Position Constraints Research Articles

Microlensing and the type Ia supernova iPTF16geu

The observed magnifications and light curves of the quadruply imaged iPTF16geu supernova (SN) offers a unique opportunity to study a lens system with a variety of independent constraints. The four observed positions can be used to constrain the macrolens model. The magnifications and light curves at the four SN positions are more useful to constrain microlensing models. We define the macrolens model as a combination of a baryonic component that traces the observed light distribution, and a dark matter halo component. We constrained the macrolens model using the positional constraints given by the four observed images, and compared it with the best model obtained when magnification constraints were included. We found that the magnification cannot be explained by a macrolens model alone, and that contributions from substructures such as microlenses are needed to explain the observed magnifications. We considered microlens models based on the inferred stellar mass from the baryonic component of the macrolens model, and used the observed magnification and light curves to constrain the contribution from microlenses. We computed the likelihood of a variety of macro and micro lens models where we varied the dark matter halo, baryonic component, and microlens configurations. We used information about the position, magnification, and, for the first time, the light curves of the four observed SN images. We combined macrolens and microlens models in order to reproduce the observations; the four SN positions, magnifications, and lack of fluctuations in the light curves. After marginalizing over the model parameters, we found that larger stellar surface mass densities are preferred. This result suggests that the mass of the baryonic component is dominated by its stellar component. We conclude that microlensing from the baryonic component suffices to explain the observed flux ratios and light curves.

Three-dimensional reconstruction for flame chemiluminescence field using a calibration enhanced non-negative algebraic reconstruction technique

The three-dimensional optical diagnostic method has received extensive attention from researchers because of its ability to provide three-dimensional physical information for reactive flow studies such as combustion. Computed tomography of chemiluminescence (CTC) has become a commonly used technique for three-dimensional, transient flame reconstruction purposes. However, due to view number limitations and considerable computational costs, the spatial resolution achieved and accuracy of the reconstruction are less satisfactory compared with applications such as in the medical fields. This investigation focuses on a few methods for improving the experimental and numerical performance of the CTC methods. Firstly, a cylindrical ChArUco calibration target was introduced and a multi-camera calibration method considering the position constraints of cameras was proposed to eliminate the registration error due to the rotation of the calibration target. Furthermore, a sub-voxel method was adopted to improve the spatial resolution of flame reconstructions. Finally, a non-negative algebraic reconstruction technique (NNART) was developed. The algorithm was verified with a simulated jet flame and then was tested against a diffusion jet flame and a swirl flame experimentally.

Containment problem for multi‐agent systems with position and velocity constraints

AbstractThe containment problem is investigated for networked second‐order agents with nonuniform position and nonconvex velocity constraints under directed switching topologies. A distributed containment algorithm is designed for each agent to drive it into the convex target area formed by multiple leaders. The proposed control strategy only utilizes the information of each agent and its neighbor interaction. Theoretical analysis demonstrates that the constrained containment problem can be addressed only if each agent has a directed communication path from at least one leader to it in the union of the graphs. Finally, several numerical simulation results are presented to demonstrate the proposed control schemes.

Optimal Aggressive Constrained Trajectory Synthesis and Control for Multi-Copters

In this paper, we propose a novel time and control effort optimal aggressive trajectory synthesis and control design methodology. The trajectory synthesis is a modified minimum snap design but with specific position and orientation constraints on a multi-copter, such as flying through tight spaces (windows) at specific orientations. The paper also introduces a means to stitch together multiple flight segments, enforce smoothness, and minimize segment times as well as the overall time, thereby resulting in very aggressive and feasible trajectories. A novel analysis for a specific scenario when no yaw angle specifications are provided is conducted, wherein a trade-off results in additional aggressiveness. The control algorithms to follow these trajectories are based on an inverse dynamics approach. Several candidate high-fidelity simulations are performed to verify the effectiveness of the proposed approach.

