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.

scholarly journals Implementation and intelligent gain tuning feedback–based optimal torque control of a rotary parallel robot

2021 ◽  
pp. 107754632110191
Author(s):  
Farzam Tajdari ◽  
Naeim Ebrahimi Toulkani
Keyword(s):  
Real Time ◽  
Tracking Error ◽  
Parallel Robot ◽  
Torque Control ◽  
Test Bed ◽  
Linear Quadratic ◽  
Control Effort ◽  
The Real ◽  
Unknown Disturbances ◽  
Quadratic Integral

Aiming at operating optimally minimizing error of tracking and designing control effort, this study presents a novel generalizable methodology of an optimal torque control for a 6-degree-of-freedom Stewart platform with rotary actuators. In the proposed approach, a linear quadratic integral regulator with the least sensitivity to controller parameter choices is designed, associated with an online artificial neural network gain tuning. The nonlinear system is implemented in ADAMS, and the controller is formulated in MATLAB to minimize the real-time tracking error robustly. To validate the controller performance, MATLAB and ADAMS are linked together and the performance of the controller on the simulated system is validated as real time. Practically, the Stewart robot is fabricated and the proposed controller is implemented. The method is assessed by simulation experiments, exhibiting the viability of the developed methodology and highlighting an improvement of 45% averagely, from the optimum and zero-error convergence points of view. Consequently, the experiment results allow demonstrating the robustness of the controller method, in the presence of the motor torque saturation, the uncertainties, and unknown disturbances such as intrinsic properties of the real test bed.

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.

Optimal regulation of a cable robot in presence of obstacle using optimal adaptive feedback linearization approach

Robotica ◽  
2014 ◽  
Vol 33 (4) ◽  
pp. 933-952 ◽  
Author(s):  
M. H. Korayem ◽  
H. Tourajizadeh ◽  
A. Zehfroosh ◽  
A. H. Korayem
Keyword(s):  
Obstacle Avoidance ◽  
Feedback Linearization ◽  
Optimal Path ◽  
Linear Quadratic Regulator ◽  
Experimental Tests ◽  
Linear Quadratic ◽  
Optimal Regulation ◽  
Cable Robot ◽  
Optimal Controllers ◽  
Feedback Linearization Approach

SUMMARYOptimal path planning of a closed loop cable robot, between two predefined points in presence of obstacles is the goal of this paper. This target is met by proposing a new method of optimal regulation for non linear systems while Dynamic Load Carrying Capacity (DLCC) of the robot is supposed as the related cost function. Feedback linearization is used to linearize the system while Linear Quadratic Regulator (LQR) is employed to optimize the DLCC of the system based on torque and error constraints. Obstacle avoidance for both the end-effector and cables is also considered by the aid of designing an adaptive local obstacle avoidance controller. As a result of linearized nature of the proposed optimal regulation and obstacle avoidance, fast calculation for real time applications is possible. Therefore, formulation of the optimal feedback linearization, together with calculating the DLCC of the robot based on the presented constraints is derived. Finally, a simulation study is performed to study the optimal dynamics and also the maximum DLCC of the cable robot in presence of obstacles. Simulation results are eventually compared with experimental tests conducted on IUST Cable Suspended Robot (ICaSbot) to verify the validity and efficiency of the proposed optimal controllers.

Modal decoupling control for a double gimbal magnetically suspended control moment gyroscope based on modal controller and feedback linearization method

2014 ◽  
Vol 228 (13) ◽  
pp. 2303-2313 ◽  
Author(s):  
Xiaocen Chen ◽  
Yuan Ren
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
Linearization Method ◽  
System Stability ◽  
Control Effort ◽  
Decoupling Method ◽  
Control Moment Gyroscope ◽  
Control Moment ◽  
Gyroscopic Effects ◽  
Modal Controller

To effectively reject the gyroscopic effects and moving-gimbal effects of the double gimbal magnetically suspended control moment gyroscope (DGMSCMG) and to avoid high control effort, this paper proposes a novel control method based on modal decoupling strategy. Modal controller is employed to realize the modal separation of the translation and rotation modes of the magnetically suspended rotor (MSR). Then the dynamic coupling among the two rotation modes of the MSR system and the two rotational motions of the gimbal servo systems have been decoupled by using differential geometry theory. Dynamic compensation filters have been designed to improve the decoupling performance and the system stability without large control resource. Compared with the existing channel decoupling method, the presented one can not only realize the separate control of stiffness and damping of the MSR but also simplify the control system design significantly. The simulation results verify the effectiveness and superiority of the proposed method.

