arXiv subjects

Jouni Mattila

Publications and source records attributed to Jouni Mattila.

At least 55 records · Page 3Linked to original sources

arXiv2024

Robust Model-Free Control Framework with Safety Constraints for a Fully Electric Linear Actuator System

This paper introduces a novel model-free control strategy for a complex multi-stage gearbox electromechanical linear actuator (EMLA) system, driven by a permanent magnet synchronous motor (PMSM) with non-ideal ball screw characteristics. The proposed control approach aims to (1) manage user-specified safety constraints, (2) identify optimal control parameters for minimizing tracking errors, (3) ensure robustness, and (4) guarantee uniformly exponential stability. First, this paper employs a trajectory-setting interpolation-based algorithm to specify the piecewise definition of a smooth and jerk-bounded reference trajectory. Then, a dual robust subsystem-based barrier Lyapunov function (DRS-BLF) control is proposed for the PMSM-powered EMLA system to track the reference motions, guaranteeing user-specified safety related to constraints on system characteristics and alleviating control signal efforts. This methodology guarantees robustness and uniform exponential convergence. Lastly, optimal control parameter values are determined by customizing a swarm intelligence technique known as the Jaya (a term derived from the Sanskrit word for `victory') algorithm to minimize tracking errors. Experimental results validate the performance of the DRS-BLF control.

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arXiv2024

System-Level Efficient Performance of EMLA-Driven Heavy-Duty Manipulators via Bilevel Optimization Framework with a Leader--Follower Scenario

The global push for sustainability and energy efficiency is driving significant advancements across various industries, including the development of electrified solutions for heavy-duty mobile manipulators (HDMMs). Electromechanical linear actuators (EMLAs), powered by permanent magnet synchronous motors, present an all-electric alternative to traditional internal combustion engine (ICE)-powered hydraulic actuators, offering a promising path toward an eco-friendly future for HDMMs. However, the limited operational range of electrified HDMMs, closely tied to battery capacity, highlights the need to fully exploit the potential of EMLAs that driving the manipulators. This goal is contingent upon a deep understanding of the harmonious interplay between EMLA mechanisms and the dynamic behavior of heavy-duty manipulators. To this end, this paper introduces a bilevel multi-objective optimization framework, conceptualizing the EMLA-actuated manipulator of an electrified HDMM as a leader--follower scenario. At the leader level, the optimization algorithm maximizes EMLA efficiency by considering electrical and mechanical constraints, while the follower level optimizes manipulator motion through a trajectory reference generator that adheres to manipulator limits. This optimization approach ensures that the system operates with a synergistic trade-off between the most efficient operating region of the actuation system, achieving a total efficiency of 70.3\%, and high manipulator performance. Furthermore, to complement this framework and ensure precise tracking of the generated optimal trajectories, a robust, adaptive, subsystem-based control strategy is developed with accurate control and exponential stability. The proposed methodologies are validated on a three-degrees-of-freedom manipulator, demonstrating significant efficiency improvements while maintaining high-performance operation.

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arXiv2024

Robustness-Guaranteed Observer-Based Control Strategy with Modularity for Cleantech EMLA-Driven Heavy-Duty Robotic Manipulator

This paper introduces an innovative observer-based modular control strategy in a class of n_a-degree-of-freedom (DoF) fully electrified heavy-duty robotic manipulators (HDRMs) to (1) guarantee robustness in the presence of uncertainties and disturbances, (2) address the complexities arising from several interacting mechanisms, (3) ensure uniformly exponential stability, and (4) enhance overall control performance. To begin, the dynamic model of HDRM actuation systems, which exploits the synergy between cleantech electromechanical linear actuators (EMLAs) and permanent magnet synchronous motors (PMSMs), is investigated. In addition, the reference trajectories of each joint are computed based on direct collocation with B-spline curves to extract the key kinematic and dynamic quantities of HDRMs. To guarantee robust tracking of the computed trajectories by the actual motion states, a novel control methodology, called robust subsystem-based adaptive (RSBA) control, is enhanced through an adaptive state observer. The RSBA control addresses inaccuracies inherent in motion, including modeling errors, non-triangular uncertainties, and both torque and voltage disturbances, to which the EMLA-driven HDRM is susceptible. Furthermore, this approach is presented in a unified generic equation format for all subsystems to mitigate the complexities of the overall control system. By applying the RSBA architecture, the uniformly exponential stability of the EMLA-driven HDRM is proven based on the Lyapunov stability theory. The proposed RSBA control performance is validated through simulations and experiments of the scrutinized PMSM-powered EMLA-actuated mechanisms.

