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A L1 adaptive backstepping controller is proposed for path-following control of an underactuated ship based on a nonlinear steering model, and the control law is derived using Lypunov control function. L1 adaptive controller is a novel technology considering both the robustness and fast adaptation. The closed-loop control system is proved to be uniformly global asymptotically stable. A novel guidance law, time-varying vector field, is proposed for the guidance system. The kinematic analysis of path-following shows that the guidance and control systems are coupled, and the guidance system is affected by the performance of the controller. The Lyapunov method is employed to show that the equilibrium point of the whole system is uniformly global asymptotically stable. Path-following simulations are carried out to validate the performance of the proposed control law and vector field guidance law using a fully nonlinear manoeuvring mode of an underactuated tanker in the presence of stochastic ocean current. [ABSTRACT FROM AUTHOR]

The current study employs a novel nonlinear robust control approach for path-following control of underactuated autonomous underwater vehicles (AUVs) with multiple uncertainties in the vertical plane. Firstly, a nonlinear underactuated AUV model is established to characterize the dynamics of AUV and path-following error. To resolve dependence on a detailed model that appeared in previous studies, the unknown time-varying attack angular velocity in the dynamic model of the path-following error is considered as the kinematic uncertainty, while the linear superposition of the external environmental disturbances, the perturbations in the internal model parameters, and other unmodeled dynamics in the dynamic model is chosen as lumped dynamic uncertainties. Several reduced-order extended state observers (ESOs) are designed for estimating both of these uncertainties. Secondly, to reduce the impact of input saturation and avoid the “explosion of complexity” associated with traditional back-stepping method, a nonlinear track differentiator (NTD) is utilized to follow the virtual control signal and its derivative. Thirdly, the constructed reduced-order ESOs and NTD are adopted to establish an augmented back-stepping controller, where its ability to stabilize the overall system is demonstrated using the Lyapunov theorem. Finally, extensive simulations and analyses in various working conditions, including the nominal working condition without disturbances, the working condition with multiple uncertainties, and the conditions which better replicate the actual environment, are performed to demonstrate the effectiveness, superiority, and robustness of the designed controller.

This article presents a novel extensible continuum robot (ECR) with growing motion capability for improved flexible access in transoral laryngeal procedures. The robot uses an extensible continuum joint with a staggered V-shaped notched structure as the backbone, driven by the pushing and pulling of superelastic Nitinol rods. The notched structure is optimized to achieve a wide range of extension/contraction and bending motion for the continuum joint. The successive and uniform deflection of the notches provides the continuum joint with excellent constant curvature bending characteristics. The bidirectional rod-driven approach expands the robot's extension capabilities with both pushing and pulling operations, and the superelasticity of the driving rods preserves the robot's bending performance. The ECR significantly increases motion dexterity and reachability through its variable length, which facilitates collision-free access to deep lesions by following the anatomy. To further exploit the advantages of the ECR in path-following for flexible access, a growing motion approach inspired by the plant growth process has been proposed to minimize the path deviation error. Characterization experiments are conducted to verify the performances of the proposed ECR. The extension ratio achieves up to 225.92%, and the average distal positioning error and hysteresis error values are 2.87% and 0.51% within the ±120° bending range. Compared with the typical continuum robot with a fixed length, the path-following deviation of this robot is reduced by more than 58.30%, effectively reducing the risk of collision during access. Phantom experiments validate the feasibility of the proposed concept in flexible access procedures.

The paper addresses path planning and path-following problems in an unknown complex environment for an underactuated autonomous underwater vehicle (AUV). The AUV is required to follow a given reference path represented as a sequence of smoothly joined lines and arcs, bypassing obstacles encountered on the path. A two-level control system is proposed with an upper level for event-driven path planning and a lower level for path-following. A discrete event system is designed to identify situations that require planning a new path. An improved waypoint guidance algorithm and a Dubins curves based algorithm are proposed to build paths that allow the AUV to avoid collision with obstacles and to return to the reference path respectively. Both algorithms generate paths that meet the minimum turning radius constraint. A robust parameter-varying controller is designed using sublinear vector Lyapunov functions to solve the path-following problem. The performance of the developed event-based control system is demonstrated in three different simulation scenarios: with a sharp-edged obstacle, with a U-shaped obstacle, and with densely scattered obstacles. The proposed scheme does not require significant computing resources and allows for easy implementation on board. [ABSTRACT FROM AUTHOR]