Iterative Guidance Algorithm for Lunar Soft Landing

A closed-form explicit guidance algorithm for the deceleration, attitude adjustment and final landing phases before lunar probe soft landing is presented in this paper. Guidance with a variable-thrust engine is extended from the iterative guidance mode (IGM) to satisfy the terminal velocity, position, and attitude constraints. The closed form expression, obtained by integrating the acceleration and shutdown time, is analysed to obtain an explicit ex-pression for the velocity and position requirements and vertical touchdown of the spacecraft toward a designated landing site with high terminal accuracy. The influence of the attitude constraint on the motion equation is analysed to calculate the attitude, which is the physical control variable for the guidance loop. The variable thrust IGM formulation ensures the least switch of the thrust magnitude profile based on the analysis result of the residual flight altitude. The simulation results demonstrate that the proposed multi-constrained iterative guidance method can help accomplish an accurate lunar soft landing and that employed the algorithm is simple and easy to implement in engineering practice.

Adaptive Cooperative Control of Multiple Urban Rail Trains with Position Output Constraints

This paper studies the distributed adaptive cooperative control of multiple urban rail trains with position output constraints and uncertain parameters. Based on an ordered set of trains running on the route, a dynamic multiple trains movement model is constructed to capture the dynamic evolution of the trains in actual operation. Aiming at the position constraints and uncertainties in the system, different distributed adaptive control algorithms are designed for all trains by using the local information about the position, speed and acceleration of the train operation, so that each train can dynamically adjust its speed through communicating with its neighboring trains. This control algorithm for each train is designed to track the desired position and speed curve, and the headway distance between any two neighboring trains is stable within a preset safety range, which guarantee the safety of tracking operation of multiple urban rail trains. Finally, the effectiveness of the designed scheme is verified by numerical examples.

Pattern-based autonomous smooth switching control for constrained flexible joint manipulator

The paper proposes a pattern-based control scheme for a class of flexible joint manipulators with unknown dynamics and position constraints. The scheme consists of two phases: (i) online controller adjustment and task pattern identification; (ii) offline pattern recognition and controller calling. In phase (i), the constraint position vectors are transformed into unconstrained variables by using a transformation function. Subsequently, a set of static neural learning controllers are constructed for different reference patterns by employing experience weights obtained from stable adaptive neural control. Moreover, a dynamic estimator is developed to identify different reference patterns. The identified patterns are stored by constant NNs, thereby constructing a trained pattern library by combining with their corresponding static neural learning controllers. In phase (ii), the dynamic residual system is designed to recognize a tested pattern by comparing the size of residual error between the tested pattern and trained patterns. To avoid misjudgment, a novel recognition strategy is proposed by pre-recognition and recognition phases. When the tested pattern is recognized, the relevant experience-based controller strategy is recalled by an autonomous smooth switching technology. The proposed pattern-based control scheme has some advantages including accurate pattern recognition ability, small controller chattering, and highly autonomous control. Simulation studies on a 2-link flexible joint manipulator are implemented to show these advantages of the proposed scheme.

A Fast Circle Detector with Efficient Arc Extraction

Circle detection is a crucial problem in computer vision and pattern recognition. Improving the accuracy and efficiency of circle detectors has important scientific significance and excellent application value. In this paper, we propose a circle detection method with efficient arc extraction. In order to reduce edge redundancy and eliminate crossing points, we present an edge refinement algorithm to refine the edges into single-pixel-wide branchless contour curves. To address the contour curve segmentation difficulty, we improved the CTAR (Chord to Triangular Arms Ratio) corner detection method to enhance corner point detection and segment the contour curves based on corner points. Then, we used the relative position constraint of arcs to improve the circle detection accuracy further. Finally, we verified the feasibility and reliability of the proposed method by comparing our approach with five other methods using three datasets. The experimental results showed that the presented method had the advantages of anti-obscuration, anti-defect, and real-time performance over other methods.

