Link Manipulator Research Articles

Dynamic robust path-following control of UVMS subject to manipulator disturbance

This study addresses path-following control issue of underwater vehicle-manipulator systems (UVMS) in the presence of manipulator disturbances. It considers disturbance forces arising from manipulator position changes, including restorative forces and coupling forces, to achieve precise UVMS path-following control. By analysing the variations in the center of mass and buoyant center of manipulator links during motion, the corresponding restorative torque is deduced, and disturbance forces are calculated. Additionally, joint coupling forces generated during manipulator startup, braking, and rotation are taken into account. These aspects collectively yield the expression for disturbance forces. Subsequently, adaptive sliding mode control are employed to achieve accurate control of the UVMS system. This study effectively addresses the issue of UVMS body control under manipulator disturbances. By analysing the motion of manipulator links, the disturbance forces exerted by the manipulator on the UVMS are identified, offering insights for similar control challenges arising from manipulator disturbances. Simulation results are conducted to show the effectiveness of the proposed control method.

Application of the crow search algorithm to achieve an optimal solution for a double link manipulator

Robotic manipulators are mechanical devices that are electronically controlled and have several linkages that allow them to do specific jobs under specified situations. Here, a double-link manipulator is explored and modified using uncertainty factors that impact the robot manipulator's performance in monitoring the angular position. Unlike, the standard Lagrangian technique is employed to derive the motion equations and calculate the performance of the Two Link Robot Manipulator. Because the motion equation involves a nonlinear system of ordinary differential equations, getting to the target place is challenging. Meta-heuristic search algorithms were standard methodologie to solve any optimization problem, mainly real-time problems. Meta-heuristic algorithms depend upon the natural behaviour of the animals or birds. This paper uses a Crow search algorithm to minimize the trajectory and position of the double link manipulator. It also demonstrates how the Crow search algorithm can easily be used to solve optimal control problems (OCP) with constraints in MATLAB simulation. The Crow search algorithm depends on the crow's behaviour of keeping their excess food in a safe place and getting it as needed. The Crow search algorithm (CSA) was compared with particle swarm optimization (PSO), differential evolution (DE), and Grey Wolf Optimization (GWO). The double link manipulator's fundamental Model's performance is computed to find a solution. The Crow search method has produced notable results in terms of performance, i.e. 25 % to 98 % better, compared to other algorithms such as DE, PSO, and GWO.

Hybrid controller with neural network PID/FOPID operations for two-link rigid robot manipulator based on the zebra optimization algorithm.

The performance of the robotic manipulator is negatively impacted by outside disturbances and uncertain parameters. The system's variables are also highly coupled, complex, and nonlinear, indicating that it is a multi-input, multi-output system. Therefore, it is necessary to develop a controller that can control the variables in the system in order to handle these complications. This work proposes six control structures based on neural networks (NNs) with proportional integral derivative (PID) and fractional-order PID (FOPID) controllers to operate a 2-link rigid robot manipulator (2-LRRM) for trajectory tracking. These are named as set-point-weighted PID (W-PID), set-point weighted FOPID (W-FOPID), recurrent neural network (RNN)-like PID (RNNPID), RNN-like FOPID (RNN-FOPID), NN+PID, and NN+FOPID controllers. The zebra optimization algorithm (ZOA) was used to adjust the parameters of the proposed controllers while reducing the integral-time-square error (ITSE). A new objective function was proposed for tuning to generate controllers with minimal chattering in the control signal. After implementing the proposed controller designs, a comparative robustness study was conducted among these controllers by altering the initial conditions, disturbances, and model uncertainties. The simulation results demonstrate that the NN+FOPID controller has the best trajectory tracking performance with the minimum ITSE and best robustness against changes in the initial states, external disturbances, and parameter uncertainties compared to the other controllers.

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.