This article studies the design, modeling, and implementation of a path-following algorithm as a guidance, navigation, and control (GNC) architecture for an autonomous underwater vehicle (AUV). First, a mathematical model is developed based on nonlinear equations of motion and parameter estimation techniques, including the model validation based on field test data. Then, the guidance system incorporates a line-of-sight (LOS) algorithm with a combination of position PID controllers. The GNC architecture includes a modular and multi-layer approach with an LOS-based, path-following algorithm in the AUV platform. Furthermore, the navigation used in the path-following algorithm is developed based on a predefined coverage area. Finally, this study addresses simulation and field test control scenarios to verify the developed GNC architecture.

This paper presents a nonlinear, universal, path-following controller for Wheeled Mobile Robots (WMRs). This approach, unlike previous algorithms, solves the path-following problem for all common categories of holonomic and nonholonomic WMRs, such as omnidirectional, unicycle, car-like, and all steerable wheels. This generality is the consequence of a two-stage solution that tackles separately the platform path-following and wheels’ kinematic constraints. In the first stage, for a mobile platform divested of the wheels’ constraints, we develop a general paradigm of a path-following controller that plans asymptotic paths from the WMR to the desired path and, accordingly, we derive a realization of the presented paradigm. The second stage accounts for the kinematic constraints imposed by the wheels. In this stage, we demonstrate that the designed controller simplifies the otherwise impenetrable wheels’ kinematic and nonholonomic constraints into explicit proportional functions between the velocity of the platform and that of the wheels. This result enables us to derive a closed-form trajectory generation scheme for the asymptotic path that constantly keeps the wheels’ steering and driving velocities within their corresponding, pre-specified bounds. Extensive experimental results on several types of WMRs, along with simulation results for the other types, are provided to demonstrate the performance and the efficacy of the method.

In this paper, a full-Newton step Interior-Point Method for solving monotone Weighted Linear Complementarity Problem is designed and analyzed. This problem has been introduced recently as a generalization of the Linear Complementarity Problem with modified complementarity equation, where zero on the right-hand side is replaced with the nonnegative weight vector. With a zero weight vector, the problem reduces to a linear complementarity problem. The importance of Weighted Linear Complementarity Problem lies in the fact that it can be used for modelling a large class of problems from science, engineering and economics. Because the algorithm takes only full-Newton steps, the calculation of the step size is avoided. Under a suitable condition, the algorithm has a quadratic rate of convergence to the target point on the central path. The iteration bound for the algorithm coincides with the best iteration bound obtained for these types of problems. [ABSTRACT FROM AUTHOR]

We present an electrothermal drift–diffusion model for organic semiconductor devices with Gauss–Fermi statistics and positive temperature feedback for the charge carrier mobilities. We apply temperature-dependent Ohmic contact boundary conditions for the electrostatic potential and discretize the system by a finite volume based generalized Scharfetter–Gummel scheme. Using path-following techniques, we demonstrate that the model exhibits S-shaped current–voltage curves with regions of negative differential resistance, which were only recently observed experimentally. [ABSTRACT FROM AUTHOR]

This article studies the design, modeling, and implementation challenges of a path-following with obstacle avoidance algorithms as guidance, navigation, and control (GNC) architecture of an unmanned surface vehicle (USV) in harbor conditions. First, an effective mathematical model is developed based on system identification, validating the USV model with field-test data. Then, a guidance system is addressed based on a line-of-sight algorithm, which uses a LiDAR as the main perception sensor for the obstacle avoidance algorithm. The GNC architecture uses a modular approach, including obstacle detection, path-following, and control in the USV platform. Finally, an implementation challenge in two control scenarios, simulation and field test, is addressed to validate the designed GNC architecture. [ABSTRACT FROM AUTHOR]

The actual performance of model-based path-following methods for unmanned aerial vehicles (UAVs) shows considerable dependence on the wind knowledge and on the fidelity of the dynamic model used for design. This study analyzes and demonstrates the performance of an adaptive vector field (VF) control law which can compensate for the lack of knowledge of the wind vector and for the presence of unmodeled course angle dynamics. Extensive simulation experiments, calibrated on a commercial fixed-wing UAV and proven to be realistic, show that the new VF method can better cope with uncertainties than its standard version. In fact, while the standard VF approach works perfectly for ideal first-order course angle dynamics (and perfect knowledge of the wind vector), its performance degrades in the presence of unknown wind or unmodeled course angle dynamics. On the other hand, the estimation mechanism of the proposed adaptive VF effectively compensates for wind uncertainty and unmodeled dynamics, sensibly reducing the path-following error as compared to the standard VF. [ABSTRACT FROM AUTHOR]

