FEA-based tracking control of flexible body switching dynamic structure

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
M. R. Homaeinezhad ◽  
F. FotoohiNia
Keyword(s):  
Continuum Mechanics ◽  
Tracking Control ◽  
Sliding Mode ◽  
Equations Of Motion ◽  
Operating Conditions ◽  
System Stability ◽  
Control Input ◽  
Element Analysis ◽  
Control Effort ◽  
Modeling Uncertainties

Abstract In dynamically switched systems with unknown switching signal, the control system is conventionally designed based on the worst switching scenario to ensure system stability. Such conservative design demands excessive control effort in less critical switching configurations. In the case of continuum mechanics systems, such excessive control inputs result in increased structural deformations and resultant modeling uncertainties. These deformations alter differential equations of motion which cripple the task of control. In this paper, a new approach for tracking control of uncertain continuum mechanics multivariable systems undergoing switching dynamics and unknown time delay has been proposed. Control algorithm is constructed based on the mathematical rigid model of the plant and a Common Lyapunov Function (CLF) is proposed upon sliding hyperplane regarding all switching configurations. Considering the model-based nature of sliding mode control (SMC) and inevitable uncertainties induced from modeling simplifications of continuum system or parameter evaluation errors, Finite Element Analysis (FEA) is utilized to approximate total model uncertainties. To obtain robust stability, instead of conventional switching functions in the construction of control law, the control inputs are selected such that system dynamics reside within stability bounds which are calculated based on the Lyapunov asymptotic stability criterion. Therefore, the unwanted chattering issue caused by continuous switching is not observed in control input signals. Eventually, the accuracy of the proposed method has been verified through the student version of ANSYS® mechanical APDL-based simulations and its effectiveness has been demonstrated in multiple operating conditions.

Globally neural-adaptive simultaneous position and torque variable structure tracking control for permanent magnet synchronous motors

2016 ◽  
Vol 23 (1) ◽  
pp. 147-163 ◽  
Author(s):  
Chih-Lyang Hwang ◽  
Wei-Li Fang ◽  
Ching-Long Shih
Keyword(s):  
Permanent Magnet ◽  
Tracking Control ◽  
Variable Structure ◽  
Operating Conditions ◽  
System Stability ◽  
Control Input ◽  
Neural Network Models ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors ◽  
Control Gain

A globally neural-adaptive simultaneous position and torque variable structure tracking control (GNASPTVSTC) for the permanent magnet synchronous motors (PMSMs) subjected to excess uncertainties (e.g., time-varying system parameters, friction and load torques for different operating conditions, the avoidance of zero control gain, the similar convergence of position and torque) is developed. Based on Lyapunov stability criterion, the desired torque is first derived from the mechanical subsystem. A simultaneous position and torque variable structure tracking control (SPTVSTC) with the avoidance of zero control gain and the similar convergence of position and torque is first designed to obtain acceptable performance for the PMSM with mild uncertainties. To improve the PMSM in the presence of excess uncertainties, the integration of SPTVSTC and two on-line neural network models for uncertainties is employed to construct the proposed GNASPTVSTC. For approximating these non-autonomous uncertainties, they are assumed to be absolutely bounded for time variable and relatively bounded for other variables, respectively. It not only improves the steady state performance as compared with SPTVSTC, but also enhances the system stability in the face of excess uncertainties. The compared simulation results validate the global tracking ability outside of approximated set and the excess robustness for different amplitudes of uncertainties and saturated control input.

Obstacle avoidance control of a human-in-the-loop mobile robot system using harmonic potential fields

Robotica ◽  
2017 ◽  
Vol 36 (4) ◽  
pp. 463-483 ◽  
Author(s):  
C. Ton ◽  
Z. Kan ◽  
S. S. Mehta
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Sliding Mode ◽  
Harmonic Potential ◽  
Control Allocation ◽  
Control Input ◽  
Continuous Control ◽  
Control Effort ◽  
Human In The Loop ◽  
Allocation Function

