Design and control of a novel variable stiffness soft arm

Soft robot arms possess such characteristics as light weight, simple structure and good adaptability to the environment, among others. On the other hand, robust control of soft robot arms presents many difficulties. Based on these reasons, this paper presents a novel design and modelling of a fuzzy active disturbance rejection control (FADRC) controller for a soft PAM arm. The soft arm comprises three contractile and one extensor PAMs, which can vary its stiffness independently of its position in space. Force analysis for the soft arm is conducted, and stiffness model of the arm is established based on the relational model of contractile and extensor PAM. The accuracy of stiffness model for the soft arm was verified through experiments. Associated to this, a controller based on the fuzzy adaptive theory and ADRC, FADRC, has been designed to control the arm. The fuzzy adaptive theory is used to adjust the parameters of the ADRC, the control algorithm has the ability to control stiffness and position of the soft arm. In this paper, FADRC was further verified through comparative experiments on the soft arm. This paper reinforces the hypothesis that FADRC control, as an algorithm, indeed possesses good robustness and adaptive abilities. Key words: soft robot, variable stiffness, PAM, stiffness modelling, FADR

Cable Estimation-Based Control for Wire-Borne Underactuated Brachiating Robots: A Combined Direct-Indirect Adaptive Robust Approach

In this paper, we present an online adaptive robust control framework for underactuated brachiating robots traversing flexible cables. Since the dynamic model of a flexible body is unknown in practice, we propose an indirect adaptive estimation scheme to approximate the unknown dynamic effects of the flexible cable as an external force with parametric uncertainties. A boundary layer-based sliding mode control is then designed to compensate for the residual unmodeled dynamics and time-varying disturbances, in which the control gain is updated by an auxiliary direct adaptive control mechanism. Stability analysis and derivation of adaptation laws are carried out through a Lyapunov approach, which formally guarantees the stability and tracking performance of the robot-cable system. Simulation experiments and comparison with a baseline controller show that the combined direct-indirect adaptive robust control framework achieves reliable tracking performance and adaptive system identification, enabling the robot to traverse flexible cables in the presence of unmodeled dynamics, parametric uncertainties and unstructured disturbances.Comment: 8 pages, 8 figures, 2020 IEEE Conference on Decision and Control (CDC

Nonlinear control and its application to active tilting-pad bearings

The drawbacks of active magnetic bearings are arousing interest in the adaptation of mechanical bearings for active use. A promising mechanical bearing candidate for active operation is the tilting-pad bearing. In this research, we introduce an active tilting-pad bearing with linear actuators that translate each pad. The use of feedback in determining the actuator forces allows for the automatic, continuous adjustment of the pad position during the machine operation. In this work, we develop the dynamic model of the active bearing system such that the actuator forces are the control inputs. The hydrodynamic force is modeled as a spring/damper-like force with unknown damping and stiffness coefficients. Whereas in the literature, the damping and stiffness effects are normally considered linear, here, motivated by a numerical study based on the Reynolds equation, we use a nonlinear model for the stiffness force. An adaptive controller is designed to asymptotically regulate the rotor to the bearing center. The proposed control design is applicable to both the linear and nonlinear stiffness models. Simulations and experiments show that the active strategy improves the bearing performance in comparison to its traditional passive operation. Further, the experiments indicate the nonlinear stiffness-based controller slightly improves the active bearing regulation performance relative to the linear-based one. To the best of our knowledge, this dissertation is the first to report the experimental demonstration of an active tilting-pad bearing using feedback control. Since the model of the active tilting-pad bearing has a parametric strict-feedback-like form, the second part of this dissertation is dedicated to constructing new nonlinear control tools for this class of systems. Specifically, we consider the regulation and tracking control problems for multi-input/multi-output parametric strict-feedback systems in the presence of additive, exogenous disturbances and parametric uncertainties. For such systems, robust adaptive controllers usually cannot ensure asymptotic tracking or even regulation. In this work, under the assumption the disturbances are C2 with bounded time derivatives; we present a new C0 robust adaptive control construction that guarantees the output/tracking error is asymptotically driven to zero. Numerical examples illustrate the main results, including cases where the disturbances do not satisfy the aforementioned assumptions

Control Strategies for Machining with Industrial Robots

This thesis presents methods for improving machining with industrial robots using control, with focus on increasing positioning accuracy and controlling feed rate. The strong process forces arising during high-speed machining operations, combined with the limited stiffness of industrial robots, have hampered the usage of industrial robots in high-end machining tasks. However, since such manipulators may offer flexible and cost-effective machining solutions compared to conventional machine tools, it is of interest to increase the achievable accuracy using industrial robots. In this thesis, several different methods to increase the machining accuracy are presented. Modeling and control of a piezo-actuated high-dynamic compensation mechanism for usage together with an industrial robot during a machining operation, such as milling in aluminium, is considered. Position control results from experiments are provided, as well as an experimental verification of the benefit of utilizing the online compensation scheme. It is shown that the milling surface accuracy achieved with the proposed compensation mechanism is increased by up to three times compared to the uncompensated case. Because of the limited workspace and the higher bandwidth of the compensator compared to the robot, a mid-ranging approach for control of the relative position between the robot and the compensator is proposed. An adaptive, model-based solution is presented, which is verified through simulations as well as experiments, where a close correspondence with the simulations was achieved. Comparing the IAE from experiments using the proposed controller to previously established methods, a performance increase of up to 56 % is obtained. Additionally, two different approaches to increasing the accuracy of the machining task are also presented in this thesis. The first method is based on identifying a stiffness model of the robot, and using online force measurements in order to modify the position of the robot to compensate for position deflections. The second approach uses online measurements from an optical tracking system to suppress position deviations. In milling experiments performed in aluminium, the absolute accuracy was increased by up to a factor of approximately 6 and 9, for the two approaches, respectively. Robotic machining is often performed using position feedback with a conservative feed rate, to avoid excessive process forces. By controlling the applied force, realized by adjusting the feed rate of the workpiece, precise control over the material removal can be exercised. This will in turn lead to maximization of the time-efficiency of the machining task, since the maximum amount of material can be removed per time unit. This thesis presents an adaptive force controller, based on a derived model of the machining process and an identified model of the Cartesian dynamics of the robot. The controller is evaluated in both simulation and an experimental setup