• The paper presents an efficient computational method for economic nonlinear model predictive control, which is based on nonlinear programming (NLP) sensitivity update. • The novelty of the paper lies on the NLP sensivity method that is designed for a weaker constraint qualification namely, Mangasarian-Fromovitz constraint qualification (MFCQ). • The proposed method is demonstrated on a large-scale chemical process case example, consisting more than 10.000 decision variables. We present a sensitivity-based nonlinear model predictive control (NMPC) algorithm and demonstrate it on a case study with an economic cost function. In contrast to existing sensitivity-based approaches that make strong assumptions on the underlying optimization problem (e.g. the linear independence constraint qualification implying unique multiplier), our method is designed to handle problems satisfying a weaker constraint qualification, namely the Mangasarian-Fromovitz constraint qualification (MFCQ). Our nonlinear programming (NLP) sensitivity update consists of three steps. The first step is a corrector step in which a system of linear equations is solved. Then a predictor step is computed by a quadratic program (QP). Finally, a linear program (LP) is solved to select the multipliers that give the correct sensitivity information. A path-following scheme containing these steps is embedded in the advanced-step NMPC (asNMPC) framework. We demonstrate our method on a large-scale case example consisting of a reactor and distillation process. We show that LICQ does not hold and the path-following method is able to accurately approximate the ideal solutions generated by an NLP solver. [ABSTRACT FROM AUTHOR]

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance. [ABSTRACT FROM AUTHOR]

• Eccentric CG causes considerable tracking error (TE) as well as added tire wear (TW). • An upgraded 8DOF vehicle model is presented, which includes off-centre CG impact. • The highest theoretically removal of TE/TW is achieved through the ideal model. Electric Vehicles (EVs) are becoming an inimitable answer to the problem of transport sector pollution. The inherent potential of individual wheels' control makes in-wheel-drive EVs even more advantageous. This paper investigates the dynamics control of a laterally off-centre CG (Centre of Gravity) electric vehicle as a real-world practice, nevertheless ignored. Apart from dynamic performance, tires' loss as a representative of their wear and hence TWP (Tire Wear Particle) emission is analysed. In this regard, mathematical modelling of an eight-degree-of-freedom electric vehicle with eccentric CG is pioneered. The model is used to develop a novel control strategy which calculates torque distributions for the front-left and right in-wheel motors. The ideal torque distribution satisfies the torque demand as well as perfect reference yaw rate tracking. Simulation results for two straight and cornering scenarios reveal that while almost removing path-following error, a properly designed torque distribution controller could potentially cancel up to nearly 5 % of tires' wear compared to three other rival strategies. [ABSTRACT FROM AUTHOR]

Economic efficient Autonomous Road Vehicles (ARVs) are invariably subjected to uncertainties and perturbations. Therefore, control of vehicle systems requires stability to withstand the effect of variations in the nominal performance. Lateral path-tracking is a substantial task of ARVs, especially in critical maneuvering and cornering with variable speed. In this study, a new controller on the basis of interval type-3 (T3) fuzzy logic system (FLSs) is designed. The main novelties and advantages are as follows. (1) The uncertainty is a main challenge in the path-following problem of ARVs. However, in the fuzzy-based approaches, the bounds of uncertainty are assumed to be known. However, in the our suggested approach, the bounds of uncertainties are also fuzzy sets and type-3 FLSs with online adaptation rules are suggested to handle the uncertainties. (2) The approximation errors (AEs) and perturbations are investigated and tackled by the compensators. (3) The bounds of estimation errors are also uncertain and are estimated by the suggested adaptation laws. (4) The stability is ensured under unknown dynamics, perturbations and critical maneuvers. (5) Comparison with the benchmarking techniques and conventional fuzzy approaches verifies that the suggested path-following scheme results in better maneuver performance.