SUMMARYThis paper considers applications where a human agent is navigating a semi-autonomous mobile robot in an environment with obstacles. The human input to the robot can be based on a desired navigation objective, which may not be known to the robot. Additionally, the semi-autonomous robot can be programmed to ensure obstacle avoidance as it navigates the environment. A shared control architecture can be used to appropriately fuse the human and the autonomy inputs to obtain a net control input that drives the robot. In this paper, an adaptive, near-continuous control allocation function is included in the shared controller, which continuously varies the control effort exerted by the human and the autonomy based on the position of the robot relative to obstacles. The developed control allocation function facilitates the human to freely navigate the robot when away from obstacles, and it causes the autonomy control input to progressively dominate as the robot approaches obstacles. A harmonic potential field-based non-linear sliding mode controller is developed to obtain the autonomy control input for obstacle avoidance. In addition, a robust feed-forward term is included in the autonomy control input to maintain stability in the presence of adverse human inputs, which can be critical in applications such as to prevent collision or roll-over of smart wheelchairs due to erroneous human inputs. Lyapunov-based stability analysis is presented to guarantee finite-time stability of the developed shared controller, i.e., the autonomy guarantees obstacle avoidance as the human navigates the robot. Experimental results are provided to validate the performance of the developed shared controller.

Controlling Chaos by Hybrid System Based on FREN and Sliding Mode Control

2005 ◽  
Vol 128 (2) ◽  
pp. 352-358 ◽  
Author(s):  
C. Treesatayapun ◽  
S. Uatrongjit
Keyword(s):  
Sliding Mode ◽  
Adaptive Controller ◽  
Descent Method ◽  
Fuzzy Rules ◽  
System Stability ◽  
Steepest Descent Method ◽  
Upper And Lower Bounds ◽  
Adaptation Algorithm ◽  
Control Effort ◽  
Fine Tune

This paper presents a direct adaptive controller for chaotic systems. The proposed adaptive controller is constructed using the network called fuzzy rules emulated network (FREN). FREN’s structure is based on human knowledge in the form of fuzzy rules. Parameter adaptation algorithm based on the steepest descent method is presented to fine tune the controller’s performance. To improve the system stability, the modified sliding mode algorithm is applied to estimate the upper and lower bounds of the control effort. The suitable control effort is generated by FREN and kept within these bounds. Some computer simulations of using the controller to control the Hénon map have been performed to demonstrate the performance of the proposed controller.

Optimal Control of a Wheeled Mobile Cable-Driven Parallel Robot ICaSbot with Viscoelastic Cables

Robotica ◽  
2019 ◽  
Vol 38 (8) ◽  
pp. 1513-1537 ◽  
Author(s):  
Moharam Habibnejad Korayem ◽  
Mahdi Yousefzadeh ◽  
Hami Tourajizadeh
Keyword(s):  
Feedback Linearization ◽  
Parallel Robot ◽  
System Stability ◽  
Control Input ◽  
Linear Quadratic ◽  
Combined System ◽  
Viscoelastic System ◽  
Control Effort ◽  
Cable Robot ◽  
Data Feedback

SUMMARYIn this paper, a new mobile cable-driven parallel robot is proposed by mounting a spatial cable robot on a wheeled mobile robot. This system includes all the advantages of cable robots such as high ratio of payload to weight and good stiffness and accuracy while its deficiency of limited workspace is eliminated by the aid of its mobile chassis. The combined system covers a vast workspace area whereas it has negligible vibrations and cable sag due to using shorter cables. The dynamic equations are derived using Gibbs–Appell formulation considering viscoelasticity of the cables. Therefore, the more realistic viscoelastic cable model of the robot reveals the system flexibility effect and shows the requirements needed to control the end-effector in the conditions with cable elasticity. The viscoelastic system stability is investigated based on the input–output feedback linearization and using only the actuators feedback data. Feedback linearization controller is equipped by two additional controllers, that is, the optimal controller based on Linear Quadratic Regulator (LQR) method and finite horizon model predictive approach. They are used to control the system compromising between the control effort and error signals of the feedback linearized system. The applied control input to the robot plant is the voltage signal limited to a specified band. The validity of modeling and the designed controller efficiency are investigated using MATLAB simulation and its verification is accomplished by experimental tests conducted on the manufactured cable robot, ICaSbot.