Uncertainty and velocity observer-based predefined-time nonsingular terminal sliding mode control of the underwater robot manipulators

This paper introduces an observer-based predefined-time nonsingular terminal sliding mode control to the position tracking control of the n-degree-of-freedoms underwater robot manipulators subject to the uncertainty compensation and sensor reduction. The proposed sliding surface has only the sliding phase, while the reaching phase is eliminated using a continuous augmented function. Besides, the sliding phase is predefined-time, where it is independent of the initial conditions and control parameters. As a result, it has led to the development of a predefined-time control scheme, in which not only its convergence time is fast, but also (due to the elimination of the reaching phase) the effect of uncertainties in this phase is eliminated. Naturally, there is a wide range of uncertainties such as structured-unstructured uncertainties and/or un-modeled dynamics, ocean current, waves, etc., in the underwater robot manipulators and underwater conditions. Therefore, the proposed predefined-time nonsingular terminal sliding mode control is combined with a finite-time observer to estimate the underwater robot manipulator's joint velocity and eliminate the destructive effect of existing uncertainties. Under this combination, the stability analysis could guarantee predefined-time global asymptotic stability of the system in the presence of existing uncertainties. Simulation results are conducted on a 2-link underwater robot manipulator to validate the proposal.

Performance analysis of input shaped model reference adaptive control for a single-link flexible manipulator

Motion control for flexible link manipulators will have a great influence on their overall performance. Conventional control systems have the problem that they cannot compensate for the presence of uncertainty due to a variety of factors such as a change in the system itself-payload variations, degradation and modelling uncertainty. In addition, the underdamped structure of these systems entails motion-induced transient deflection and residual vibration. On the contrary, adaptive control, in particular Model Reference Adaptive Control (MRAC), has therefore been proposed to handle problems of this type dealing with other systems such as cranes, steering stability control for ground vehicles, airplanes and so on. This study presents a review and discussion on the MRAC and some individual issues of MRAC for these flexible link manipulators are addressed to specify: the state tracking error, the limitation of the adaptation values corresponding to the control gains and the control effort. Dealing with the last one, this work proves that shaping the command input to a Model Reference Adaptive Control (IS-MRAC) reduces the control effort necessary for the plant to follow the reference model and also mitigates the detrimental effects of flexibility. The IS-MRAC is implemented in a Single-Link Flexible Manipulator whose natural frequencies, experimentally and analytically estimated using the Transfer Matrix Method plus symbolic computation, vary significantly depending on payload mass and position. To this structured or parametric uncertainty, the proposed Lyapunov control law using the states associated with the low mode is designed for asymptotic stability and accommodates correctly. The state tracking, vibration suppression and control effort reduction performances of the proposed IS-MRAC combined controller are analysed via numerical simulations and experiments.

A PSO optimized RBFNN and STSMC scheme for path tracking of robot manipulator

This article presents the design of super twisting sliding mode control (STSMC) based on radial basis function neural network (RBFNN) for path tracking of two link robot manipulator. The proposed controller is utilized to guarantee and achieve that the surface of sliding can be in equilibrium point within a short time and avoid the problem of chattering at the output. The Lyapunov theory is used in presenting a new convergence proof. Also, the particle swarm optimization (PSO) algorithm is employed to give the optimal parameter values of the proposed controller. Simulation results explain the goodness of the proposed control method for trajectory tracking of 2-link robot manipulator when compared with SMC strategy. Results demonstrate that the the percentage improvement in mean square error (MSE) of using STSMC when compared with the standard SMC are 15.36%, 16.94% and 12.92%, for three different cases respectively.

High-Precision Tip Tracking of a Flexible Link Manipulator Using Two-Time Scale Adaptive Robust Control

A flexible link manipulator (FLM) has advantages of greater payload-to-manipulator-weight ratio, safer operation, and lower energy consumption compared with the rigid manipulator, which has promising demands in various industrial and aerospace applications. However, the internal dynamics of the system is easy to be unstable due to its nonminimum phase characteristics, and there exists severe parametric uncertainties and uncertain nonlinearities in its dynamics, which has brought many difficulties in the precise tip tracking control and effective vibration suppression. In this article, the entire mathematical model of the FLM is established with assumed mode method and actuator dynamics. Then, the system is decomposed into a slow subsystem and a fast subsystem through introducing an adjustable time-scale factor according to a new output redefined dynamics with uncertainties from truncated vibration modes and unknown disturbances of system. A two-time scale adaptive robust control (TTSARC) scheme, which consists of an adaptive robust control for the slow subsystem and a state feedback control for the fast subsystem, is proposed to effectively handle parametric uncertainties and uncertain nonlinearities as well as improve behavior of internal dynamics. Moreover, the clear connection of achievable performances and control parameters based on the stability analysis of the entire system is addressed. The experimental results indicate that precise tip tracking with small link deflection for the FLM working on different conditions can be achieved with the proposed TTSARC.

