Pneumatic Manipulator Research Articles

Research on Pneumatic Manipulator Control Methods

With the rapid development of pneumatic technology, there has been an increasing focus on leveraging pneumatic manipulator equipment that offers a blend of affordability, high performance, and numerous advantages, catering to the diverse needs of modern production practices. Pneumatic manipulators stand out among controlled manipulators due to their cost-effectiveness, straightforward design, impressive power-to-volume ratio, environmentally friendly operation, and robust resilience to external interference. This paper delves into addressing significant control deviations encountered during the dynamic movement of pneumatic manipulators, aiming to optimize the manipulator s structure and devise an efficient pneumatic system circuit. Additionally, it harnesses PLC control technology to devise a comprehensive control ladder diagram for the pneumatic manipulator, thereby ensuring precise control over its motion. By validating the feasibility and accuracy of the designed motion control methods, this study contributes to enhancing the overall efficiency and reliability of pneumatic manipulator systems in industrial settings.

Motion control for a multi-DOF pneumatic manipulator via angle deflection gravity compensation

Motion control for a multi-DOF pneumatic manipulator via angle deflection gravity compensation

Mechatronic automatic control system of electropneumatic manipulator

Mechatronic systems of electropneumatic automation are one of the main classes of industrial automation systems. A laboratory stand for the study of the mechatronic system of automatic control of the pneumatic manipulator and a computer model for preliminary experiments on the adjustment of the automatic control system were developed. Manual and software control modes are provided for research of indicators of safety and quality of management in both modes. To implement the software control mode, a microcontroller part of the laboratory stand based on ADuC841 was developed, with the help of which it is possible to simulate a part of a certain technological process, to detect and eliminate faults in the automatic control system. A study of automatic control systems using a traditional relay-contactor control system, based on GrafCet technology and using a virtual controller. The combination of computer modeling of technological processes and physical modeling of executive mechanisms is a kind of digital double that displays its state, parameters and behavior in real time. The use of a laboratory stand in combination with an adequate simulation model reduces the complexity of developing control systems for practical applications, and also contributes to the formation of students' creative component, ability to analyze the results, and make decisions in unusual situations, which will increase their theoretical and practical training. The study of mechatronic systems of pneumatic manipulators will allow to increase their efficiency and productivity, to optimize their speed and accuracy for various applications in production. The interaction of mechatronic systems of pneumatic manipulators with other technologies, such as machine learning, artificial intelligence, IoT is the basis for creating more integrated and intelligent systems.

Decoupling control for a multi-DOF pneumatic manipulator subject to imbalanced torques

Decoupling control for a multi-DOF pneumatic manipulator subject to imbalanced torques

Waterbomb Origami Mechanism Pneumatic Manipulator Design Based on DH Parameter Method and Symmetric Folding Hypothesis

Waterbomb Origami Mechanism Pneumatic Manipulator Design Based on DH Parameter Method and Symmetric Folding Hypothesis

Model-Free Intelligent Control for Space Soft Robotic Manipulators

Given the advantages of softness, lightness, low cost, and interaction safety, inverse kinematic modeling and control of soft actuators has caused a research boom. However, in realizing dexterous manipulation of space large soft manipulators, it is much more difficult to achieve precise control not only because of the greater accumulation of errors in the multiple degrees of freedom and nonlinear properties of soft materials at large scales but also because of the inability of directly solving the inverse kinematics in the cases of singular pure elongation. In this work, a model-free intelligent kinematic control strategy is proposed for these problems that exhibit a mapping relationship between the output end-effector position and the input pressure. For multiple-degree-of-freedom robots, especially pneumatic soft manipulators, traditional inverse kinematic modeling methods are complex and inverse Jacobian matrix solution often encounters geometric singularities. To address this issue, this paper proposes an inverse kinematics–multilayer perceptron (IK-MLP) method for soft manipulators. In this strategy, the trained intelligent controller can be applied to control pneumatic manipulators without establishing a traditional inverse kinematic model. The control algorithm is experimentally tested based on the ground experiment system of the space soft manipulator. Simulations and experiments are carried out to validate the given model-free intelligent controller, proving that the IK-MLP method can effectively solve the singularity of inverse kinematics.