Experimental and Numerical Comparison Between Two Nonlinear Control Logics

2016 ◽  
Vol 08 (05) ◽  
pp. 1650061 ◽  
Author(s):  
Francesco Ripamonti ◽  
Egidio Leo ◽  
Ferruccio Resta
Keyword(s):  
Nonlinear Control ◽  
Sliding Mode ◽  
Nonlinear Behavior ◽  
Operating Conditions ◽  
System Stability ◽  
Flexible Manipulator ◽  
Engineering Practice ◽  
Numerical Comparison ◽  
System A ◽  
Nonlinear Form

Nonlinear behavior is present in the operating conditions of many mechanical systems, especially if nonsmall oscillations are considered. In these cases, in order to improve vibration control performance, a common engineering practice is to design the control system on a set of linearized models, for given operating conditions. The well-known gain-scheduling technique allows the parameters of the control law to be changed according to the current working condition, also increasing system stability. However, more recently new control logics directly applicable to the systems in nonlinear form have been developed. The aim of this paper is to study, both numerically and experimentally, the dynamic of a mechanical system (a 3-link flexible manipulator) comparing the performance of a fully nonlinear control (the sliding-mode control) and a standard linearized approach.

scholarly journals Adaptive Backstepping Sliding Mode Control of Air-Breathing Hypersonic Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shuo Wang ◽  
Ju Jiang ◽  
Chaojun Yu
Keyword(s):  
Sliding Mode Control ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Hypersonic Vehicles ◽  
Control Input ◽  
Backstepping Method ◽  
Trajectory Tracking Control ◽  
Air Breathing ◽  
Mode Control

In this paper, a controller combining backstepping and adaptive supertwisting sliding mode control method is proposed for altitude and velocity tracking control of air-breathing hypersonic vehicles (AHVs). Firstly, the nonlinear longitudinal model of AHV is introduced and transformed into a strict feedback form, to which the backstepping method can be applied. Considering the longitudinal trajectory tracking control problem (altitude control and velocity control), the altitude tracking control system is decomposed to several one-order subsystems based on the backstepping method, and an adaptive supertwisting sliding mode controller is designed for each subsystem, in order to obtain the virtual control variables and actual control input. Secondly, the overall stability of the closed-loop system is proved by the Lyapunov stability theory. At last, the simulation is carried out on an AHV model. The results show that the proposed controller has good control performances and good robustness in the parameter perturbation case.

Optimal Selection of Basis Functions for Robust Tracking Control of Uncertain Linear Systems - with Application to 3D Printing

2021 ◽  
Author(s):  
Keval Ramani ◽  
Chinedum Okwudire
Keyword(s):  
Linear Systems ◽  
Tracking Control ◽  
Basis Functions ◽  
Frobenius Norm ◽  
Control Input ◽  
Optimal Selection ◽  
Control Methods ◽  
Tracking Accuracy ◽  
Control Effort ◽  
Selection Of

Abstract There is growing interest in the use of the filtered basis functions (FBF) approach to track linear systems, especially nonminimum phase (NMP) plants, because of its distinct advantages compared to other tracking control methods in the literature. The FBF approach expresses the control input to the plant as a linear combination of basis functions with unknown coefficients. The basis functions are forward filtered through the plant dynamics and the coefficients are selected such that tracking error is minimized. Similar to other feedforward control methods, the tracking accuracy of the FBF approach deteriorates in the presence of uncertainties. However, unlike other methods, the FBF approach presents flexibility in terms of the choice of the basis functions, which can be used to improve its accuracy. This paper analyzes the effect of the choice of the basis functions on the tracking accuracy of FBF, in the presence of uncertainties, using the Frobenius norm of the lifted system representation of FBF's error dynamics. Based on the analysis, a methodology for optimal selection of basis functions to maximize robustness is proposed, together with an approach to avoid large control effort when it is applied to NMP systems. The basis functions resulting from this process are called robust basis functions. Applied experimentally to a desktop 3D printer with uncertain NMP dynamics, up to 48% improvement in tracking accuracy is achieved using the proposed robust basis functions compared to B-splines, while utilizing much less control effort.

