scholarly journals Feedforward of Measurable Disturbances to Improve Multi-Input Feedback Control

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2114
Author(s):  
Javier Rico-Azagra ◽  
Montserrat Gil-Martínez
Keyword(s):  
Feedback Control ◽  
Model Uncertainty ◽  
Control Architecture ◽  
Control Input ◽  
Useful Plants ◽  
Reference Tracking ◽  
Output Performance ◽  
Input Control ◽  
Single Input ◽  
Noise Amplification

The availability of multiple inputs (plants) can improve output performance by conveniently allocating the control bandwidth among them. Beyond that, the intervention of only the useful plants at each frequency implies the minimum control action at each input. Secondly, in single input control, the addition of feedforward loops from measurable external inputs has been demonstrated to reduce the amount of feedback and, subsequently, palliate its sideband effects of noise amplification. Thus, one part of the action calculated by feedback is now provided by feedforward. This paper takes advantage of both facts for the problem of robust rejection of measurable disturbances by employing a set of control inputs; a previous work did the same for the case of robust reference tracking. Then, a control architecture is provided that includes feedforward elements from the measurable disturbance to each control input and feedback control elements that link the output error to each control input. A methodology is developed for the robust design of the named control elements that distribute the control bandwidth among the cheapest inputs and simultaneously assures the prescribed output performance to correct the disturbed output for a set of possible plant cases (model uncertainty). The minimum necessary feedback gains are used to fight plant uncertainties at the control bandwidth, while feedforward gains achieve the nominal output response. Quantitative feedback theory (QFT) principles are employed. An example illustrates the method and its benefits versus a control architecture with only feedback control elements, which have much more gain beyond the control bandwidth than when feedforward is employed.

Statistical Feedback Control Architecture for Layered Manufacturing

1999 ◽  
Vol 7 (4) ◽  
pp. 391-404 ◽  
Author(s):  
TONG FANG ◽  
MOHSEN A. JAFARI ◽  
AHMAD SAFARI ◽  
STEPHEN C. DANFORTH
Keyword(s):  
Feedback Control ◽  
Layered Manufacturing ◽  
Control Architecture

Extended state observer–based output feedback control for spacecraft pose tracking with control input saturation

2021 ◽  
pp. 095441002110177
Author(s):  
Kejie Gong ◽  
Ying Liao ◽  
Yafei Mei
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Finite Time ◽  
Output Feedback Control ◽  
State Observer ◽  
Extended State Observer ◽  
Control Input ◽  
Extended State ◽  
Pose Tracking ◽  
Control Scheme

This article proposed an extended state observer (ESO)–based output feedback control scheme for rigid spacecraft pose tracking without velocity feedback, which accounts for inertial uncertainties, external disturbances, and control input constraints. In this research, the 6-DOF tracking error dynamics is described by the exponential coordinates on SE(3). A novel continuous finite-time ESO is proposed to estimate the velocity information and the compound disturbance, and the estimations are utilized in the control law design. The ESO ensures a finite-time uniform ultimately bounded stability of the observation states, which is proved utilizing the homogeneity method. A non-singular finite-time terminal sliding mode controller based on super-twisting technology is proposed, which would drive spacecraft tracking the desired states. The other two observer-based controllers are also proposed for comparison. The superiorities of the proposed control scheme are demonstrated by theory analyses and numerical simulations.

scholarly journals Robust Synchronization of Delayed Chaotic FitzHugh-Nagumo Neurons under External Electrical Stimulation

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Muhammad Rehan ◽  
Keum-Shik Hong
Keyword(s):  
Electrical Stimulation ◽  
Nonlinear Control ◽  
Control Law ◽  
Input Control ◽  
Control Schemes ◽  
Multiple Input ◽  
Cognitive Diseases ◽  
Single Input ◽  
Error Dynamics ◽  
Nonlinear Control Law

Synchronization of chaotic neurons under external electrical stimulation (EES) is studied in order to understand information processing in the brain and to improve the methodologies employed in the treatment of cognitive diseases. This paper investigates the dynamics of uncertain coupled chaotic delayed FitzHugh-Nagumo (FHN) neurons under EES for incorporated parametric variations. A global nonlinear control law for synchronization of delayed neurons with known parameters is developed. Based on local and global Lipschitz conditions, knowledge of the bounds on the neuronal states, the Lyapunov-Krasovskii functional, and theL2gain reduction, a less conservative local robust nonlinear control law is formulated to address the problem of robust asymptotic synchronization of delayed FHN neurons under parametric uncertainties. The proposed local control law guarantees both robust stability and robust performance and provides theL2bound for uncertainty rejection in the synchronization error dynamics. Separate conditions for single-input and multiple-input control schemes for synchronization of a wide class of FHN systems are provided. The results of the proposed techniques are verified through numerical simulations.

Modeling and Control of a Rotary Crane

1985 ◽  
Vol 107 (3) ◽  
pp. 200-206 ◽  
Author(s):  
Y. Sakawa ◽  
A. Nakazumi
Keyword(s):  
Feedback Control ◽  
Equilibrium State ◽  
Open Loop ◽  
The State ◽  
Control Input ◽  
Loop Control ◽  
Modeling And Control ◽  
Control Scheme ◽  
Rotary Crane ◽  
And Control

In this paper we first derive a dynamical model for the control of a rotary crane, which makes three kinds of motion (rotation, load hoisting, and boom hoisting) simultaneously. The goal is to transfer a load to a desired place in such a way that at the end of transfer the swing of the load decays as quickly as possible. We first apply an open-loop control input to the system such that the state of the system can be transferred to a neighborhood of the equilibrium state. Then we apply a feedback control signal so that the state of the system approaches the equilibrium state as quickly as possible. The results of computer simulation prove that the open-loop plus feedback control scheme works well.

scholarly journals The Best Achievableℋ2Tracking Performances for SIMO Feedback Control Systems

2007 ◽  
Vol 2007 ◽  
pp. 1-12 ◽  
Author(s):  
Shinji Hara ◽  
Toni Bakhtiar ◽  
Masaaki Kanno
Keyword(s):  
Feedback Control ◽  
Control Systems ◽  
Linear Time ◽  
Tracking Error ◽  
Control Input ◽  
Discrete Time System ◽  
Time System ◽  
Linear Time Invariant ◽  
Augmentation Strategy ◽  
Feedback Control Systems

This paper is concerned with the inherentℋ2tracking performance limitation of single-input and multiple-output (SIMO) linear time-invariant (LTI) feedback control systems. The performance is measured by the tracking error between a step reference input and the plant output with additional penalty on control input. We employ the plant augmentation strategy, which enables us to derive analytical closed-form expressions of the best achievable performance not only for discrete-time system, but also for continuous-time system by exploiting the delta domain version of the expressions.

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