Manipulation Problem Research Articles

Fixed-time adaptive fuzzy control with prescribed tracking performances for flexible-joint manipulators

In this paper, we study the tracking control problem of flexible-joint manipulators with uncertain unstructured dynamics, and develop a prescribed fixed-time solution scheme by combining direct adaptive fuzzy control design with a class of smooth functions. With our scheme, only one adaptive law needs to be calculated online, and also there are no complicated terms, e.g., the partial derivatives of some multivariable functions, involved in virtual controllers and the actual control input, which show that the raised scheme is computationally attractive. Moreover, the boundedness of all closed-loop signals, and the fixed-time convergence of tracking error to a prescribed interval can be established through a rigorous proof, and the obtained results are further confirmed by simulation tests.

Learn to flap: foil non-parametric path planning via deep reinforcement learning

To optimize flapping foil performance, in the current study we apply deep reinforcement learning (DRL) to plan foil non-parametric motion, as the traditional control techniques and simplified motions cannot fully model nonlinear, unsteady and high-dimensional foil–vortex interactions. Therefore, a DRL training framework is proposed based on the proximal policy optimization algorithm and the transformer architecture, where the policy is initialized from the sinusoidal expert display. We first demonstrate the effectiveness of the proposed DRL-training framework, learning the coherent foil flapping motion to generate thrust. Furthermore, by adjusting reward functions and action thresholds, DRL-optimized foil trajectories can gain significant enhancement in both thrust and efficiency compared with the sinusoidal motion. Last, through visualization of wake morphology and instantaneous pressure distributions, it is found that DRL-optimized foil can adaptively adjust the phases between motion and shedding vortices to improve hydrodynamic performance. Our results give a hint of how to solve complex fluid manipulation problems using the DRL method.

Kinematics analysis of a novel hybrid manipulator for optomechanical modules assembly

A novel hybrid manipulator is proposed in this work, in order to assemble optomechanical modules in an inertial confinement fusion facility (SG-Ⅲ). Differ from general serial and parallel manipulators, both the inverse and forward kinematics problems of hybrid manipulators are difficult to be solved. Based on an analytic method, the position and orientation mapping functions between the optomechanical module and the parallel manipulators are established, and then the method of transformation matrix is employed to obtain the inverse kinematics solution. The forward kinematics of this hybrid manipulator is highly nonlinear and coupled, so a back propagation neural network using all class one network strategy is trained to approximate the mapping relation. Aiming to improve the accuracy, the network is split into two sub-networks corresponding to the natural property of the outputs. In the end, an improved back propagation neural network is proposed to optimize the network, results illustrate that the kinematic accuracy is increased significantly.

An efficient solver for the inverse kinematics of cable-driven manipulators with pure rolling joints using a geometric iterative approach

The inverse kinematics (IK) problem of cable-driven manipulators with pure rolling joints (CDM-PRJs) presents unique challenges due to the equal angle constraints and strict joint limits. These factors render existing IK solvers ineffective or result in substantial degradation of their performance. To address these challenges, we propose a three-phase geometric iterative method to efficiently solve the IK problem for CDM-PRJs, which is a variant of the forward and backward reaching inverse kinematics method. Our method begins by establishing a surrogate model for CDM-PRJs to handle the equal angle constraints. Subsequently, we introduce a geometric iterative approach comprising a forward reaching phase, a backward reaching phase, and a state update phase. Additionally, we devise two novel measures, the random disturbance measure and the branch change measure, to effectively address deadlock situations and asymmetric joint limits, respectively. Simulation results demonstrate that our method surpasses the inverse Jacobian method and the sequential quadratic programming method in terms of success rate and computational efficiency. Furthermore, our method exhibits generality across various CDM-PRJs.

Fixed-time nonsingular terminal sliding mode control for trajectory tracking of uncertain robot manipulators

Fixed-time nonsingular terminal sliding mode control for trajectory tracking of uncertain robot manipulators

Controlled transport of fluid particles by microrotors in a Stokes flow using linear transfer operators

The manipulation of a collection of fluid particles in a low Reynolds number environment has several important applications. As we demonstrate in this paper, this manipulation problem is related to the scientific question of how fluid flow structures direct Lagrangian transport. We investigate this problem of directing the transport by manipulating the flow, specifically in the Stokes flow context, by controlling the strengths of two rotors fixed in space. We demonstrate a novel dynamical systems approach for this problem and apply this method to several scenarios of Stokes flow in unbounded and bounded domains. Furthermore, we show that the time-varying flow field produced by the optimal control can be understood in terms of dynamical structures such as coherent sets that define Lagrangian transport. We model the time evolution of the fluid particle density using finite-dimensional approximations of the Liouville operators for the microrotor flow fields. Using these operators, the particle transport problem is framed as an optimal control problem, which we solve numerically. This framework is then applied to the problem of transporting a blob of fluid particles in domains with different boundary conditions: free space, near to a plane wall, in a circular confinement, and the transport of two distributions of particles to a common target. These examples demonstrate the effectiveness of the proposed framework and also shed light on the effects of boundaries on the ability to achieve a desired fluid transport using a rotor-driven flow.