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arXiv2024

Impact-Resilient Orchestrated Robust Controller for Heavy-duty Hydraulic Manipulators

Heavy-duty operations, typically performed using heavy-duty hydraulic manipulators (HHMs), are susceptible to environmental contact due to tracking errors or sudden environmental changes. Therefore, beyond precise control design, it is crucial that the manipulator be resilient to potential impacts without relying on contact-force sensors, which mostly cannot be utilized. This paper proposes a novel force-sensorless robust impact-resilient controller for a generic 6-degree-of-freedom (DoF) HHM constituting from anthropomorphic arm and spherical wrist mechanisms. The scheme consists of a neuroadaptive subsystem-based impedance controller, which is designed to ensure both accurate tracking of position and orientation with stabilization of HHMs upon contact, along with a novel generalized momentum observer, which is for the first time introduced in Plücker coordinate, to estimate the impact force. Finally, by leveraging the concepts of virtual stability and virtual power flow, the semi-global uniformly ultimately boundedness of the entire system is assured. To demonstrate the efficacy and versatility of the proposed method, extensive experiments were conducted using a generic 6-DoF industrial HHM. The experimental results confirm the exceptional performance of the designed method by achieving a subcentimeter tracking accuracy and by 80% reduction of impact of the contact.

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arXiv2024

Exponential Auto-Tuning Fault-Tolerant Control of N Degrees-of-Freedom Manipulators Subject to Torque Constraints

This paper presents a novel auto-tuning subsystem-based fault-tolerant control (SBFC) system designed for robotic manipulator systems with n degrees of freedom (DoF). It initially proposes a novel model for joint torques, incorporating an actuator fault correction model to account for potential faults and a mathematical saturation function to mitigate issues related to unforeseen excessive torque. This model is designed to prevent the generation of excessive torques even by faulty actuators. Subsequently, a robust subsystem-based adaptive control strategy is proposed to force system states closely along desired trajectories, while tolerating various actuator faults, excessive torques, and unknown modeling errors. Furthermore, optimal SBFC gains are determined by tailoring the JAYA algorithm (JA), a high-performance swarm intelligence technique, standing out for its capacity to optimize without the need for meticulous tuning of algorithm-specific parameters, relying instead on its intrinsic principles. Notably, this control framework ensures uniform exponential stability (UES). The enhancement of accuracy and tracking time for reference trajectories, along with the validation of theoretical assertions, is demonstrated through the presentation of simulation outcomes.

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arXiv2024

Integrating DeepRL with Robust Low-Level Control in Robotic Manipulators for Non-Repetitive Reaching Tasks

In robotics, contemporary strategies are learning-based, characterized by a complex black-box nature and a lack of interpretability, which may pose challenges in ensuring stability and safety. To address these issues, we propose integrating a collision-free trajectory planner based on deep reinforcement learning (DRL) with a novel auto-tuning low-level control strategy, all while actively engaging in the learning phase through interactions with the environment. This approach circumvents the control performance and complexities associated with computations while addressing nonrepetitive reaching tasks in the presence of obstacles. First, a model-free DRL agent is employed to plan velocity-bounded motion for a manipulator with 'n' degrees of freedom (DoF), ensuring collision avoidance for the end-effector through joint-level reasoning. The generated reference motion is then input into a robust subsystem-based adaptive controller, which produces the necessary torques, while the cuckoo search optimization (CSO) algorithm enhances control gains to minimize the stabilization and tracking error in the steady state. This approach guarantees robustness and uniform exponential convergence in an unfamiliar environment, despite the presence of uncertainties and disturbances. Theoretical assertions are validated through the presentation of simulation outcomes.