Toward Reactive Walking: Control of Biped Robots Exploiting an Event-Based FSM

Reactivity to unforeseen disturbances is one of the most crucial characteristics for biped robots to walk robustly in the real world. Nevertheless, conventional walking methods generally have limited capability for generating rapid reactions to disturbances, because in these methods it is necessary to wait until the end of the preplanned time period to proceed to the next phase. In this study, to improve reactivity, we develop an event-based finite-state machine (E-FSM) for walking pattern generation. Reactivity is enhanced by determining the state transition conditions of the E-FSM only with time-independent events based on the present robot state. Moreover, in the E-FSM, the robot can walk robustly even when the center of mass and the swing foot motion are disturbed, by employing the capture point concept combined with a new swing foot position constraint. Finally, we propose to control the walking robot by incorporating the E-FSM with an inverse dynamics-based motion/force controller to achieve compliant behavior. This can provide safe responses to external disturbances. The developed method is verified by experiments on a 12-degrees-of-freedom torque-controlled biped robot while it locomotes under irregular external disturbances applied to the upper body or swing leg.

Optimal robust constraints-following control for rail vehicle virtual coupling

This paper puts forward the robust control problem of rail vehicle virtual coupling platoon that is subject to nonlinear and time-varying uncertainties. The uncertainties are caused by external disturbances and parameter variations. To this end, this paper designs a robust controller based on the Udwadia-Kalaba (UK) equation. First, we introduce the concept of virtual coupling and establish the longitudinal dynamics model of the rail vehicle. In order to ensure the control objective of the virtual coupling process, the spatial constraint on position and bidirectional inequality constraints for the spacing error between the marshalling trains are established. After changing the bounded state into the unbounded state through the state transformation, the UK approach can be used. Then, the constraint-following robust controller design is based on the UK approach and Lyapunov stability theory. The controller can render the unbounded state eventual uniform boundedness and uniform ultimate boundedness, which also satisfies the spatial constraint and the bidirectional restriction for the spacing error. Moreover, an optimized design scheme for the tunable parameter of this controller is proposed, which minimizes the control cost and comprehensive index of system performance. Finally, numerical simulations are given to illustrate the effectiveness of the proposed methods.

Adaptive Cruise Control of Virtual Coupled Trains Based on Sliding Mode

In this paper, the adaptive cruise control method for the virtually coupled train set (VCTS) in rail transit is proposed. First of all, a leader-following VCTS dynamics model is constructed by analyzing the dynamic evolution of VCTS in a real-world environment, taking into account uncertain parameters, unknown disturbances and controller input saturation. Next, to cope with the position and speed constraints, the position artificial potential field function and the speed barrier function are embedded into the designed sliding manifold. And a novel adaptive cruise control protocol is designed, which can simultaneously deal with uncertain resistance parameters and unknown disturbances while tracking the desired cruise speed and maintaining the desired distance. Based on Lyapunov stability theory, the proposed control protocol guarantees the ultimate boundedness of all subsystems. Finally, the simulation results verify the effectiveness of the theoretical analysis.

A Unified Approach for Finite-Time Global Stabilization of Affine, Rigid, and Translational Formation

This article studies the multiagent control problem for affine, rigid, and translational formation, with the aim of developing a unified distributed control strategy for global and finite-time convergence. Global stabilization of rigid formation in arbitrary dimensional spaces still remains open and challenging. This article provides a general solution to this open problem based on the sliding mode control idea. The control law design consists of two parts: the main control force regulates the trajectories of all agents to reach a sliding surface defined by an affine formation space in finite time and remain in it thereafter; the extra control force governs certain chosen leader agents towards the desired formation in the sliding surface. The article then presents in detail two approaches for designing the extra control force, one based on distance constraints and the other based on relative position constraints. For the first time, the proposed sliding mode formation control laws solve the open problem of (almost) global and finite-time stabilization of affine, rigid, and translational formations in any dimensional space. Simulation results are provided to illustrate the effectiveness of the proposed control schemes.

Solving the constrained Single-Row Facility Layout Problem with Integer Linear Programming

The Single-Row Facility Layout Problem (SRFLP) is one of the most studied facility layout problems in the literature. It asks for an optimal arrangement of departments with given lengths on a row such that the weighted sum of all centre-to-centre distances between department pairs is minimised. Real-world facility layouts may require taking different restrictions on the placement of departments into account, such as arrangement on a fixed position, pairwise placement, or precedence considerations. Therefore, we consider the constrained Single-Row Facility Layout Problem (cSRFLP) that additionally considers positioning, ordering, and relation constraints on single-row facility layouts. In this work, we suggest a new Integer Linear Programming (ILP) formulation for the cSRFLP, which outperforms the best available exact approach in literature. In an extensive computational study, we apply our ILP approach as well as an LP-based cutting plane algorithm on SRFLP and cSRFLP instances from the literature. We provide optimal cSRFLP layouts as well as strong lower bounds for instances with up to 42 departments. Further, we present new results for SRFLP instances from the literature. Additionally, we demonstrate the individual impact of the constraint sets on the run times of cSRFLP instances to emphasise further research on this rarely studied practice-oriented Facility Layout Problem.

