scholarly journals Switching Perfect Control Algorithm

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 816 ◽  
Author(s):  
Marek Krok ◽  
Wojciech P. Hunek ◽  
Tomasz Feliks
Keyword(s):  
Control Algorithm ◽  
Closed Loop ◽  
Switching Control ◽  
Control Law ◽  
Matlab Simulink ◽  
Control Framework ◽  
Nonlinear Plants ◽  
New Framework

The application of the switching control framework to the perfect control algorithm is presented in this paper. Employing the nonunique matrix inverses, the different closed-loop properties are obtained and further enhanced with possible switching methodology implementation. Simulation examples performed in the MATLAB/Simulink environment clearly show that the new framework can lead to benefits in terms of the control energy, speed, and robustness of the perfect control law. The possibility of transferring the new obtained results to the symmetrical nonlinear plants seems to be immediate.

scholarly journals Open-closed Iterative Learning Control Algorithm for Exoskeleton Rehabilitation Purposes

2019 ◽  
Vol 292 ◽  
pp. 01010
Author(s):  
Mihailo Lazarević ◽  
Nikola Živković ◽  
Darko Radojević
Keyword(s):  
Iterative Learning Control ◽  
Control Algorithm ◽  
Closed Loop ◽  
Learning Control ◽  
Open Loop ◽  
Iterative Learning ◽  
Control Law ◽  
Exact Linearization ◽  
Outer Loop ◽  
Control Scheme

The paper designs an appropriate iterative learning control (ILC) algorithm based on the trajectory characteristics of upper exosk el eton robotic system. The procedure of mathematical modelling of an exoskeleton system for rehabilitation is given and synthesis of a control law with two loops. First (inner) loop represents exact linearization of a given system, and the second (outer) loop is synthesis of a iterative learning control law which consists of two loops, open and closed loop. In open loop ILC sgnPDD2 is applied, while in feedback classical PD control law is used. Finally, a simulation example is presented to illustrate the feasibility and effectiveness of the proposed advanced open-closed iterative learning control scheme.

Iterative Learning Impedance Control in Gait Rehabilitation Robot

2014 ◽  
Vol 494-495 ◽  
pp. 1084-1087
Author(s):  
Fu Cheng Cao ◽  
Hai Xin Sun ◽  
Li Rong Wang
Keyword(s):  
Iterative Learning Control ◽  
Control Algorithm ◽  
Closed Loop ◽  
Impedance Control ◽  
Iterative Learning ◽  
Gait Rehabilitation ◽  
Control Law ◽  
Rehabilitation Robot ◽  
Simulation Results ◽  
Impedance Parameters

An iterative learning impedance control algorithm is presented to control a gait rehabilitation robot. According to the circumstances of the patient, the appropriate rehabilitation target impedance parameters are set. With the adoption of iterative learning control law, the impedance error in the closed loop is guaranteed to converge to zero and the iterative trajectories follow the desired trajectories over the entire operation interval. The effectiveness of the proposed method is shown through numerical simulation results.

scholarly journals Continuous-Time Perfect Control Algorithm—A State Feedback Approach

2021 ◽  
Vol 11 (16) ◽  
pp. 7466
Author(s):  
Marek Krok ◽  
Wojciech P. Hunek ◽  
Paweł Majewski
Keyword(s):  
Design Process ◽  
Process Simulation ◽  
Continuous Time ◽  
Control Algorithm ◽  
State Feedback ◽  
Closed Loop ◽  
Control Design ◽  
Control Law ◽  
New Approach

In this paper, a new approach to the continuous-time perfect control algorithm is given. Focusing on the output derivative, it is shown that the discussed control law can effectively be implemented in terms of state-feedback scenarios. Moreover, the application of nonunique matrix inverses is also taken into consideration during the perfect control design process. Simulation examples given within this work allow us to showcase the main properties obtained for continuous-time perfect control closed-loop plants.

