. DP “robustification” for heavy lift operations, i.e., handling such uncertainties systematically and with stability guarantees, is a long-standing challenge in DP design. A new DP method, composed by an observer and a controller, is proposed to address this challenge, with stability guarantees in the presence of uncertainties. We test the proposed method on an integrated cranevessel simulation environment, where the integration of several subsystems (winch dynamics, crane forces, thruster dynamics, fuel injection system etc.) allow a realistic validation under a wide set of uncertainties.

Abstract

The focus of this paper is (i) to derive a suitable dynamic model for a self-reconfigurable pavement sweeping robot PANTHERA and (ii) to design a robust controller for the same to tackle uncertainties stemming from the reconfiguration process, external disturbances and from actuator saturation. To meet the first objective, an Euler-Lagrangian dynamic model is proposed to incorporate the effects of configuration changes on the system dynamics. Based on this model, the second objective is met via designing a singular perturbation based robust controller which can tackle the aforementioned uncertainties without violating the actuation limits. To circumvent the vulnerability toward actuator saturation, the proposed controller is built on contraction theory, which, compared to a conventional Lyapunov theory based design, allows to improve closed-loop tracking performance without reducing the singular perturbation parameter. Experimental results on the PANTHERA reconfigurable robot validate the effectiveness of the proposed controller over the state of the art.

Abstract

We address a distributed adaptive synchronization problem for complex networks composed of nonlinear nodes under state-dependent a priori interconnections, i.e. interconnection terms acting before control design. The interconnection terms are uncertain and the heterogeneous dynamics of the network nodes further contain state-dependent uncertainty and uncertain input matrix gain. Adaptive distributed control laws are proposed to tackle such an unsolved design. The proposed controller is verified in simulation via a multi-area load frequency control for power systems.

Abstract

By increasingly relying on network-based operation for control, monitoring, and protection functionalities, modern wide-area power systems have also become vulnerable to cyber- attacks aiming to damage system performance and/or stability. Resilience in state-of-the-art methods mostly relies on known characteristics of the attacks and static control loops (i.e., with fixed input/output channels). This work proposes a ‘dynamic loop’ wide-area damping strategy, where input/output channel pairs are changed dynamically. We study ‘reactive’ dynamic switching in case of detectable attack and ‘pro-active’ dynamical switching, in case of undetectable (stealth) attacks. Stability of the dynamic loop is presented via Lyapunov theory, under para- metric perturbations, average dwell time switching and external perturbations. Using two- and five-area IEEE benchmarks, it is shown that the proposed strategy provides effective damping and robustness under various detectable (e.g., false data injection, denial-of-service) and stealth (replay, bias injection) attacks. Index Terms—Cyber-attack, dynamic loop, resilience, switched controller, wide-area damping control.

Abstract

Position control for heavy-lift construction vessels is crucial for safe operation during offshore construction. During the various phases of a typical offshore construction assignment, considerable changes in the dynamics of the crane-vessel system occur. Operational hazard was reported if such interchanging dynamics are not properly handled. However, to date and the best of our knowledge, no systematic control solution is reported considering multiphase offshore construction scenarios. This article proposes a switched dynamical framework to model the interchanging phases and to formulate a comprehensive position control solution for heavy-lift vessels. Stability and robustness against modeling imperfections and environmental disturbances are analytically assessed. The effectiveness of the solution is verified on a realistic heavy-lift vessel simulation platform; it is shown that the proposed switched framework sensibly improves accuracy and reduces hazard compared with a nonswitched solution designed for only one phase of the construction scenario. Index Terms— Dynamic positioning (DP) system, heavy-lift construction vessel, observer-based control, switched systems.

Abstract

This article proposes an adaptive-robust maneuvering control framework for a planar snake robot under the influence of parameter uncertainties. The entire control objective of maneuvering control can be viewed as the simultaneous establishments of two goals: one to maintain a time-varying body shape of the snake robot for consistent motion (called the outer layer) and the other dealing with the velocity and head-angle tracking of the same (called the inner layer). Unknown variations in the ground friction coefficients have been considered to be the primary source of time-varying uncertainties which affects the control performance in both the layers. Accordingly, an artificial time delay-based adaptive-robust control (ARC) framework, dual adaptive-robust time-delayed control (ARTDC), is proposed. The term dual signifies simultaneous application of ARTDC for the outer as well as the inner layer. ARTDC comprises of two segments: an artificial time delay-based time-delayed estimation (TDE) part and an ARC part. While TDE approximates the completely unknown friction forces, the ARC tackles the approximation error arising from the TDE. More importantly, compared with the existing ARC methodologies, the proposed ARTDC neither presumes the overall uncertainty to be upper bounded by a constant nor requires any prior knowledge of the bound of uncertainty to implement the controller. A Lyapunov function-based method has been adopted for analyzing the stability of the closed-loop system. Simulation studies affirm the improved performance of the ARTDC in contrast to the classical artificial delay-based methodology.

Abstract

Artificial-delay control is a method in which state and input measurements collected at an immediate past time instant (i.e., artificially delayed) are used to compensate the uncertain dynamics affecting the system at the current time. This article formulates an artificial-delay control method with adaptive gains in the presence of nonlinear (Euler–Lagrange) underactuation. The appeal of studying Euler–Lagrange dynamics is to capture many robotics applications of practical interest, as demonstrated via stability and robustness analysis and via robotic ship and robotic aerial vehicle test cases.