Backstepping integral sliding mode control for pneumatic manipulators via adaptive extended state observers

In this paper, a nonlinear control strategy is proposed for a pneumatic manipulator based on an adaptive extended state observer and a backstepping integral sliding mode controller. A single degree of freedom dynamic model is established for the pneumatic manipulator using an Euler–Lagrange dynamic equation. The adaptive extended state observer is designed by an adaptive law to estimate uncertainties and disturbances. The backstepping integral sliding mode controller is proposed using an integral sliding mode surface based on backstepping technique. Comparative experiments verify effectiveness of the proposed nonlinear control strategy for the pneumatic manipulator.

Semi-Physical Modeling of Soft Pneumatic Actuators With Stiffness Tuning

Abstract The inherent low stiffness in soft robots makes them preferable for working in close proximity to humans. However, having this low stiffness creates challenges when operating in terms of control and sensitivity to disturbances. To alleviate this issue, soft robots often have built-in stiffness tuning mechanisms that allow for controlled increases in stiffness. Additionally, redundant pneumatic manipulators can utilize antagonistic pressure to achieve identical positions under increased stiffness. In this paper, we develop a model to predict the stiffness and configuration of a pneumatic soft manipulator under different pressure inputs and external forces. The model is developed based on the physical characteristics of a soft manipulator while enabling efficient parameter estimation and computation. The efficacy of the modeling approach is supported via experimental results.

Coupling Field Simulation of Soft Capacitive Sensors Toward Soft Robot Perception

Simulation is a standard tool for robot design, control and performance analysis. Numerous mature, thoroughly validated methods exist to build fast and reliable simulation models for traditional rigid robotics platforms. However, when it comes to novel soft robotics systems, most existing models concern themselves with the dynamics of the soft bodies during actuation, largely disregarding the sensory system. Simultaneous simulation of sensors and actuators is essential to establishing a realistic and accurate robot model in the virtual environment. This paper proposes a pipeline to implement Coupling Field Simulation (CFS) of capacitive sensors deployed on a square soft arm and a pneumatic manipulator. The CFS approach can seamlessly integrate mechanical and sensing components, enabling us to understand sensor behaviour better by simulating sensor responses to various deformations including bending, inflation and the combinations of bending, twisting and elongation. We also demonstrate CFS is an effective and costly manner to acquire a large number of annotated data that can be used for pre-training in soft robot perception tasks through two case studies (i.e., applied force estimation and deformation classification).

A Hybrid Controller for a Soft Pneumatic Manipulator Based on Model Predictive Control and Iterative Learning Control.

Due to the outstanding characteristics of the large structural flexibility and strong dexterity of soft robots, they have attracted great attention. However, the dynamic modeling and precise control of soft robots face huge challenges. Traditional model-based and model-free control methods find it difficult to obtain a balance between complexity and accuracy. In this paper, a dynamic model of a three-chamber continuous pneumatic manipulator is established based on the modal method. Moreover, a hybrid controller integrating model predictive control (MPC) and iterative learning control (ILC) is proposed, which can simultaneously perform model parameter learning and trajectory tracking control. Experimental results show that the proposed control method can optimize the parameters of the dynamic model in real time with less iterations than the traditional model-free method and have good control performance in trajectory tracking experiments. In the future, the proposed dynamic model and the hybrid controller should be verified on a multi-section manipulator.