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arXiv2024

Analytical Forward Dynamics Modeling of Linearly Actuated Heavy-Duty Parallel-Serial Manipulators

This paper presents a new geometric and recursive algorithm for analytically computing the forward dynamics of heavy-duty parallel-serial mechanisms. Our solution relies on expressing the dynamics of a class of linearly-actuated parallel mechanism to a lower dimensional dual Lie algebra to find an analytical solution for the inverse dynamics problem. Thus, by applying the articulated-body inertias method, we successfully provide analytic expressions for the total wrench in the linear-actuator reference frame, the linear acceleration of the actuator, and the total wrench exerted in the base reference frame of the closed loop. This new formulation allows to backwardly project and assemble inertia matrices and wrench bias of multiple closed-loops mechanisms. The final algorithm holds an O(n) algorithmic complexity, where $n$ is the number of degrees of freedom (DoF). We provide accuracy results to demonstrate its efficiency with 1-DoF closed-loop mechanism and 4-DoF manipulator composed by serial and parallel mechanisms. Additionally, we release a URDF multi-DoF code for this recursive algorithm.

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arXiv2023

Physical Human-Robot Interaction Control of an Upper Limb Exoskeleton with a Decentralized Neuro-Adaptive Control Scheme

Within the concept of physical human-robot interaction (pHRI), the most important criterion is the safety of the human operator interacting with a high degree of freedom (DoF) robot. Therefore, a robust control scheme is in high demand to establish safe pHRI and stabilize nonlinear, high DoF systems. In this paper, an adaptive decentralized control strategy is designed to accomplish the abovementioned objectives. To do so, a human upper limb model and an exoskeleton model are decentralized and augmented at the subsystem level to enable a decentralized control action design. Moreover, human exogenous force (HEF) that can resist exoskeleton motion is estimated using radial basis function neural networks (RBFNNs). Estimating both human upper limb and robot rigid body parameters, along with HEF estimation, makes the controller adaptable to different operators, ensuring their physical safety. The barrier Lyapunov function (BLF) is employed to guarantee that the robot can operate in a safe workspace while ensuring stability by adjusting the control law. Unknown actuator uncertainty and constraints are also considered in this study to ensure a smooth and safe pHRI. Then, the asymptotic stability of the whole system is established by means of the virtual stability concept and virtual power flows (VPFs) under the proposed robust controller. The experimental results are presented and compared to proportional-derivative (PD) and proportional-integral-derivative (PID) controllers. To show the robustness of the designed controller and its good performance, experiments are performed at different velocities, with different human users, and in the presence of unknown disturbances. The proposed controller showed perfect performance in controlling the robot, whereas PD and PID controllers could not even ensure stable motion in the wrist joints of the robot.

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arXiv2023

Hybrid Controller for Robot Manipulators in Task-Space with Visual-Inertial Feedback

This paper presents a visual-inertial-based control strategy to address the task space control problem of robot manipulators. To this end, an observer-based hybrid controller is employed to control end-effector motion. In addition, a hybrid observer is introduced for a visual-inertial navigation system to close the control loop directly at the Cartesian space by estimating the end-effector pose. Accordingly, the robot tip is equipped with an inertial measurement unit (IMU) and a stereo camera to provide task-space feedback information for the proposed observer. It is demonstrated through the Lyapunov stability theorem that the resulting closed-loop system under the proposed observer-based controller is globally asymptotically stable. Besides this notable merit (global asymptotic stability), the proposed control method eliminates the need to compute inverse kinematics and increases trajectory tracking accuracy in task-space. The effectiveness and accuracy of the proposed control scheme are evaluated through computer simulations, where the proposed control structure is applied to a 6 degrees-of-freedom long-reach hydraulic robot manipulator.

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arXiv2023

Nonlinear Subsystem-based Adaptive Impedance Control of Physical Human-Robot-Environment Interaction in Contact-rich Tasks

Haptic upper limb exoskeletons are robots that assist human operators during task execution while having the ability to render virtual or remote environments. Therefore, the stability of such robots in physical human-robot-environment interaction must be guaranteed, in addition to performing well during task execution. Having a wide range of Z-width, which shows the region of passively renderable impedance by a haptic display, is also important to render a wide range of virtual environments. To address these issues, in this study, subsystem-based adaptive impedance control is designed for having a stable human-robot-environment interaction of 7 degrees of freedom haptic exoskeleton. The presented control decomposes the entire system into subsystems and designs the controller at the subsystem level. The stability of the controller in the presence of contact with the virtual environment and human arm force is proved by employing the virtual stability concept. Additionally, the Z-width of the 7-DoF haptic exoskeleton is drawn using experimental data and improved using varying virtual mass element for the virtual environment. Finally, experimental results are provided to demonstrate the perfect performance of the proposed controller in accomplishing the predefined task.