Sliding Mode Control of Mechanical Systems Actuated by Shape Memory Alloy

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
Hashem Ashrafiuon ◽  
Vijay Reddy Jala
Keyword(s):  
Sliding Mode Control ◽  
Shape Memory ◽  
Sliding Mode ◽  
Equations Of Motion ◽  
Mechanical Systems ◽  
Constitutive Law ◽  
System Model ◽  
Control Law ◽  
Mode Control ◽  
Modeling Uncertainties

This paper presents a model-based sliding mode control law for mechanical systems, which use shape memory alloys (SMAs) as actuators. The systems under consideration are assumed to be fully actuated and represented by unconstrained equations of motion. A system model is developed by combining the equations of motion with SMA heat convection, constitutive law, and phase transformation equations, which account for hysteresis. The control law is introduced using asymptotically stable second-order sliding surfaces. Robustness is guaranteed through the inclusion of modeling uncertainties in the controller development. The control law is developed assuming only positions are available for measurement. The unmeasured states, which include velocities and SMA temperatures and stresses, are estimated using an extended Kalman filter based on the nonlinear system model. The control law is applied to a three-link planar robot for position control problem. Simulation and experimental results show good agreement and verify the robustness of the control law despite significant modeling uncertainty.

scholarly journals A Novel Active Fault-Tolerant Tracking Control for Robot Manipulators with Finite-Time Stability

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8101
Author(s):  
Thanh Nguyen Truong ◽  
Anh Tuan Vo ◽  
Hee-Jun Kang ◽  
Mien Van
Keyword(s):  
Dynamic Model ◽  
Finite Time ◽  
Tracking Control ◽  
Sliding Mode ◽  
Robotic Manipulators ◽  
Convergence Speed ◽  
Lyapunov Theory ◽  
Control Input ◽  
Observation Error ◽  
Simulation Performance

Many terminal sliding mode controllers (TSMCs) have been suggested to obtain exact tracking control of robotic manipulators in finite time. The ordinary method is based on TSMCs that secure trajectory tracking under the assumptions such as the known robot dynamic model and the determined upper boundary of uncertain components. Despite tracking errors that tend to zero in finite time, the weakness of TSMCs is chattering, slow convergence speed, and the need for the exact robot dynamic model. Few studies are handling the weakness of TSMCs by using the combination between TSMCs and finite-time observers. In this paper, we present a novel finite-time fault tolerance control (FTC) method for robotic manipulators. A finite-time fault detection observer (FTFDO) is proposed to estimate all uncertainties, external disturbances, and faults accurately and on time. From the estimated information of FTFDO, a novel finite-time FTC method is developed based on a new finite-time terminal sliding surface and a new finite-time reaching control law. Thanks to this approach, the proposed FTC method provides a fast convergence speed for both observation error and control error in finite time. The operation of the robot system is guaranteed with expected performance even in case of faults, including high tracking accuracy, small chattering behavior in control input signals, and fast transient response with the variation of disturbances, uncertainties, or faults. The stability and finite-time convergence of the proposed control system are verified that they are strictly guaranteed by Lyapunov theory and finite-time control theory. The simulation performance for a FARA robotic manipulator proves the proposed control theory’s correctness and effectiveness.

Finite Element Modelling of Rotating Tires in the Time Domain

2002 ◽  
Vol 30 (1) ◽  
pp. 19-33 ◽  
Author(s):  
O. A. Olatunbosun ◽  
A. M. Burke
Keyword(s):  
Finite Element ◽  
Dynamic Behavior ◽  
Time Domain ◽  
Equations Of Motion ◽  
Operating Conditions ◽  
Element Analysis ◽  
Successful Model ◽  
Linear Effects ◽  
Tire Rotation ◽  
The Time Domain

Abstract Finite element analysis presents an opportunity for a detailed study of the dynamic behavior of a rotating tire under real operating conditions providing a better understanding of the influence of tire construction and material detail on tire dynamic behavior in such areas as ride, handling and noise and vibration transmission. Modelling issues that need to be considered include non-linear effects due to tire inflation and hub loading, tire/road contact and time domain solution of the equations of motion. In this paper techniques and strategies for tire rotation modelling are presented and discussed as a guide to the creation of a successful model.

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