Flatness-based control in successive loops for robotic manipulators and autonomous vehicles

ABSTRACT The control problem for the multivariable and nonlinear dynamics of robotic manipulators and autonomous vehicles is solved with the use of a flatness-based control approach which is implemented in successive loops. The state-space model of these robotic systems is separated into two subsystems, which are connected between them in cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system and control about it can be performed with inversion of its dynamics as in the case of input–output linearised flat systems. The state variables of the second subsystem become virtual control inputs for the first subsystem. In turn, exogenous control inputs are applied to the first subsystem. The whole control method is implemented in two successive loops and its global stability properties are also proven through Lyapunov stability analysis. The validity of the control method is confirmed in two case studies: (a) control of a 3-DOF industrial rigid-link robotic manipulator and (b) control of a 3-DOF autonomous underwater vessel. The novel control method can simplify significantly the solution of the nonlinear control problem for robotic manipulators and vehicles. Unlike global linearisation-based control schemes, the proposed flatness-based method in successive loops does not need any changes in state variables of complicated state-space model transformations.

AnyFace++: A Unified Framework for Free-style Text-to-Face Synthesis and Manipulation.

Human faces contain rich semantic information that could hardly be described without a large vocabulary and complex sentence patterns. However, most existing text-to-image synthesis methods could only generate meaningful results based on limited sentence templates with words contained in the training set, which heavily impairs the generalization ability of these models. In this paper, we define a novel 'free-style' text-to-face generation and manipulation problem, and propose an effective solution, named AnyFace++, which is applicable to a much wider range of open-world scenarios. The CLIP model is involved in AnyFace++ for learning an aligned language-vision feature space, which also expands the range of acceptable vocabulary as it is trained on a large-scale dataset. To further improve the granularity of semantic alignment between text and images, a memory module is incorporated to convert the description with arbitrary length, format, and modality into regularized latent embeddings representing discriminative attributes of the target face. Moreover, the diversity and semantic consistency of generation results are improved by a novel semi-supervised training scheme and a series of newly proposed objective functions. Compared to state-of-the-art methods, AnyFace++ is capable of synthesizing and manipulating face images based on more flexible descriptions and producing realistic images with higher diversity.

Reinforcement learning-based adaptive tracking control for flexible-joint robotic manipulators

<p>In this paper, we investigated the optimal tracking control problem of flexible-joint robotic manipulators in order to achieve trajectory tracking, and at the same time reduced the energy consumption of the feedback controller. Technically, optimization strategies were well-integrated into backstepping recursive design so that a series of optimized controllers for each subsystem could be constructed to improve the closed-loop system performance, and, additionally, a reinforcement learning method strategy based on neural network actor-critic architecture was adopted to approximate unknown terms in control design, making that the Hamilton-Jacobi-Bellman equation solvable in the sense of optimal control. With our scheme, the closed-loop stability, the convergence of output tracking error can be proved rigorously. Besides theoretical analysis, the effectiveness of our scheme was also illustrated by simulation results.</p>

Formation Control of Cooperative-Competitive Robot Manipulators with Inter-agent Constraints

This paper addresses the distributed formation control problem of networked robot manipulators in end-effector coordinates. We propose a distributed bipartite formation controller that guarantees collision avoidance and maximum distance maintenance for cooperative and competitive manipulators’ end-effectors. In the considered setting, two groups of manipulators are formed and reach bipartite consensus. On the other hand, the end-effectors in the same group achieve formation. We design a gradient-based control law using barrier-Lyapunov functions to ensure that the constraints on the end-effectors are satisfied. Moreover, we establish asymptotic stability of the bipartite formation manifold. Finally, we illustrate our theoretical results via numerical simulations.

Research of the robot-manipulators singularity

The article is devoted to the problem of the robot manipulators —singularities, the presence of their special configurations, in which some degrees of freedom are lost, which limits the ability to control the manipulator and reduces its accuracy. Eight three-link robotic manipulators, consisting of links of various types, are described and their singularities are analyzed. Keywords singularity, robot-manipulator, technological complex, inverse kinematics, analysis

Vibration control of an experimental flexible manipulator against input saturation

Dear Editor, This letter considers the control problem of an experimental flexible manipulator in position tracking, vibration suppression, and saturation compensation. Based on the backstepping technology and a Nussbaum function, we develop an anti-windup control to restrain the manipulator's vibration, realize the desire trajectory tracking, and eliminate the saturation. Applying the Lyapunov's method, the control system's stability with the proposed control is proved. Finally, the practicability and effectiveness of the control methodology are verified on a Quanser experiment platform.