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arXiv2023

Task Space Control of Robot Manipulators based on Visual SLAM

This paper aims to address the open problem of designing a globally stable vision-based controller for robot manipulators. Accordingly, based on a hybrid mechanism, this paper proposes a novel task-space control law attained by taking the gradient of a potential function in SE(3). The key idea is to employ the Visual Simultaneous Localization and Mapping (VSLAM) algorithm to estimate a robot pose. The estimated robot pose is then used in the proposed hybrid controller as feedback information. Invoking Barbalats lemma and Lyapunov's stability theorem, it is guaranteed that the resulting closed-loop system is globally asymptotically stable, which is the main accomplishment of the proposed structure. Simulation studies are conducted on a six degrees of freedom (6-DOF) robot manipulator to demonstrate the effectiveness and validate the performance of the proposed VSLAM-based control scheme.

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arXiv2023

Decentralized Nonlinear Control of Redundant Upper Limb Exoskeleton with Natural Adaptation Law

The aim of this work is to utilize an adaptive decentralized control method called virtual decomposition control (VDC) to control the orientation and position of the end-effector of a 7 degrees of freedom (DoF) right-hand upper-limb exoskeleton. The prevailing adaptive VDC approach requires tuning of 13n adaptation gains along with 26n upper and lower parameter bounds, where n is the number of rigid bodies. Therefore, utilizing the VDC scheme to control high DoF robots like the 7-DoF upper-limb exoskeleton can be an arduous task. In this paper, a new adaptation function, so-called natural adaptation law (NAL), is employed to eliminate these burdens from VDC, which results in reducing all 13n gains to one and removing dependency on upper and lower bounds. In doing so, VDC-based dynamic equations are restructured, and inertial parameter vectors are made compatible with NAL. Then, the NAL adaptation function is exploited to design a new adaptive VDC scheme. This novel adaptive VDC approach ensures physical consistency conditions for estimated parameters with no need for upper and lower bounds. Finally, the asymptotic stability of the algorithm is proved with the virtual stability concept and the accompanying function. The experimental results are utilized to demonstrate the excellent performance of the proposed new adaptive VDC scheme.

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arXiv2022

A Global Asymptotic Convergent Observer for SLAM

This paper examines the global convergence problem of SLAM algorithms, an issue that faces topological obstructions. This is because the state-space of attitude dynamics is defined on a non-contractible manifold: the special orthogonal group of order three SO(3). Therefore, this paper presents a novel, gradient-based hybrid observer to overcome these topological obstacles. The Lyapunov stability theorem is used to prove the globally asymptotic convergence of the proposed algorithm. Finally, comparative analyses of two simulations were conducted to evaluate the performance of the proposed scheme and to demonstrate the superiority of the proposed hybrid observer to a smooth observer.

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arXiv2022

Analytic Solutions for Wheeled Mobile Manipulator Supporting Forces

When a mobile manipulator's wheel loses contact with the ground, tipping-over may occur, causing material damage, and in the worst case, it can put human lives in danger. The tip-over stability of wheeled mobile manipulators must not be overlooked at any stage of a mobile manipulator's life, starting from the design phase, continuing through the commissioning period and extending to the operational phase. Many tip-over stability criteria formulated throughout the years do not explicitly consider the normal wheel loads, with most of them relying on prescribed stability margins in terms of overturning moments. In these formulations, it is commonly argued that overturning will occur about one of the axes connecting adjacent manipulator's contact points with the ground. This claim may not always be valid and is certainly restrictive. Explicit expressions for the manipulator supporting forces provide the best insight into relevant affecting terms which contribute to the tip-over (in)stability. They also remove the necessity for thinking about which axis the manipulator could tip over and simultaneously enable the formulation of more intuitive stability margins and on-line tip-over prevention techniques. The present study presents a general dynamics modelling approach in the Newton--Euler framework using 6D vectors and gives normal wheel load equations in a typical 4-wheeled mobile manipulator negotiating a slope. The given expressions are expected to become standard in wheeled mobile manipulators and to provide a basis for effective tip-over stability criteria and tip-over avoidance techniques. Based on the presented results, specific improvements of the state-of-the-art criteria are discussed.