We highlight an essential difference between path-following and reference-tracking for nonminimum phase systems. It is well known that in the reference-tracking, for nonminimum phase systems, there exists a fundamental performance limitation in terms of a lower bound on the L-2-norm of the tracking error, even when the control effort is free. We show that this is not the case for the less stringent path-following problem, where the control objective is to force the output to follow a geometric path without a timing law assigned to it. Furthermore, the same is true even when an additional desired speed assignment is imposed.

A modified path-following control system using the vector field method for an underactuated autonomous surface ship model is proposed in the presence of static obstacles. With this integrated system, autonomous ships are capable of following the predefined path, while avoiding the obstacles automatically. It is different from the methods in most published papers, which usually study path-following and obstacle collision avoidance, separately. This paper considers the coupled path following and collision avoidance task as a whole. Meanwhile, the paper also shows the heading control design method in the presence of static obstacles. To obtain a strong stability property, a nonlinear autopilot is designed based on the manoeuvring tests of the free-running ship model. The equilibrium point of the controller is globally exponentially stable. For the guidance system, a novel vector field method was proposed, and the proof shows the coupled guidance and control system is uniform semi-global exponentially stable (USGES). To prevent the obstacles near the predefined path, the proposed guidance law is augmented by integrating the repelling field of obstacles so that it can control the ship travel toward the predefined path through the obstacles safely. The repelling field function is given considering the obstacle shape and collision risk using the velocity obstacle (VO) algorithm. The simulations and ship model test were performed to validate the integrated system of autonomous ships.

A synthesis of recent progress is presented on a topic that lies at the heart of both structural engineering and non-linear science. The emphasis is on thin elastic structures that lose stability subcritically—without a nearby stable post-buckled state—a canonical example being a uniformly axially-loaded cylindrical shell. Such structures are hard to design and certify because imperfections or shocks trigger buckling at loads well below the threshold of linear stability. A resurgence of interest in structural instability phenomena suggests practical stability assessments require stochastic approaches and imperfection maps. This article surveys a different philosophy; the buckling process and ultimate post-buckled state are well-described by the perfect problem. The significance of the Maxwell load is emphasized, where energy of the unbuckled and fully-developed buckle patterns are equal, as is the energetic preference of localized states, stable, and unstable versions of which connect in a snaking load-deflection path. The state of the art is presented on analytical, numerical and experimental methods. Pseudo-arclength continuation (path-following) of a finite-element approximation computes families of complex localized states. Numerical implementation of a mountain-pass energy method then predicts the energy barrier through which the buckling process occurs. Recent developments also indicate how such procedures can be replicated experimentally; unstable states being accessed by careful control of constraints, and stability margins assessed by shock sensitivity experiments. Finally, the fact that subcritical instabilities can be robust, not being undone by reversal of the loading path, opens up potential for technological exploitation. Several examples at different length scales are discussed; a cable-stayed prestressed column, two examples of adaptive structures inspired by morphing aeroelastic surfaces, and a model for a functional auxetic material.

A new type of path-following method has been developed to steer marine surface vehicles along desired paths. Path-following is achieved by a new hyperbolic guidance law for straight-line paths and a backstepping control law for curved paths. An optimal controller has been improved for heading control, based on linear quadratic regulator (LQR) theory with nonlinear feedback control techniques. The control algorithm performance is validated by simulation and comparison against the requirements of International Standard IEC62065. Deviations are within the allowable range of the standard. In addition, the experimental results show that the proposed method has higher control accuracy.

This paper proposes a novel approach to the visual path following problem based on Nonlinear Model Predictive Control. Simplified visual features are extracted from the path to be followed. Then, aiming to calculate the control actions directly from the image plane, a regulatory model is obtained in the optimal control problem scope. For this purpose a Serret-Frenet system is placed in the center of camera's field of view and the optimal control actions generate velocity references to an inner loop embedded in the robot. Stability issues are handled through a classical method and a new approach based on constraints relaxation is proposed in order to guarantee feasibility. Experimental results with a nonholonomic platform illustrate the performance of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper focuses on the controller design for path-tracking problem of autonomous ground vehicles (AGVs) by employing a multi-constraint nonlinear predictive control (NMPC) schema. It is aimed to improve the transient performance of the vehicle and to consider a rollover prevention criterion in the proposed method. The path-tracking problem is transformed into the yaw stabilization issue, and a feedback control law with input saturation is developed to decrease the steady-state errors. Furthermore, the yaw-rate signal is generated for the desired path-tracking performance. The major contributions of the present paper are, first, developing a neural network autoregressive with exogenous input system to assist in obtaining an accurate and explicit model in order to contribute to the control of the system over the prediction horizon; second, describing a Frenet–Serret differential geometry based path-following agenda and developing AGV dynamic model by incorporating the vehicle vertical mode of motion to prevent vehicle rollover during critical maneuvers, and finally, achieving an enhanced yaw stabilization and transient tracking performance considering saturated input signal by employing the proposed system identification algorithm. The effectiveness of the proposed control system is verified by comparing with the traditional NMPC method by employing a high fidelity CarSim/MATLAB framework. [ABSTRACT FROM AUTHOR]