Analytical Evaluation of Force-Projecting Bilateral Control for Pneumatic Manipulators

This paper presents performance and stability analyses of the Force-Projecting Bilateral Control (the Force-Projecting Type) for master-follower operation of pneumatic manipulators. In this control method, the operational force on the master side is directly projected to the driving force on the follower. Unlike other bilateral control methods, the Force-Projecting Type does not have a position controller on the follower side. Therefore, it is considered highly suitable for manipulators with low-rigidity and slow response, such as pneumatic manipulators. In this study, the Force-Projecting Type was applied to a one-degree-of-freedom master-follower model with characteristics of low-rigidity and response delay as a pneumatic manipulator on the follower side, and the time and frequency responses were numerically investigated. Then, the responses were compared with those of the conventional Force-Reflecting Bilateral Control. As a result of the analyses, the Force-Projecting Type showed both higher stability and performance. In addition, the equivalent block diagram of the system suggests that the Force-Projecting Type is more robust to changes in environmental characteristics.

Security Analysis for Distributed IoT-Based Industrial Automation

Internet of Things (IoT) technologies enable development of reconfigurable manufacturing systems—a new generation of modularized industrial equipment suitable for highly customized manufacturing. Sequential control in these systems is largely based on discrete events, whereas their formal execution semantics is specified as control interpreted Petri nets (CIPN). Despite industry-wide use of programming languages based on the CIPN formalism, formal verification of such control applications in the presence of adversarial activity is not supported. Consequently, in this article, we introduce security-aware modeling and verification techniques for CIPN-based sequential control applications. Specifically, we show how CIPN models of networked industrial IoT controllers can be transformed into time Petri net (TPN)-based models and composed with plant and security-aware channel models in order to enable system-level verification of safety properties in the presence of network-based attacks. Additionally, we introduce realistic channel-specific attack models that capture adversarial behavior using nondeterminism. Moreover, we show how verification results can be utilized to introduce security patches and facilitate design of attack detectors that improve system resiliency and enable satisfaction of critical safety properties. Finally, we evaluate our framework on an industrial case study. Note to Practitioners—Our main goal is to provide formal security guarantees for distributed sequential controllers. Specifically, we target smart automation controllers geared toward Industrial IoT applications that are typically programed in C/C++ and are running applications originally designed in, for example, GRAFCET (IEC 60848)/SFC (IEC 61131-3) automation programming languages. Since existing tools for the design of distributed automation do not support system-level verification of relevant safety properties, we show how security-aware transceiver and communication models can be developed and composed with distributed controller models. Then, we show how existing tools for verification of time Petri nets can be used to verify relevant properties including safety and liveness of the distributed automation system in the presence of network-based attacks. To provide an end-to-end analysis as well as security patching, results of our analysis can be used to deploy suitable firmware updates during the stage when executable code for target controllers (e.g., in C/C++) is generated based on GRAFCET/SFC control models. We also show that security guarantees can be improved as the relevant safety/liveness properties can be verified after corresponding security patches are deployed. Finally, we show applicability of our framework on a realistic distributed pneumatic manipulator.

Fixed-Time Dynamic Surface Control for Pneumatic Manipulator System With Unknown Disturbances

In this article, a new nonlinear disturbance observer (NDO) based fixed-time dynamic surface control (FTDSC) approach is developed to achieve desired trajectory tracking control performances of the pneumatic manipulator system driven by pneumatic artificial muscles (PAMs). To achieve active disturbance rejection, an NDO is proposed to estimate the unknown disturbances in the pneumatic manipulator system. Then, a fixed-time dynamic surface controller is introduced, and the variable gains are designed to achieve desired control performances. Finally, comparative simulations and experiments verify that the proposed approach is effective to achieve desired trajectory tracking control performances.

Offset-free model predictive control of a soft manipulator using the Koopman operator

The modeling and control of soft manipulators remain challenging due to their inherent complex kinematics and dynamics. This paper presents an offset-free Koopman operator-based model predictive control (OK-MPC) scheme that offers a practical data-driven approach to model and control the soft manipulator in the task space. In this scheme, the Koopman operator is used to derive a straightforward linear model to describe the complex dynamics of a soft manipulator. Then, an offset-free control strategy is incorporated with the Koopman operator to minimize the effect of modeling uncertainties and external disturbance, allowing the precise control of the soft manipulator. The proposed OK-MPC scheme was examined on both a soft pneumatic manipulator and a cable-driven origami manipulator through trajectory tracking experiments. The experimental results showed that the tracking errors decreased by 30.0% in free space and 45.4% in confined space, indicating that the OK-MPC has the capability to improve the control performance of a normal Koopman-based controller. Besides, the OK-MPC is readily available for the two different soft robotic prototypes, demonstrating its general applicability for the modeling and control in the field of soft robotics.