Piecewise Sundman Transformation for Spacecraft Trajectory Optimization Using Many Embedded Lambert Problems

Direct optimization of many-revolution spacecraft trajectories requires path discretization into segments. The well-known Sundman transformation guides the development of a piecewise function that regularly varies flight time for each segment. This flight-time function approximates the regularization effect on the dynamics for a spatially even discretization, conveniently not changing the independent variable from time. The flight-time functions are analyzed in the following two ways: first, in a trajectory propagation problem, and second, in several optimization problems. First, an eccentric Keplerian orbit is propagated to reveal similar behavior between flight-time functions and dynamic regularization, increasingly so for more segments per orbit. Second, the piecewise transformation is applied to trajectory optimization problems that embed the Lambert boundary value problem for every segment, defined here as the embedded boundary value problem (EBVP) technique. This EBVP technique performs favorably to a similar, state-of-the-art, optimization technique using a Kepler solver. The improvement is a result of eliminating explicit enforcement of position and velocity constraints by the optimizer. The EBVP technique is further enhanced by the approximate Sundman function by using an exponent of , enabling otherwise infeasible fuel- and energy-optimal problems. The largest solution contains up to 12,287 segments and 512 revolutions, and significantly varies semimajor axis and eccentricity.

Capture and detumble of a non-cooperative target without a specific gripping point by a dual-arm space robot

This paper focuses on the control strategy of a dual-arm space robot to capture and detumble a non-cooperative satellite without a specific gripping point. First, an elastic hemispherical claw was designed to reduce the collision impacts and adjust the capture position, and its contact dynamics and capture ability were verified by ground experiments. Analysis of the position constraints led to the proposal of a compliant control scheme to achieve stable capture without a contact-force sensor. Subsequently, a modified adaptive sliding mode based prescribed trajectory tracking control (PTTC) and null space intersection approach was proposed to achieve target detumbling under the actuator constraints. The control system stability was analyzed via the Lyapunov method. Finally, numerical simulations were employed to validate the effectiveness and correctness of the strategy. Results showed that, a large inertia target could be steadily captured and detumbled within 80 s.

Containment control with delays, velocity constraints and position constraints in directed changing networks

This paper discusses a containment problem of multi-agent networks with inconsistently bounded communication time delays in directed changing topologies, where the velocity and position of each follower are, respectively, confined in a nonconvex set and a convex set during its movement. A projection-based distributed control protocol is developed to drive all followers into a target convex area spanned by some given leaders, and a sufficient condition for achieving the constrained containment is established. It is proven that the constrained containment problem can be solved by the developed control protocol only if every follower can communicate with no less than one stationary leader directly or indirectly in the union of the communication topologies. Eventually, a representative simulation experiment is performed to verify the main results.

Model Analysis of Sandstone Tunnel Cracking Based on Fracture Mechanics Theory and Sensor Testing Technology Research