An efficient, function-space-based second-order method for the |$H^1$| -projection onto the Gibbs simplex is presented. The method makes use of the theory of semismooth Newton methods in function spaces as well as Moreau–Yosida regularization and techniques from parametric optimization. A path-following technique is considered for the regularization parameter updates. A rigorous first- and second-order sensitivity analysis of the value function for the regularized problem is provided to justify the update scheme. The viability of the algorithm is then demonstrated for two applications found in the literature: binary image inpainting and labeled data classification. In both cases, the algorithm exhibits mesh-independent behavior. [ABSTRACT FROM AUTHOR]

This paper presents an application and stability result of a modified line-of-sight (LOS) guidance law for 3-D path-following (PF) of an unmanned underactuated underwater vehicle subject to environmental disturbances. The PF problem is solved using a revised relative system model with an improved FLOW frame and a complete model of ocean current/wave disturbances. The PF approach uses course control and speed allocation, which is the problem of allocating the desired inertial total speed into desired BODY velocities including current/wave velocities. The definitions of track-errors in the general PF problem have been accurately illustrated in the inertial frame. The course control strategy, defined by incorporating the slip angles into the desired heading angles, has been extended to vertical plane with the new definition of vertical-slip. Stability results include local exponential stability (LES) of the enclosure-based LOS (ELOS) and semi-global exponential stability (SGES) of the modified LOS guidance laws. The 3-D LOS vector is tracked simultaneously in both planes using a planar speed assignment strategy in 4-DOF for a coupled 3-D tracking. Simulation results show robust PF performance of a sway-underactuated AUV in course control in the presence of significant ocean current disturbances and measurement noises. The effectiveness of simple course control and speed allocation in disturbance rejection has also been illustrated. [ABSTRACT FROM AUTHOR]

In this paper, a three-dimensional (3-D) path-following control design for an underactuated stratospheric airship is proposed based on the parameterized path description. The desired attitude, velocity, and the path parameter updating law are obtained by employing the guidance-based path-following principle. The resultant system possesses a cascaded structure, which consists of a guidance loop, an attitude stabilization loop, and a velocity tracking loop. The stability analysis shows that the path-following error and all states of the closed-loop system are ultimately uniformly bounded. Simulation results demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

Abstract In this work, the post-buckling analysis of thin-walled beams by using the Generalized Beam Theory (GBT) is presented. To this purpose, a geometrically nonlinear GBT finite element is developed by exploiting the features of mixed-stress GBT finite element formulation in the framework of the Implicit Corotational Method (ICM). The application of the ICM to GBT is briefly discussed and the details necessary to successfully transform the linear GBT finite element in its nonlinear counterpart are illustrated. The numerical results show how the proposed finite element can deal with global and distortional geometrically nonlinear phenomena, in good accordance with respect to 3D shell models. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We investigate uniform versions of (metric) regularity and strong (metric) regularity on compact subsets of Banach spaces, in particular, along continuous paths. These two properties turn out to play a key role in analyzing path-following schemes for tracking a solution trajectory of a parametric generalized equation or, more generally, of a differential generalized equation (DGE). The latter model allows us to describe in a unified way several problems in control and optimization such as differential variational inequalities and control systems with state constraints. We study two inexact path-following methods for DGEs having the order of the grid error and , respectively. We provide numerical experiments, comparing the schemes derived, for simple problems arising in physics. Finally, we study metric regularity of mappings associated with a particular case of the DGE arising in control theory. We establish the relationship between the pointwise version of this property and its counterpart in function spaces. [ABSTRACT FROM AUTHOR]