Trajectory planning of vibration suppression for hybrid structure flexible manipulator based on differential evolution particle swarm optimization algorithm

A differential evolution particle swarm optimization algorithm is proposed to address the vibration problem of a hybrid structure flexible manipulator after motion and stop. Firstly, the errors in the modeling process of the flexible manipulator were corrected, and its state variables were decomposed to establish dynamic and kinematic models. A sliding mode controller was then designed to track the trajectory. To find the optimal trajectory, a mapping function was constructed, and non-uniform interpolation points were selected. A normal distribution function was used to select discrete interpolation points, and the cubic spline interpolation was used to fit the trajectory. To prevent the particle swarm optimization algorithm from falling into local optima, the mutation and crossover operators of the differential evolution algorithm are incorporated into the algorithm, thereby expanding the search range. The effectiveness of this improved method was verified by comparing it with traditional particle swarm optimization algorithms. This study provides a new trajectory planning approach for the motion control of a hybrid structured flexible manipulator and has important practical significance.

Fast and High Accuracy CSM Control Under Manipulator Actuator Fault Conditions

The dynamic performance metrics of manipulators are decreased when actuator faults happen. To ensure the response speed and improve the tracking accuracy under actuator fault, the complementary sliding mode (CSM) controller is designed in this article. Different from the general sliding mode control (SMC), there are two sliding surfaces in the CSM controller design process, and the mathematical complexity of the controller is simplified through the relationship of the two complementary sliding surfaces, which helps to reduce the response time. Also, the structural parameter changes and disturbance existed in the real manipulator system are also considered in this paper by introducing uncertainty item during modeling, thus the robustness of the controller is improved. In the experimental part, the control effect of the CSM proposed is compared with that of the conventional sliding mode method. Normal conditions and actuator constant deviation fault of the manipulator are studied. The results show that the CSM has superiority in control accuracy and response speed. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In recent years, the control problem of manipulators under complex conditions has attracted particular attention. The key to the design of the controller lies in its stability while keeping the tracking performance. Many complex auxiliary methods are proposed to guarantee this, but a few can achieve acceptable performance. This article proposed the complementary sliding mode controller design method, in which two sliding surfaces are used to simplify the proof in the controller design. We choose the error variables to construct the sliding surface, so the CSM could handle several actuator faults very well, which enhances the adaptive ability of the algorithm.

Douglas–Rachford algorithm for control-constrained minimum-energy control problems

Splitting and projection-type algorithms have been applied to many optimization problems due to their simplicity and efficiency, but the application of these algorithms to optimal control is less common. In this paper we utilize the Douglas–Rachford (DR) algorithm to solve control-constrained minimum-energy optimal control problems. Instead of the traditional approach where one discretizes the problem and solves it using large-scale finite-dimensional numerical optimization techniques we split the problem in two subproblems and use the DR algorithm to find an optimal point in the intersection of the solution sets of these two subproblems hence giving a solution to the original problem. We derive general expressions for the projections and propose a numerical approach. We obtain analytic closed-form expressions for the projectors of pure, under-, critically- and over-damped harmonic oscillators. We illustrate the working of our approach to solving not only these example problems but also a challenging machine tool manipulator problem. Through numerical case studies, we explore and propose desirable ranges of values of an algorithmic parameter which yield smaller number of iterations.

Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation

This article addresses an autonomous manipulation problem for an underwater vehicle-manipulator system (UVMS) operating in a free-floating way while subjecting to unknown continuous disturbance. More specifically, a composite control scheme composed of disturbance observer (DOB), predictor model network (PM-Net), and nonlinear model predictive control (NMPC), is devised to improve the control performance of UVMS (i.e., unicycle-like UVMS actuated only in the surge, heave, and yaw for vehicle body) in the case of disturbance, model mismatch, and input saturation. A RBF-DOB is formulated by combining a DOB and a Radial Basis Function (RBF) neural network to estimate disturbance at the current step. Then, the PM-Network, composed of a disturbance predictor network and state predictor network, is developed based on long short-term memory (LSTM) network that predicts UVMS state sequences considering model mismatch and disturbance. The NMPC is deployed as a feedback control law to endow the input saturation of the UVMS and produce optimal control action. Compared with conventional DOB control methods using feed-forward compensation of disturbance, the primary merit of the proposed approach is that the disturbance estimated by RBF-DOB is utilized in the PM-Net to predict future UVMS state sequences, which are exploited on the NMPC’s receding optimization. RGB0,0,0Finally, realistic simulation and relevant experiment are conducted to demonstrate the effectiveness of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation behind this article is the autonomous manipulation of an underwater vehicle-manipulator system subjected to unknown disturbance. However, it is not always feasible or straightforward to obtain the external disturbance and unmodeled dynamics for designing robust controllers. On the one hand, how to manipulate the disturbance into the designed controller to generate optimal control action rather than by using feed-forward compensation. On the other hand, the control input saturation often occurs in the UVMS control, especially under the disturbance rejection conditions, where it should be considered in the controller design. Currently, the predominant methods for UVMS control lack a control scheme that provides a complete and credible control strategy that takes the aforementioned issues into consideration. Motivated by the above analysis, this study provides a composite control scheme to deal with the dynamic uncertainties, unknown disturbance, and input saturation. RGB0,0,0The results of realistic simulation and relevant experiments demonstrate the effectiveness of the proposed method. Hopefully, our control method can provide valuable theoretical and technical guidance to practicing marine engineers for controller design.