An LQ Approach to Active Control of Vibrations in Helicopters

1996 ◽  
Vol 118 (3) ◽  
pp. 482-488 ◽  
Author(s):  
Sergio Bittanti ◽  
Fabrizio Lorito ◽  
Silvia Strada
Keyword(s):  
Optimal Control ◽  
Active Control ◽  
Linear Quadratic ◽  
Control Effort ◽  
Vibration Effect ◽  
Suitable Definition ◽  
Lq Optimal Control ◽  
The One ◽  
Definition Of ◽  
And Control

In this paper, Linear Quadratic (LQ) optimal control concepts are applied for the active control of vibrations in helicopters. The study is based on an identified dynamic model of the rotor. The vibration effect is captured by suitably augmenting the state vector of the rotor model. Then, Kalman filtering concepts can be used to obtain a real-time estimate of the vibration, which is then fed back to form a suitable compensation signal. This design rationale is derived here starting from a rigorous problem position in an optimal control context. Among other things, this calls for a suitable definition of the performance index, of nonstandard type. The application of these ideas to a test helicopter, by means of computer simulations, shows good performances both in terms of disturbance rejection effectiveness and control effort limitation. The performance of the obtained controller is compared with the one achievable by the so called Higher Harmonic Control (HHC) approach, well known within the helicopter community.

scholarly journals Two Inverse Problems Solution by Feedback Tracking Control

Axioms ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 137
Author(s):  
Vladimir Turetsky
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Feedback Linearization ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Linear Quadratic Tracking ◽  
Ill Posed ◽  
Quadratic Optimal Control ◽  
Quadratic Tracking

Two inverse ill-posed problems are considered. The first problem is an input restoration of a linear system. The second one is a restoration of time-dependent coefficients of a linear ordinary differential equation. Both problems are reformulated as auxiliary optimal control problems with regularizing cost functional. For the coefficients restoration problem, two control models are proposed. In the first model, the control coefficients are approximated by the output and the estimates of its derivatives. This model yields an approximating linear-quadratic optimal control problem having a known explicit solution. The derivatives are also obtained as auxiliary linear-quadratic tracking controls. The second control model is accurate and leads to a bilinear-quadratic optimal control problem. The latter is tackled in two ways: by an iterative procedure and by a feedback linearization. Simulation results show that a bilinear model provides more accurate coefficients estimates.

Analysis and Optimization of a New Differentially Driven Cable Parallel Robot

2015 ◽  
Vol 7 (3) ◽  
Author(s):  
Hamed Khakpour ◽  
Lionel Birglen ◽  
Souheil-Antoine Tahan
Keyword(s):  
Kinematic Analysis ◽  
Design Methodology ◽  
Degrees Of Freedom ◽  
Parallel Robot ◽  
Cable Robot ◽  
Proper Design ◽  
Two Indices ◽  
Three Degrees Of Freedom ◽  
Cable Robots

In this paper, a new three degrees of freedom (DOF) differentially actuated cable parallel robot is proposed. This mechanism is driven by a prismatic actuator and three cable differentials. Through this design, the idea of using differentials in the structure of a spatial cable robot is investigated. Considering their particular properties, the kinematic analysis of the robot is presented. Then, two indices are defined to evaluate the workspaces of the robot. Using these indices, the robot is subsequently optimized. Finally, the performance of the optimized differentially driven robot is compared with fully actuated mechanisms. The results show that through a proper design methodology, the robot can have a larger workspace and better performance using differentials than the fully driven cable robots using the same number of actuators.

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.

scholarly journals Nonlinear Control Design of a Half-Car Model Using Feedback Linearization and an LQR Controller

2020 ◽  
Vol 10 (9) ◽  
pp. 3075
Author(s):  
Muhammad Aseer Khan ◽  
Muhammad Abid ◽  
Nisar Ahmed ◽  
Abdul Wadood ◽  
Herie Park
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
Control Technique ◽  
Effective Control ◽  
Ride Quality ◽  
Linear Quadratic ◽  
Suspension Systems ◽  
Car Model ◽  
Road Disturbance ◽  
Lqr Controller

Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for off-road applications. The nonlinearities tend to degrade the performance of active suspension systems; these introduce harshness to the ride quality and reduce off-road mobility. Typical control strategies rely on linear models of the suspension dynamics. While these models are convenient, nominally accurate, and controllable due to the abundance of linear control techniques, they neglect the nonlinearities present in real suspension systems. The techniques already implemented and methods used to cope with problem of Half-Car model were studied. Every method and technique had some drawbacks in terms of complexity, cost-effectiveness, and ease of real time implementation. In this paper, an improved control method for Half-Car model was proposed. First, input/output feedback linearization was performed to convert the nonlinear system of Half-Car model into an equivalent linear system. This was followed by a Linear Quadratic Regulator (LQR) controller. This controller had minimized the effects of road disturbances by designing a gain matrix with optimal robustness properties. The proposed control technique was applied in the presence of the deterministic road disturbance. The results were verified using the Matlab/Simulink toolbox.

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