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arXiv2022

Mathematical modelling and virtual decomposition control of heavy-duty parallel$-$serial hydraulic manipulators

This paper proposes a novel modelling approach for a heavy-duty manipulator with parallel$-$serial structures connected in series. Each considered parallel$-$serial structure contains a revolute segment with rigid links connected by a passive revolute joint and actuated by a linear hydraulic actuator, thus forming a closed kinematic loop. In addition, prismatic segments, consisting of prismatic joints driven by hydraulic linear actuators, also are considered. Expressions for actuator forces are derived using the Newton$-$Euler (N$-$E) dynamics formulation. The derivation process does not assume massless actuators decoupled from manipulator links, which is common in the Lagrange dynamics formulation. Actuator pressure dynamics are included in the analysis, leading in total to a third-order system of ordinary differential equations (ODEs). The proposed model in the N$-$E framework, with fewer parameters than its predecessors, inspires revision of the virtual decomposition control (VDC) systematic process to formulate a control law based on the new model. The virtual stability of each generic manipulator revolute and prismatic segment is obtained, leading to the Lyapunov stability of the entire robot.

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arXiv2021

Subsystem-Based Control with Modularity for Strict-Feedback Form Nonlinear Systems

This study proposes an adaptive subsystem-based control (SBC) for systematic and straightforward nonlinear~control of nth-order strict-feedback form (SFF) systems.~By decomposing the SFF system to subsystems, a generic~term (namely stability connector) can be created to address dynamic interactions between the subsystems. This 1) enables modular control design with global asymptotic stability, 2) such that both the control design and the stability analysis can be performed locally at a subsystem level, 3) while avoiding an excessive growth of the control design complexity when the system order n increases. The latter property makes the method suitable especially for high-dimensional systems. We also design a smooth projection function for addressing system parametric uncertainties. Numerical simulations demonstrate the efficiency of the method.

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arXiv2021

Decentralized Observer Design for Virtual Decomposition Control

In this paper, we incorporate velocity observer design into the virtual decomposition control (VDC) strategy of an $n$-DoF open chain robotic manipulator. Descending from the VDC strategy, the proposed design is based on decomposing the $n$-DoF manipulator into subsystems, i.e., rigid links and joints, for which the decentralized controller-observer implementation can be done locally. Similar to VDC, the combined controller-observer design is passivity-based, and we show that it achieves semiglobal exponential convergence of the tracking error. The convergence analysis is carried out using Lyapunov functions based on the observer and controller error dynamics. The proposed design is demonstrated in a simulation study of a 2-DoF open chain robotic manipulator in the vertical plane.

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arXiv2020

Force-Sensor-Less Bilateral Teleoperation Control of Dissimilar Master-Slave System with Arbitrary Scaling

This study designs a high-precision bilateral teleoperation control for a dissimilar master-slave system. The proposed nonlinear control design takes advantage of a novel subsystem-dynamics-based control method that allows designing of individual (decentralized) model-based controllers for the manipulators locally at the subsystem level. Very importantly, a dynamic model of the human operator is incorporated into the control of the master manipulator. The individual controllers for the dissimilar master and slave manipulators are connected in a specific communication channel for the bilateral teleoperation to function. Stability of the overall control design is rigorously guaranteed with arbitrary time delays. Novel features of this study include the completely force-sensor-less design for the teleoperation system with a solution for a uniquely introduced computational algebraic loop, a method of estimating the exogenous operating force of an operator, and the use of a commercial haptic manipulator. Most importantly, we conduct experiments on a dissimilar system in 2 degrees of freedom (DOF). As an illustration of the performance of the proposed system, a force scaling factor of up to 800 and position scaling factor of up to 4 was used in the experiments. The experimental results show an exceptional tracking performance, verifying the real-world performance of the proposed concept.

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