A Task Process Pre-Experimental Model

The Adaptive Architectures for Command and Control (A2C2) program is a multidisciplinary program that employs a scientific basis for designing and analyzing adaptive and reconfigurable organizational structures at the Joint Task Force level. As part of its unique model-driven experimentation method, a pre-experimental model is created to support the formulation of hypotheses, the determination of key variables and parameter values, and the prediction of organizational performance. The pre-experimental model is used to explore the parameters of the experimental design in order to determine the appropriate region to conduct officer-in-the-loop experiments at the Naval Postgraduate School. A pre-experimental model based on the task process was created for an upcoming A2C2 subject experiment, which will examine the congruence between organizational structure and mission requirements. The pre-experimental model is a dynamic model created with Colored Petri nets, which can represent the changes in the task environment over time by implementing the stages of the tasks (i.e., detection, identification, attack, destroy, and disappear). The simulator used in the subject experiments, Distributed Dynamic Decision-Making (DDD), records timing information over the life of each task. Therefore, timing information regarding the tasks can be extracted from the output files of the trial experimental runs and included in the model before the final experimental simulations. In this way the model can be validated at the pre-experimental stage

Optimized Adaptive Sliding-mode Position Control System for Linear Induction Motor Drive

[[abstract]]This paper proposes an optimized adaptive position control system applied for a linear induction motor (LIM) drive taking into account the longitudinal end effects and uncertainties including the friction force. The dynamic mathematical model of an indirect field-oriented LIM drive is firstly derived for controlling the LIM. On the basis of a backstepping control law, a sliding mode controller (SMC) with embedded fuzzy boundary layer is designed to compensate the lumped uncertainties during the tracking control of periodic reference trajectories. Since it is difficult to obtain the bound of lumped uncertainties in advance in practical applications, an adaptive tuner based on the sense of Lyapunov stability theorem is derived to adjust the fuzzy boundary parameters in real-time. It is a quite complicated process of parameter tuning, especially for the proposed controller, due to the difficulty arisen from lacking of the accurate mathematical model of a system accompanied with unknown disturbance. Therefore, the soft-computing technique is adopted for off-line optimizing the controller parameters. The effectiveness of the proposed control scheme is validated through simulations and experiments for several scenarios. Finally, the advantages of performance improvement and robustness are illustrated at the end of the optimization procedure.[[conferencetype]]國際[[conferencedate]]20130410~20130412[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Paris, Franc

Force and impedance control for hydraulically driven hexapod robot walking on uneven terrain

A variety approach of multi-legged robot designs, especially on a large scale design with hydraulically driven actuators exist, but most of it still unsolved and used primitive techniques on control solutions. This made this area of research still far from demonstrating the scientific solutions, which is more towards developing and optimizing the algorithm, control technique and software engineering for practical locomotion (flexibility and reliability). Therefore in this thesis,the study is done to propose two categories of solution for statically stable and hydraulically driven hexapod robot, named COMET-IV, which are dynamic walking trajectory generation and force/impedance control implementation (during body start patching), in order to solve the stability problems (horizontal) that encountered when walking on extremely uneven terrains.Only three sensors are used for control feedback; potentiometers (each leg joint), pressure sensors (hydraulic cylinders) and attitude sensor (center of body). For dynamic walking trajectory generation, the fixed/determined of tripod walking trajectory is modified with force threshold-based, named as environment trailed trajectory (ETT),on each first step of foot during support phase (preliminary sensing uneven terrain surfaces). Moreover,the proposed dynamic trajectory generation is then upgraded with capability of omni-directional walking with a proposed center of body rotational-based method. The instability of using the ETT module alone and with proposed hybrid force/position control in the previous progress, during body patching on walking session is then solved using the proposed pull-back position-based force control (PPF). PPF controller is derived from the ETT module itself and supported by proposed compliant (switching) mechanism, logical attitude control and dynamic swing rising control. The limitation of PPF controller applied with ETT module for walking on uneven terrain contains extreme soft surface makes the study narrowed to the impedance control approaches as a replacement of PPF controller. Three new adaptive impedance controller are designed and proposed: Optimal single leg impedance control based on body inertia, Optimal center of mass—based impedance control based on body inertia and Single leg impedance control with self-tuning stiffness. To reduce the hard swinging/shaking of the robot's body in motion that arise after applying the proposed impedance controllers, fuzzy logic control via Takagaki-Sugeno-Kang (TSK) model is proposed to be cascaded on the input feedback of the controller.The study has verified the effectiveness of both categories of control unit (dynamic trajectory,force controller and impedance controllers) combination throughout several experiments of COMET-IV walking on uneven/unstructured terrains