Abstract This paper describes experiments and analysis of the complete post-buckling behavior of shallow geodesic lattice domes. Although individual members are straight, their geometric arrangement approximates a curved surface and typical behavior is highly nonlinear, including the possibility of sudden jumps in which there may be multiple discontinuous pops from one equilibrium configuration to another. A number of shallow domes were produced using a 3D printer and tested using a load cell and proximity laser sensor. In contrast to most previous studies, rather than pinned or semi-rigid joints, the lattices studied here incorporate moment-transmitting joints and clamped boundary conditions at the perimeter. Thus, flexure is the dominant mode of deformation under lateral loading and coupled instability behaviors are possible in practice. The complete load-displacement relationship and multiple equilibrium configurations are exhibited both in experiment and in simulation. The experimental data shows a close correlation with nonlinear finite element analysis using path-following techniques. A typical member (coupled) buckling behavior and its influence on the critical load are presented. Conclusions are drawn with respect to symmetry and geometric sensitivity. [ABSTRACT FROM AUTHOR]

Abstract This note focuses on the waypoints-based path-following problem of underactuated ships, where the reference path is surrounded by multiple static and moving obstacles. By virtue of the improved dynamical virtual ship (DVS) principle, a novel guidance law with multi-obstacles avoidance is proposed to generate the real-time attitude reference. In this approach, the manoeuvering tasks are specified as three priority levels: the static obstacle avoidance, the moving obstacle avoidance and the path-following mission. And the detailed design abides the International Regulations for Preventing Collisions at Sea (COLREGs) to ensure the sailing safety, especially for moving obstacles or other vessels. Furthermore, a robust neural algorithm is developed by using the neural networks (NNs) approximation and the robust neural damping technique. The system gain uncertainty of actuators is tackled and less information about the hydrodynamic structure, the actuator model and the external disturbances are required. Considerable efforts are made to obtain the semi-global practical finite-time bounded (SGPFB) stability. The proposed scheme is with advantages of concise structure and improved autonomy. Finally, two experiments are employed to verify the effectiveness of the proposed strategy. Graphical abstract Image 1 Highlights • A novel DVS-based obstacles avoidance guidance is proposed for underactuated ships. • The proposed algorithm is developed with the finite-time convergence property. • The path-following controller is easy to be implemented in practice. • The measurable variables $n$ and $\delta$ are selected as the control inputs. [ABSTRACT FROM AUTHOR]

The paper addresses path planning and path-following problems in an unknown complex environment for an underactuated autonomous underwater vehicle (AUV). The AUV is required to follow a given reference path represented as a sequence of smoothly joined lines and arcs, bypassing obstacles encountered on the path. A two-level control system is proposed with an upper level for event-driven path planning and a lower level for path-following. A discrete event system is designed to identify situations that require planning a new path. An improved waypoint guidance algorithm and a Dubins curves based algorithm are proposed to build paths that allow the AUV to avoid collision with obstacles and to return to the reference path respectively. Both algorithms generate paths that meet the minimum turning radius constraint. A robust parameter-varying controller is designed using sublinear vector Lyapunov functions to solve the path-following problem. The performance of the developed event-based control system is demonstrated in three different simulation scenarios: with a sharp-edged obstacle, with a U-shaped obstacle, and with densely scattered obstacles. The proposed scheme does not require significant computing resources and allows for easy implementation on board.

This paper deals with actuation planning and control for active tensegrity structures. Within actuation planning, a specific actuation in the form of adjustments of cables' rest lengths is assigned to the resulting structure to follow a prescribed complex trajectory. The methodology is based on the desired trajectory discretisation and following consecutive actuation optimisation, which employs the dynamic relaxation method. Since the actuation planning problem is treated as static, a controller is designed to suppress possible structural vibrations. With regard to the need to test dynamical properties and simulate the structure's motion, a methodology for automatic creation of tensegrity computational models in Simscape software is developed in the MATLAB scripting environment. Numerical examples of particular tensegrity structures show the whole algorithm's efficiency. • New actuation planning method for the analysis and design of active tensegrity. • Prevents from overuse of any active members and overstressing of the structure. • Convenient approach that discovers reachability of structure's workspace. • General method which is applicable to a wide range of tensegrity structures. • Optional H2 controller enables further enhancement of control performance. [ABSTRACT FROM AUTHOR]

This paper proposes a finite-time output feedback methodology for the path-following task of marine surface vessels. First, a horizontal path-following model is established with unknown sideslip angle, unmeasured system state and system uncertainties. A hierarchical control structure is adopted to deal with the cascade property. For kinematics system design, a finite-time sideslip angle observer is first proposed, and thus the sideslip angle estimation is compensated in a nonlinear line-of-sight (LOS) guidance strategy to acquire finite-time convergence. For the heading control design, an extended state observer is introduced for the unmeasured state and equivalent disturbance estimation, based on which an output feedback backstepping approach is proposed for the desired tracking of command course angle. The global stability of the cascade system is analyzed. Simulation results validate the effectiveness of the proposed methodology.