Application of direct and inverse kinematics and dynamics in motion planning of manipulator links

For the synthesis of manipulators and robots, an accurate analysis of the movements of the individual links is essential. This thesis deals with motion planning of the effector of a multi-linked manipulator. An important topic in this area is the orientation and position of links and kinematic pairs in space. In particular, attention should be paid to the position of their endpoint as well as other significant points. Trajectory planning allows the manipulator to perform complex tasks, such as picking and placing objects or following a particular path in space. Overall, trajectory planning of a multibody manipulator involves a combination of direct and inverse kinematics calculations, as well as control theory and optimization techniques. It is an important process enabling manipulators to perform complex tasks such as assembly, handling and inspection. In the design of robot kinematic structures, simulation programs are currently used for their kinematic and dynamic analysis. The proposed manipulator was first solved by inverse kinematics problem in Matlab. Subsequently, the trajectories of the end-effector were determined in Matlab by a direct kinematics problem. In Simulink, using the SimMechanics library, the inverse problem of dynamics was used to determine the trajectories of the moments.

Статическое нагружение силового гидропривода звеньев манипулятора лесотранспортной машины в критическом режиме

The safe and effective modes of operation of handling equipment of the manipulator type for the forest complex assume a mandatory horizontal position of the frame of the mobile technological machine. In unfavorable production conditions, a forest transport machine may find itself in a critical situation associated with the rotation of the manipulator's support frame relative to the horizon. Correction of this situation can be provided through the use of outriggers. This paper presents the results of a theoretical study of static loads that are characteristic of hydraulic cylinders of outriggers and other elements of the hydraulic manipulator of a forest transport machine with its various configurations. Technologies for loading, moving and unloading forest cargoes can be carried out using special equipment, subject to certain rules. The safe and effective operation modes of manipulator handling equipment assume a mandatory horizontal position of the support-turntable. In unfavorable production conditions, the wood transport machine may find itself in a critical situation related to the rotation of the support and turning frame of the manipulator relative to the horizon. Correction of such position can be insured by use of outriggers. This paper presents the theoretical study results of the static loads, which are characteristic for the hydraulic cylinder of outrigger and other elements of the hydraulic manipulator of a timber transport machine in its various configurations. Balance equations in generalized coordinates are used to describe the equilibrium conditions of the mechanical system under study, which includes a basic vehicle, outriggers, a boom, a handle with a telescopic extension, a grip device and hydraulic drives that ensure their functioning. The rotation angle of support-turning frame in vertical plane, the boom rotation angle, the handle rotation angle and extension of the telescopic part are selected as generalized coordinates. Analytical expressions are obtained for forces on rods of hydraulic cylinders and the working fluid pressure values in piston cavities of hydraulic cylinders in equilibrium state at different position of manipulator links. Calculations based on the obtained formulas can be used in designing technological modes of operation of timber transport machines for carrying out loading and unloading operations of cargoes with the possibility of bringing the support-turntable into a horizontal position.

Neural Fractional Order PID Controllers Design for 2-Link Rigid Robot Manipulator

The robotic manipulator is considered one of the complex systems that include multi-input, multi-output, non-linearity, and highly coupled. The uncertainty in the parameters and external disturbances have a negative influence on the performance of the system. Therefore, the controllers that will be designed for these systems must be able to deal with these complexities and difficulties. The Proportional, Integral, and Derivative (PID) controller is known to be simple and well robust, while the neural network has a solid ability to map complex functions. In this paper, we propose six control structures by combining the benefits of PID controller with integer and fractional order and the benefits of neural networks to produce hybrid controllers for a 2-Link Rigid Robot Manipulator (2-LRRM) handling with the problem of trajectory tracking. The Gorilla Forces Troops Optimization algorithm (GTO) was used to tune the parameters of the proposed controller schemes to minimize the Integral of Time Square Error (ITSE). In addition, the robustness of the performance of the suggested control systems is tested by altering the initial position, external disturbances and parameters and carried out using MATLAB. The best performance of the proposed controllers was the Neural Network Fractional Order Proportional Integral Derivative Controller (NNFOPID).