In this paper, we survey sandstone tunnels using sensor testing technology and conduct an in-depth analysis and research on the model of sandstone tunnel cracking based on the theory of fracture mechanics. This paper systematically investigates the static mechanical properties, energy evolution and distribution law, acoustic emission monitoring, and digital image correlation methods of intact and jointed rock chamber enclosures (including parallel jointed rock chamber enclosures and cross jointed rock chamber enclosures) under static loads, based on physical simulation test methods and combined with other technical means such as acoustic emission monitoring and digital image correlation methods. In this paper, the effects of parallel and cross-joint angles on the static mechanical properties, energy evolution and distribution, acoustic emission variability, progressive destabilization, and their mechanisms are compared and analyzed. This paper takes fiber Bragg grating (FBG) sensing theory and technology research as a breakthrough, relies on major underground engineering geohazard model tests, and proposes a grating spectral reconstruction theory based on the wavelength position constraint of the spectral center and its improvement based on an in-depth analysis of the influence of fiber grating intrinsic parameters and strain distribution on the reflection spectral properties. Based on an in-depth analysis of the influence of spectral center wavelength location and strain distribution on the reflectance spectral properties, we propose the grating spectral reconstruction theory based on the spectral center wavelength location constraint and its improved genetic algorithm optimization method; realize the fast and accurate identification and rejection of the melancholy effect of fiber grating; propose the sensor numerical simulation optimization design method; develop the high sensitivity seepage pressure sensor, new strain sensor, target flow sensor, microdisplacement sensor, and multipoint displacement sensor; and build a large capacity, multi-parameter fiber grating real-time monitoring network.

Transmit-Receive Beamforming for Distributed Phased-MIMO Radar System

Distributed phased Multiple-Input Multiple-Output (phased-MIMO) radar system consisting of separated subarrays possesses a high angle resolution but with sharing high sidelobes. This paper therefore focuses on the design of a virtual low-sidelobe beampattern in distributed phased-MIMO radar. An iterative framework with respect to subarray layout and receive weighting coefficients is proposed to minimize beampattern Peak Sidelobe Level (PSL) accounting for practical position constraints as well as the mainlobe level restriction. In each iteration, an efficient cyclic optimization algorithm based on the Coordinate Descent (CD) framework is developed to seek for the subarray layout through splitting high dimensional layout optimization problem into multiple one-dimensional optimization problems, and the SemiDefinite Relaxation (SDR) technique and rank one approximation are explored to design weighting coefficients. Numerical simulations are provided to assess the performance of the proposed algorithms in term of the achieved beampattern under different constraints and parameter settings.

Design method of a single degree-of-freedom planar linkage bionic mechanism based on continuous position constraints

Single degree-of-freedom (DOF) planar linkage mechanism has been widely used in bio-inspired robots because of its simple control. However, designing a single DOF mechanism to meet the complex motion law of creatures is difficult, and the multiple variables of six- or eight-bar mechanism further increase the design difficulty. A design method of single DOF planar linkage bionic mechanism is proposed in this paper. Through the continuous constraints on the position of all reference points with constraint descent method, the requirements of the bionic mechanism in shape, motion trajectory, and posture are met. As for the mechanism by which reference point coordinates cannot be expressed as the analytical solution of the driving angle, a single DOF mechanism is equivalent to a double DOF mechanism containing additional optimization variables, which further improves the design efficiency. For example, the design process of six- and eight-bar bionic mechanisms is given, confirming the feasibility of the method. Then, the effects of the constraint conditions on the design process are analyzed in detail. This study provides a reference for the design of bio-inspired robots.

PANTHER: Perception-Aware Trajectory Planner in Dynamic Environments

This paper presents PANTHER, a real-time perception-aware (PA) trajectory planner for multirotor-UAVs (Unmanned Aerial Vehicles) in dynamic environments. PANTHER plans trajectories that avoid dynamic obstacles while also keeping them in the sensor field of view (FOV) and minimizing the blur to aid in object tracking. The rotation and translation of the UAV are jointly optimized, which allows PANTHER to fully exploit the differential flatness of multirotors to maximize the PA objective. Real-time performance is achieved by implicitly imposing the underactuated dynamics of the UAV through the Hopf fibration. PANTHER is able to keep the obstacles inside the FOV 7.9 and 1.5 times more than non-PA approaches and PA approaches that decouple translation and yaw, respectively. The projected velocity (and hence the blur) is reduced by 18% and 34%, respectively. This leads to average success rates three times larger than state-of-the-art approaches in multi-obstacle avoidance scenarios. The MINVO basis is used to impose low-conservative collision avoidance constraints in position and velocity space. Finally, extensive hardware experiments in unknown dynamic environments with all the computation running onboard are presented, with velocities of up to 5.8 m/s, and with relative velocities (with respect to the obstacles) of up to 6.3 m/s. The only sensors used are an IMU, a forward-facing depth camera, and a downward-facing monocular camera.