The present work studies the geometrically nonlinear response of class θ = 1 tensegrity prisms modeled as a collection of elastic springs reacting in tension (strings or cables) or compression (bars), under uniform uniaxial loading. The incremental equilibrium equations of the structure are numerically solved through a path-following procedure, with the aim of modeling the mechanical behavior of the structure in the large displacement regime. Several numerical results are presented with reference to a variety of physical models, which use two different materials for the cables and the bars, and show different aspect ratios associated with either “standard” or “expanded” configurations. An experimental validation of the predicted constitutive response is conducted with reference to a “thick” and a “slender” model, observing rather good theory vs. experiment matching. The given numerical and experimental results highlight that the elastic response of the examined structures may switch from stiffening to softening, depending on the geometry of the system, the magnitude of the external load, and the applied prestress. The outcomes of the current study confirm previous literature results on the elastic response of minimal tensegrity prisms, and pave the way to the use of tensegrity systems as nonlinear spring units forming tunable mechanical metamaterials.

Studies of self-controlled practice have shown benefits when learners controlled feedback schedule, use of assistive devices and task difficulty, with benefits attributed to information processing and motivational advantages of self-control. Although haptic assistance serves as feedback, aids task performance and modifies task difficulty, researchers have yet to explore whether self-control over haptic assistance could be beneficial for learning. We explored whether self-control of haptic assistance would be beneficial for learning a tracing task. Self-controlled participants selected practice blocks on which they would receive haptic assistance, while participants in a yoked group received haptic assistance on blocks determined by a matched self-controlled participant. We inferred learning from performance on retention tests without haptic assistance. From qualitative analysis of open-ended questions related to rationales for/experiences of the haptic assistance that was chosen/provided, themes emerged regarding participants’ views of the utility of haptic assistance for performance and learning. Results showed that learning was directly impacted by the frequency of haptic assistance for self-controlled participants only and view of haptic assistance. Furthermore, self-controlled participants’ views were significantly associated with their requested haptic assistance frequency. We discuss these findings as further support for the beneficial role of self-controlled practice for motor learning.

In this paper, a new robust adaptive controller is investigated to force an underactuated surface marine vessel to follow a predefined parameterised path at a desired speed, despite actuator saturation and the presence of model uncertainties as well as environmental disturbances induced by waves, wind and sea-currents. To ensure robustness of the path-following controller, time-varying constraint on the off-track error (i.e. the maximal distance from the ship to the reference path) is considered. To address the off-track error constraint the tan-barrier Lyapunov function is incorporated with the control scheme, where the idea of auxiliary design system introduced in Chen, Sam, and Ren (2011) is adopted and its states are used in combination with backstepping and Lyapunov synthesis to adaptive tracking control design with guaranteed stability. Furthermore, the command filters are adopted to implement physical constraints on the virtual control laws so that analytic differentiation of the virtual control laws is avoided. We show that the proposed robust adaptive control law is able to guarantee semi-global uniform ultimate bounded stability of the closed-loop system. Numerical simulations and experimental results are carried out to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a design method for output-feedback path-following control of under-actuated autonomous underwater vehicles moving in a vertical plane without using surge, heave, and pitch velocities. Specifically, an extended state observer (ESO) is developed to recover the unmeasured velocities as well as to estimate total uncertainty induced by internal model uncertainty and external disturbance. At the kinematic level, a commanded guidance law is developed based on a vertical line-of-sight guidance scheme and the observed velocities. To optimize guidance signals, optimization-based reference governors are formulated as bound-constrained quadratic programming problems for computing optimal reference signals. Two globally convergent recurrent neural networks called projection neural networks are used to solve the optimization problems in real-time. Based on the optimal reference signals and ESO, a kinetic control law with disturbance rejection capability is constructed at the kinetic level. It is proved that all error signals in the closed-loop system are uniformly and ultimately bounded. Simulation results substantiate the efficacy of the proposed method for output-feedback path-following of under-actuated autonomous underwater vehicles. [ABSTRACT FROM PUBLISHER]