Torque Minimization of Dynamically Decoupled 3R Spatial Serial Manipulators via Optimal Motion Generation

This paper proposes an analytically tractable solution for minimizing input torques in decoupled three-degrees-of-freedom spatial serial manipulators. The solution relies on the generation of motion using a «bang-bang» profile. The problem is solved in two stages. Firstly, the dynamic decoupling of the manipulator is accomplished through the redistribution of the moving masses and the relocation of one of the actuators. This leads to the decoupling of the equations of motion for different degrees of mobility. It is worth mentioning that this solution represents a symbiosis of two distinct approaches: the redistribution of link masses and the relocation of one of the manipulator actuators. This innovative approach to dynamic decoupling has not been previously proposed. At the second stage, the input torques of the actuators are reduced by generating motion profiles for the manipulator's links using the «bang-bang» law. Thus, thanks to the developed methodology, it becomes possible to reduce the energy consumption of high-speed manipulators by choosing the optimal planned motion of their links. To evaluate the effectiveness of this approach, numerical simulations are carried out using the ADAMS software. A comparative analysis of the trajectories generated by the fifth-order polynomial profile, widely used in industrial robots, and the «bang-bang» profile has been performed. The simulation results show act, the use of the «bang-bang» profile allows one to reduce the maximum values of the input torques. The developed technique allows designers to create high-speed manipulators featuring decoupled dynamics and diminished energy consumption.

Deep reinforcement learning with reward shaping for tracking control and vibration suppression of flexible link manipulator

This paper puts forward a novel deep reinforcement learning control using deep deterministic policy gradient (DRLC-DDPG) framework to address the reference tracking and vibration suppression problem of rotary flexible link (RFL) manipulator. Specifically, this study attempts to address the continuous action space DRLC problem through DDPG algorithm and presents a Lyapunov function based reward shaping approach for guaranteed deep reinforcement learning (DRL) convergence and enhanced speed of training. The proposed approach synthesizes the hard and soft constraints of the flexible manipulator as a constrained Markov decision problem (MDP) and evaluates the performance of DRLC-DDPG framework through hardware in loop (HIL) testing to realize precise servo tracking and suppressed vibration of the flexible manipulator. For identifying the dynamical model of the RFL, an empirical Auto-Regressive eXogenous (ARX) model using the closed loop identification technique is built. Moreover, to extract the true states (servo angle and deflection angle) from the actual measurements, which typically have the influence of sensor noise, an adaptive Kalman filter (AKF) is augmented with the DRLC scheme. The experimental results of DRLC-DDPG scheme compared with those of the model predictive control (MPC) for several test cases reveal that the proposed scheme is superior to MPC both in terms of trajectory tracking and robustness against the external disturbances and model uncertainty.

A Tangent Release Manipulation Controlled by a Dual-Arm Space Robot

As people further develop space with advanced technology, space robots have played a significant role in on-orbit servicing missions. Space robots can carry out more risky and complicated missions with less cost than astronauts. Dual-arm space robots can perform complex on-orbit space missions more effectively than single-arm space robots. Since the coupled dynamics between the free-floating base and the arms exist in space robots, accurate coordinate control of the base and the arms is essential. Spacecraft release missions have been proposed to berth/deberth a spacecraft to a space station. Based on the existing release missions, a tangent release strategy is introduced in this paper, which can release a space object in the tangent direction of the final link of a space manipulator. This strategy can control a dual-arm space robot to deploy cargo/spacecraft in variable directions in 3D space without thrusters and the associated fuel consumption. For instance, this tangent release operation can transport cargo or modules of large-scale spacecraft needing on-orbit assembly. Considering model uncertainties, robust controllers again model uncertainties that are used to control the dual-arm space robot with high accuracy. Hence, a robust sliding mode controller (SMC) is utilized to accurately control the space robot to carry out the proposed tangent release strategy. For comparison, we select a conventional computed torque control (CTC) implemented by a PD-type controller. In the simulations, the SMC performs better in tracking accuracy and robustness against the model uncertainties than the PD controller. Numerical simulations indicate the feasibility and effectiveness of the tangent release manipulation of a space object by a dual-arm space robot.

Hybrid Controller for a Single Flexible Link Manipulator

In this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibration damping and hub position tracking. A comparison is made between the performances of these two controllers. The Hybrid controller with PD and SM shows better tracking behavior than obtained from the suggested fuzzy (PI+D)2 controller for a single link flexible manipulator.