A blockchain-based framework for carbon management towards construction material and product certification

As one of the biggest resource consumers and carbon emitters, the construction industry plays a crucial role in global carbon reduction. Carbon certification or labelling schemes are efficient ways to assess and report the carbon footprints of construction materials and products (CMPs), providing the foundation for carbon management at the CMP level. However, existing carbon management for CMP certification relies heavily on traditional centralized data management tools, which suffer from data non-transparency and manipulation problems, making carbon footprints unreliable and hard to track. Therefore, benefiting from the immutability and traceability of blockchain, this paper introduces a distributed solution for transparent and secure carbon management towards CMP certification. Contributions lie in three aspects: (1) a Green Product Chain (GPChain) framework is proposed based on blockchain. This framework provides a distributed and transparent carbon data-sharing environment, enabling reliability and traceability during certification. (2) A blockchain data model is developed considering the privacy of carbon data for CMP certification. Besides, a privacy-preserving carbon data-sharing strategy is designed for pre-processing different sensitive data before being transferred to the blockchain. (3) GPChain smart contracts are developed to granularly control user interactions with blockchain and automatically generate distributed carbon footprint records. Results show that (1) GPChain’s feasibility of supporting carbon management for GMP certification and (2) the acceptable performance of GPChain smart contracts during operations.

Интерпретационное искажение прошлого как способ манипуляции историческим сознанием современной российской молодежи

The article is devoted to the problem of manipulation of historical consciousness of modern Russian youth. The aim of the present study is to analyze the interpretive distortion of the past as a means of influencing the minds of the new generation of Russian citizens. The article analyses the historical prerequisites and directions of large-scale influence of the West on the historical consciousness of Russians. Its causes and forms leading to the destruction of the civic position of young people are analyzed. Conclusion dwells upon the fact that the con-structivist approach to understanding history and a set of technical manipulative tools that serve the designated paradigm are becoming the leading ones in this respect. The struggle against such attitudes today comes to the forefront in connection with the ideological war against Russia. The results of the work can be useful in scien-tific research and educational process in the field of Russian history, social philosophy, political science, soci-ology.

Finite-Time Tracking Control of a Flexible Link Manipulator Based on an Extended State Observer

In this paper, the finite-time trajectory tracking control problem of a flexible link manipulator (FLM) system with unknown parameters is investigated in joint space. An adaptive nonsingular terminal sliding mode (ANTSM) controller based on an extended state observer (ESO) is proposed to ensure that the tracking error converges to a small neighborhood of zero. Firstly, an adaptive ESO is introduced, which is used to estimate unknown system parameters, including the unknown rigid-flexible coupling coefficient and the unknown control gain. Then, an ESO based on the parameters estimated above is proposed to estimate the unmodeled dynamics and external disturbances of the system in real-time. Finally, an ANTSM controller based on ESO is studied to achieve finite-time trajectory tracking control and vibration suppression without any prior knowledge of system uncertainties and external disturbances. The finite-time convergence ability of the closed-loop system is proved by Lyapunov theory. Experimental results on the Quanser Flexible Link System verify the effectiveness of the proposed controller.

Direct positional kinematics problem of the RRRRT manipulator in the maple software environment

This article presents the direct positional problem of the RRRRT manipulator created by the authors of the 3D model and its movement using the Maple software environment. In this paper, the positional kinematics problem of this manipulator is studied in detail. To find the kinematic characteristics of the manipulator, the Denavit-Hartenberg and Newton-Euler methods were rationally used. The results were obtained in the Maple software environment, which allows you to obtain the results of kinematic characteristics in the form of 3D graphs. Such graphs allow you to visually see how the modules and directions of the given parameters of the manipulator in the graphs change in space, depending on the position of the manipulator in space.