Acceleration-Driven-Damper (ADD): An Optimal Control Algorithm For Comfort-Oriented Semiactive Suspensions

2004 ◽  
Vol 127 (2) ◽  
pp. 218-229 ◽  
Author(s):  
Sergio M. Savaresi ◽  
Enrico Silani ◽  
Sergio Bittanti
Keyword(s):  
Optimal Control ◽  
Numerical Analysis ◽  
Control Strategy ◽  
Control Algorithm ◽  
Closed Loop ◽  
Control Strategies ◽  
Control Algorithms ◽  
Road Vehicles ◽  
Control Framework ◽  
Analysis Of Performance

The problem considered in this paper is the design and analysis of control strategies for semiactive suspensions in road vehicles. The most commonly used control framework is the well-known Sky–Hook (SH) damping. Two-state or linear approximation of the SH concept are typically implemented. The goal of this paper is to analyze the optimality of SH-based control algorithms, and to propose an innovative control strategy, named Acceleration-Driven-Damper (ADD) control. It is shown that ADD is optimal in the sense that it minimizes the vertical body acceleration (comfort objective) when no road-preview is available. This control strategy is extremely simple; it requires the same sensors of the SH algorithms, and a simple two-state controllable damper. In order to assess and to compare the closed-loop performance of the SH and ADD control strategies, both a theoretical and a numerical analysis of performance are proposed.

Feedback control framework for car-like robots using the unicycle controllers

Robotica ◽  
2011 ◽  
Vol 30 (4) ◽  
pp. 517-535 ◽  
Author(s):  
Maciej Michałek ◽  
Krzysztof Kozłowski
Keyword(s):  
Stability Analysis ◽  
Feedback Control ◽  
Closed Loop ◽  
Path Following ◽  
Rear Wheel ◽  
Front Wheel ◽  
Steering Angle ◽  
Formal Stability ◽  
Control Framework ◽  
Error Dynamics

SUMMARYThe paper introduces a novel general feedback control framework, which allows applying the motion controllers originally dedicated for the unicycle model to the motion task realization for the car-like kinematics. The concept is formulated for two practically meaningful motorizations: with a front-wheel driven and with a rear-wheel driven. All the three possible steering angle domains for car-like robots—limited and unlimited ones—are treated. Description of the method is complemented by the formal stability analysis of the closed-loop error dynamics. The effectiveness of the method and its limitations have been illustrated by numerous simulations conducted for the three main control tasks, namely, for trajectory tracking, path following, and set-point regulation.

A Digital Algorithm for Near-Minimum-Time Control of Robot Manipulators

1987 ◽  
Vol 109 (4) ◽  
pp. 320-327 ◽  
Author(s):  
C. K. Kao ◽  
A. Sinha ◽  
A. K. Mahalanabis
Keyword(s):  
Control Algorithm ◽  
State Feedback ◽  
Closed Loop ◽  
Robot Manipulator ◽  
Minimum Time ◽  
State Feedback Control ◽  
Final States ◽  
Closed Loop System ◽  
Time Control ◽  
Digital Algorithm

A digital state feedback control algorithm has been developed to obtain the near-minimum-time trajectory for the end-effector of a robot manipulator. In this algorithm, the poles of the linearized closed loop system are judiciously placed in the Z-plane to permit near-minimum-time response without violating the constraints on the actuator torques. The validity of this algorithm has been established using numerical simulations. A three-link manipulator is chosen for this purpose and the results are discussed for three different combinations of initial and final states.

Industrial compliant robot bases in interaction tasks: a force tracking algorithm with coupled dynamics compensation

Robotica ◽  
2016 ◽  
Vol 35 (8) ◽  
pp. 1732-1746 ◽  
Author(s):  
Loris Roveda ◽  
Nicola Pedrocchi ◽  
Federico Vicentini ◽  
Lorenzo Molinari Tosatti
Keyword(s):  
Closed Loop ◽  
Control Law ◽  
Light Weight ◽  
Mobile Platforms ◽  
Control Laws ◽  
Assembly Task ◽  
Base Position ◽  
Force Tracking ◽  
Compliant Robot ◽  
Target Force

SUMMARYLight-weight manipulators are used in industrial tasks mounted on mobile platforms to improve flexibility. However, such mountings introduce compliance affecting the tasks. This work deals with such scenarios by designing a controller that also takes into account compliant environments. The controller allows the tracking of a target force using the estimation of the environment stiffness (EKF) and the estimation of the base position (KF), compensating the robot base deformation. The closed-loop stability has been analyzed. Observers and the control law have been validated in experiments. An assembly task is considered with a standard industrial non-actuated mobile platform. Control laws with and without base compensation are compared.

An Economic Model Predictive Control Approach for Wind Power Smoothing and Tower Load Mitigation

2018 ◽  
Author(s):  
Mohamed M. Alhneaish ◽  
Mohamed L. Shaltout ◽  
Sayed M. Metwalli
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Model Predictive Control ◽  
Wind Power ◽  
Predictive Control ◽  
Economic Model ◽  
Control Algorithm ◽  
Fatigue Load ◽  
Economic Model Predictive Control ◽  
Control Framework

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.

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