In this paper we consider a control system coupled with a generalized equation, which we call a differential generalized equation (DGE). This model covers a large territory in control and optimization, such as differential variational inequalities, control systems with constraints, as well as necessary optimality conditions in optimal control. We study metric regularity and strong metric regularity of mappings associated with DGE by focusing in particular on the interplay between the pointwise versions of these properties and their infinite-dimensional counterparts. Metric regularity of a control system subject to inequality state-control constraints is characterized. A sufficient condition for local controllability of a nonlinear system is obtained via metric regularity. Sufficient conditions for strong metric regularity in function spaces are presented in terms of uniform pointwise strong metric regularity. A characterization of the Lipschitz continuity of the control part of the solution mapping as a function of time is established. Finally, a path-following procedure for a discretized DGE is proposed for which an error estimate is derived. [ABSTRACT FROM AUTHOR]

In order to steer an Unmanned Aerial Vehicle (UAV) and make it follow a desired trajectory, a high level controller is needed. Depending on the control algorithm, one or more parameters have to be tuned, having their values high impact on the performance. In most of the works, these parameters are taken as constant. In this paper, we apply fuzzy logic to select the parameters of the control law and compare this approach with the tuning by constant parameters and with another adjusting method based on the kinematic analysis of the equations of the UAV. After many simulations of the quadrotor following randomly generated paths, we have proved that the fuzzy tuning law is not only a good and feasible solution, but also more general as it can be applied to any trajectory. [ABSTRACT FROM AUTHOR]

Considering navigation scenarios in elaborate waters, the high-precision waypoints-based path-following problem of underactuated surface vessel (USV) is investigated by combining the iterative learning control (ILC) and the artificial potential field (APF) in this note. A potential-based dynamic virtual ship (DVS) guidance, considering the challenge of preventing collisions with irregular barriers, is designed with the path following module and the collision avoidance module. A virtual potential field is constructed in the guidance strategy to provide the desired heading signal In particular, the desired heading signal will force that to navigate to one secure location, where the USV approaches the barrier. On the basis of guidance, the iterative control algorithm is selected to design the controller of the system due to the advantages of high accuracy. The dynamic surface control (DSC) and the robust neural damping techniques are utilized to constraint the intrinsic problem of "explosion of complexity" in ILC. The merits of the method involve concise form and controllable precision. Through the Lyapunov criterion, the corresponding closed-loop system is with the semi-global uniformly ultimately bounded (SGUUB) stability. The simulation results are illustrated to verify the effectiveness of the proposed algorithm. • The improved iterative learning control algorithm is proposed for USV. • A potential-based guidance is designed to prevent collisions with irregular barriers. • The proposed algorithm is with merits of concise form and controllable precision. • The closed-loop system is semi-global uniformly ultimately bounded. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive event-triggered control algorithm for sail-assisted unmanned surface vehicle (USV) under nonlinear modified logic virtual ship (LVS) guidance, which addresses the issues of communication load and input saturation constraint. In guidance module, the reference signal generated by LVS guidance is further processed by nonlinear modification rules. That can effectively remove the abrupt phenomenon of actuators. In the control module, a robust adaptive control technique for sail-assisted USV is proposed by fusing adaptive compensation technology and hybrid threshold event-triggered. Unnecessary transmission is reduced between controller and actuator by constructing hybrid threshold event-triggered mechanism. Different from most existing event-triggered mechanism with fixed threshold parameters, threshold parameters in hybrid threshold event-triggered are dynamically adjusted according to the demands of the controller. Furthermore, the compensation effect of sail on the dynamic mechanism is considered. Adaptive parameters of rudder and propeller are constructed to improve the robustness of the closed-loop system. Finally, the theoretical stability of the proposed method is proved by Lyapunov stability theorem, and the control performance is evaluated by simulation platform, which verifies that the scheme has reliable tracking accuracy under time-varying disturbances. • The nonlinear modified LVS principle is proposed to improve sail acting performance. • The hybrid threshold parameter setting can obtain satisfactory resource efficiency. • It can be effectively released the coupling effect of sail force on power mechanism. • The triggered state variables are semi-globally uniform ultimate bounded stable. [ABSTRACT FROM AUTHOR]