Vibration and Position Control of a Two-Link Flexible Manipulator Using Reinforcement Learning

In recent years, industries have increasingly emphasized the need for high-speed, energy-efficient, and cost-effective solutions. As a result, there has been growing interest in developing flexible link manipulator robots to meet these requirements. However, reducing the weight of the manipulator leads to increased flexibility which, in turn, causes vibrations. This research paper introduces a novel approach for controlling the vibration and motion of a two-link flexible manipulator using reinforcement learning. The proposed system utilizes trust region policy optimization to train the manipulator’s end effector to reach a desired target position, while minimizing vibration and strain at the root of the link. To achieve the research objectives, a 3D model of the flexible-link manipulator is designed, and an optimal reward function is identified to guide the learning process. The results demonstrate that the proposed approach successfully suppresses vibration and strain when moving the end effector to the target position. Furthermore, the trained model is applied to a physical flexible manipulator for real-world control verification. However, it is observed that the performance of the trained model does not meet expectations, due to simulation-to-real challenges. These challenges may include unanticipated differences in dynamics, calibration issues, actuator limitations, or other factors that affect the performance and behavior of the system in the real world. Therefore, further investigations and improvements are recommended to bridge this gap and enhance the applicability of the proposed approach.

Optimization of PID trajectory tracking controller for a 3-DOF robotic manipulator using enhanced Artificial Bee Colony algorithm

This study introduces and compares two optimization techniques, the basic Artificial Bee Colony (ABC) and the enhanced Artificial Bee Colony with multi-elite guidance (MGABC), for determining optimal gains of a Proportional-Integral-Derivative (PID) controller in a 3 degrees of freedom (DOF) rigid link manipulator (RLM) system. The objective function used in the optimization process is a novel function that is based on the well-known Lyapunov stability functions. This function is evaluated against established error-based objective functions commonly used in control systems. The convergence curves of the optimization process demonstrate that the MGABC algorithm outperforms the basic ABC algorithm by effectively exploring the search space and avoiding local optima. The evaluation of the controller's performance in trajectory tracking reveals the superiority of the Lyapunov-based objective function (LBF), with significant improvements over other objective functions such as IAE, ISE, ITAE, MAE and MRSE. The optimized system demonstrates robustness to diverse disturbance conditions and uncertainty in the mass of the payload, while also exhibiting adaptability to joints flexibility without inducing any vibrations in the movement of the end-effector. The proposed techniques and objective function offer promising avenues for the optimization of PID controllers in various robotic applications.

Addressing Model Uncertainties and External Disturbances in Optimal Robust Control for Vibration Reduction in a Flexible Link Manipulator

Addressing Model Uncertainties and External Disturbances in Optimal Robust Control for Vibration Reduction in a Flexible Link Manipulator

Collision avoidance analysis of human-robot physical interaction based on null-space impedance control of a dynamic reference arm plane.

When the terminal upper limb rehabilitation robot is used for motion-assisted training, collisions between the manipulator links and the human upper limb may occur due to the null-space self-motion of the redundant manipulator. A null-space impedance control method based on a dynamic reference arm plane is proposed to realize collision avoidance during human-robot physical interaction motion for the collision problem between the manipulator links and the human upper limb. Firstly, a dynamic model and a Cartesian impedance controller of the manipulator are established. Then, the null-space impedance controller of the redundant manipulator is established based on the dynamic reference plane, which manages the null-space self-motion of the redundant manipulator to prevent collision between the manipulator links and the human upper limb. Finally, it is experimentally verified that the method proposed in this paper can effectively manage the null-space self-motion of the redundant manipulator, and thus achieve collision avoidance during the human-robot physical interaction motion. This research has significant potential in improving the safety and feasibility of motion-assisted training with rehabilitation robots.

Elements of the theory of designing manipulators from composite materials for ground robotic complexes for special purposes

Elements of the theory of designing manipulators from composite materials intended for use in ground-based robotic complexes for special purposes have been developed. Circuit solutions of manipulators and constructive execution of their main components and elements are proposed. Special hinges and remote drives for moving links of manipulators have been developed. To ensure the required static and dynamic characteristics, special mechatronic modules are implemented in the form of geared motors that are outside the manipulators. Control systems of geared motors are implemented on the basis of artificial neural networks using the results of mathematical modeling of statics and dynamics of manipulators by helical calculus methods. The developed manipulators significantly increase the functionality of ground robotic complexes when they work with dangerous objects.