Flexible Design of the Connecting Plate in Pneumatic Soft Manipulators

This paper presents a novel connecting plate for achieving a flexible connection in a soft manipulator. The main material used in the connecting plate is silicone, which functions similarly to the bionic oblique muscle (BOM) of an octopus arm and takes over the two actuator segments. Each segment of the actuator consists of three chambers, and the chambers are assembled with the connecting plate via bolts and loops to be a manipulator. By using a flexible plate instead of a rigid one, the manipulator achieves more dexterous movements. This paper establishes a nonlinear model for analyzing the shear and compression deformation of a silicone connecting plate. Additionally, finite element method was used to analyze the mechanical performance of the connecting plate. The deformation of a soft material can reduce the stress concentration during movement of the manipulator. Therefore, in the experiment, the BOM exhibited better motion performance compared with the rigid connection plate.

Model Analysis and Experimental Investigation of Soft Pneumatic Manipulator for Fruit Grasping.

With the superior ductility and flexibility brought by compliant bodies, soft manipulators provide a nondestructive manner to grasp delicate objects, which has been developing gradually as a rising focus of soft robots. However, the unexpected phenomenon caused by environmental effects, leading to high internal nonlinearity and unpredictable deformation, makes it challenging to design, model, and control soft manipulators. In this paper, we designed a soft pneumatically actuated manipulator consisting of four soft actuators, as well as a flange, and investigated the influence of structural parameters on the output characteristics of the manipulator through finite element analysis (FEA). To enhance the bending deformation of the soft actuator, annular rings were employed on the soft actuator. A mathematical model for the bending deformation of air cavities was established to explore the relationship between the driving pressure and the bending angle based on the Yeoh strain energy function. Moreover, an end-output force model was established to depict the variation of the force output with the bending angle of the soft actuator, which was then experimentally validated by adopting the manufactured manipulator. The soft actuator studied in this paper can bend from 0° to 110° under an applied pressure of 0–60 kPa, and the maximum grasping load of the soft manipulator is 5.8 N. Finally, practical tests were conducted to assess the adaptability of the soft manipulator when grasping delicate fruits, such as apples, pears, tomatoes, and mangoes, demonstrating its broad application prospects in nondestructive fruit harvesting.

Modelling, simulation and implementation of a hybrid model reference adaptive controller applied to a manipulator driven by pneumatic artificial muscles

AbstractThe present research aims to model, simulate and implement a new hybrid control approach based on a combination of proportional integral derivative (PID) Controller and Model Reference Adaptive Controller (MRAC), in which Lyapunov’s theory is used to ensure asymptotic stability to control a two degrees of freedom (DoF) manipulator driven by McKibben’s artificial pneumatic muscles. The MRAC controller works as a nonlinearity compensator and PID controller works during the transient period, as the MRAC performs poorly in this regime. This new approach is entitled Hybrid Model Reference Adaptive Controller (H-MRAC) and it has an unprecedented topological structure based on three terms. The feedforward term acts in disturbances rejection, the derivative term in oscillations damping and the feedback term acts in error convergence to zero. In this article, a control system dedicated to pneumatic manipulators was developed. As a result, proof of asymptotic convergence was performed for the proposed topological approach, which was validated on a two DoF manipulator. The proposed mechanism satisfactorily met the ISO/TS 15066 standard, and the position tracking obtained a global error of 37.69% and 51.01% smaller than found in the literature examples, entitled MRAC and A-PID, respectively, for simulations and 37.46% and 30.25% for experiments.

Nonlinear energy-based control of soft continuum pneumatic manipulators

This paper investigates the model-based nonlinear control of a class of soft continuum pneumatic manipulators that bend due to pressurization of their internal chambers and that operate in the presence of disturbances. A port-Hamiltonian formulation is employed to describe the closed loop system dynamics, which includes the pressure dynamics of the pneumatic actuation, and new nonlinear control laws are constructed with an energy-based approach. In particular, a multi-step design procedure is outlined for soft continuum manipulators operating on a plane and in 3D space. The resulting nonlinear control laws are combined with adaptive observers to compensate the effect of unknown disturbances and model uncertainties. Stability conditions are investigated with a Lyapunov approach, and the effect of the tuning parameters is discussed. For comparison purposes, a different control law constructed with a backstepping procedure is also presented. The effectiveness of the control strategy is demonstrated with simulations and with experiments on a prototype. To this end, a needle valve operated by a servo motor is employed instead of more sophisticated digital pressure regulators. The proposed controllers effectively regulate the tip rotation of the prototype, while preventing vibrations and compensating the effects of disturbances, and demonstrate improved performance compared to the backstepping alternative and to a PID algorithm.

A new approach for hybrid (PID + MRAC) adaptive controller applied to two-axes McKibben muscle manipulator: a mechanism for human-robot collaboration

PurposeThis paper aims to present a new approach, called hybrid model reference adaptive controller or H-MRAC, for the hybrid controller (proportional-integral-derivative [PID + MRAC]) that will be used to control the position of a pneumatic manipulator.Design/methodology/approachIt was developed a McKibben muscle using nautical mesh, latex and high-density polyethene connectors and it was constructed an elbow manipulator with two degrees of freedom, driven by these muscles. Then it was presented the H-MRAC control law based on the phenomenological characteristics of the plant, aiming at fast response and low damping. Lyapunov's theory was used as the project methodology, which ensures asymptotic stability for the control system.FindingsIt was developed a precise control system for a pneumatic manipulator and the results were compared to previous research.Research limitations/implicationsIn collaborative robotics, human and machine occupy the same workspace. This research promotes the development of safer and more complacent mechatronic systems in the event of collisions.Practical implicationsAs a practical implication, the research allows the substitution of electric motors by McKibben muscles in industrial robots with high accuracy.Social implicationsThe pneumatic manipulator will make the human-robot physical interaction safer as it can prevent catastrophic collisions causing victims or equipment breakdown.Originality/valueWhen compared to results in the literature, the present research showed a 37.51% and 36.74% lower global error in position tracking than MRAC and Adaptive proportional-integral-derivative (A-PID), respectively, validating its effectiveness.

Inertia-enhancement effect of divergent flow on the force characteristics of a Bernoulli gripper

Bernoulli grippers, which are widely employed in automated production lines, are pneumatic manipulators capable of noncontact adsorption that utilize the decelerating inertial effect of the radial air flow to generate negative pressure and a suction force. This paper proposes an innovative design for the Bernoulli grippers in which divergent flow is formed through a tiny-inclination cone structure between the gripper and the workpiece, and the inertia-enhancement effect of the divergent flow is exploited to greatly increase the negative pressure and suction force (hereafter, this is referred to as a divergent-flow gripper). First, a theoretical model of the divergent flow between the divergent-flow gripper and the workpiece was formulated. The theoretical formulas for calculating the pressure distribution and suction force were then derived. Suction force measurement experiments were then conducted, whose results indicated that the proposed divergent-flow gripper can increase the suction force by several factors compared with that of an unmodified gripper with a flat surface. The influence of the divergent flow on the inertial and viscous effects of the gripper was examined both theoretically and experimentally, and the main factors leading to the increase in suction force were analyzed. In addition, this paper discusses the influence of the inclination angle and diameter of the gripper. As a result, through changes in the geometric structure and velocity distribution, the proposed divergent-flow gripper has the advantages of a large suction force and simple structure, and these findings serve as important theoretical and experimental references for the design of the Bernoulli gripper.