Improved Pole-placement Control with Feed-forward Dead Zone Compensation for Position Tracking of Electro-Pneumatic Actuator System Improved Pole-placement Control with Feed-forward Dead Zone Compensation for Position Tracking of Electro-Pneumatic Actuato

2021 ◽  
Vol 20 (2) ◽  
pp. 25-32
Author(s):  
Noorhazirah Sunar ◽  
Mohd Fua’ad Rahmat ◽  
Ahmad ‘Athif Mohd Fauzi ◽  
Zool Hilmi Ismail ◽  
Siti Marhanis Osman ◽  
...  
Keyword(s):  
Dead Zone ◽  
Pneumatic Actuator ◽  
Pole Placement ◽  
Position Tracking ◽  
Zone Model ◽  
Feed Forward ◽  
The Dead ◽  
Chattering Effect ◽  
Pole Placement Controller ◽  
Pole Placement Control

Dead-zone in the valve degraded the performances of the Electro-Pneumatic Actuator (EPA) system.  It makes the system difficult to control, become unstable and leads to chattering effect nearest desired position.  In order to cater this issue, the EPA system transfer function and the dead-zone model is identified by MATLAB SI toolbox and the Particle Swarm Optimization (PSO) algorithm respectively.  Then a parametric control is designed based on pole-placement approach and combine with feed-forward inverse dead-zone compensation.  To reduce chattering effect, a smooth parameter is added to the controller output.  The advantages of using these techniques are the chattering effect and the dead-zone of the EPA system is reduced.  Moreover, the feed-forward system improves the transient performance.  The results are compared with the pole-placement control (1) without compensator and (2) with conventional dead-zone compensator.  Based on the experimental results, the proposed controller reduced the chattering effect due to the controller output of conventional dead-zone compensation, 90% of the pole-placement controller steady-state error and 30% and 40% of the pole-placement controller with conventional dead-zone compensation settling time and rise time.

Experimental and numerical validation of the dead-zone model for longitudinal dispersion in rivers

1998 ◽  
Vol 36 (2) ◽  
pp. 269-280 ◽  
Author(s):  
Wlodzimierz Czernuszenko ◽  
Pawel-M. RowiŃSki ◽  
Alexander Sukhodolov
Keyword(s):  
Dead Zone ◽  
Longitudinal Dispersion ◽  
Zone Model ◽  
Numerical Validation ◽  
The Dead

Model Based Control of a Smart Vibrating Cantilever Beam

2001 ◽  
Author(s):  
Robin G. Scott ◽  
Michael D. Brown ◽  
Warren J. Manning ◽  
Martin C. Levesley
Keyword(s):  
Cantilever Beam ◽  
Limit Cycles ◽  
Minimum Variance ◽  
Smart Structure ◽  
Pole Placement ◽  
Vibration Effect ◽  
Data Control ◽  
Pole Placement Controller ◽  
The Cost ◽  
Pole Placement Control

Abstract This paper compares Generalised Minimum Variance and Pole-placement techniques for the control of a lightly damped cantilever beam smart structure. Saturation of the control signal can lead to limit cycles in Pole-placement control. Saturation compensation can remove these limit cycles, allowing disturbances of the beam to be rejected, but introduces a low amplitude, higher frequency vibration effect. Control sensitivity functions used to investigate these limit cycles show that certain Pole-placement controllers are sensitive to frequencies in the 50Hz range. The sensitivity of a Generalised minimum variance (GMV) controller is shown to be less than that of the Pole-placement controller. This GMV controller is applied to the vibration control of the smart beam. The controller weightings of the cost function limit excessive control signals. Previous work allows a plant model to be generated that produces results that closely match experimental data. Control results shows that the GMV technique is highly effective in reducing both the decay time and amplitude of vibration for free and forced vibrations respectively.

Adaptive interval type-2 fuzzy dynamic surface control for uncertain nonlinear systems with unknown asymmetric dead-zone input

2018 ◽  
Vol 41 (2) ◽  
pp. 516-531 ◽  
Author(s):  
Maryam Shahriari-kahkeshi ◽  
Sanaz Rahmani
Keyword(s):  
Fuzzy System ◽  
Dead Zone ◽  
Dynamic Surface Control ◽  
Zone Model ◽  
Uncertain Nonlinear Systems ◽  
Dynamic Surface ◽  
Surface Control ◽  
The Dead ◽  
Interval Type

In this study, an adaptive dynamic surface control (DSC) scheme based on the interval type-2 fuzzy systems is proposed for uncertain nonlinear systems with unknown asymmetric dead-zone input and unknown control gains. The dead-zone nonlinearity is represented as a time-varying system with a bounded disturbance. The proposed approach invokes the interval type-2 fuzzy system to approximate the unknown nonlinear dynamics that appears in the virtual and actual control inputs. Also, it proposes adaptive terms to compensate the effect of the disturbance-like term in the dead-zone constraint. Then, the DSC scheme is designed based on the interval type-2 fuzzy system and the dead-zone model. Adaptive laws are derived to tune the consequent parameters of the interval type-2 fuzzy system and the dead-zone model. Stability analysis of the proposed scheme shows that all the signals of the closed-loop system are uniformly ultimately bounded and the tacking error can be made arbitrary small by proper selection of the design parameters. The proposed scheme avoids the “explosion of complexity” and “singularity” problems, simultaneously. Furthermore, it can compensate the effect of the dead-zone constraint without any need to its parameters. The simulation and comparison results are presented to demonstrate the effectiveness of the proposed control scheme.

Properties of the dead-zone model of longitudinal dispersion in rivers

1997 ◽  
Vol 35 (4) ◽  
pp. 491-504 ◽  
Author(s):  
W. Czernuszenko ◽  
P.M. Rowinski
Keyword(s):  
Dead Zone ◽  
Longitudinal Dispersion ◽  
Zone Model ◽  
The Dead

scholarly journals SHEAR-DRIVEN FLUSHING OF MICRO-TIDAL MARINAS

2012 ◽  
Vol 1 (33) ◽  
pp. 59 ◽  
Author(s):  
Enda Murphy ◽  
Mathieu Deiber ◽  
Sylvain Perrin
Keyword(s):  
Water Exchange ◽  
Dead Zone ◽  
Mixing Layer ◽  
Practical Implementation ◽  
Zone Model ◽  
Hydrodynamic Models ◽  
Water Renewal ◽  
Coastal Basins ◽  
The Dead ◽  
Peripheral Areas

Flushing or residence times are typically used as a first step in assessing water quality in marinas, harbours and coastal basins. Recent publications have offered guidance in relation to optimal marina basin and entrance geometries to help achieve rapid renewal. However, these guidelines have been developed for the particular case where water exchange is strongly tide-driven and are not widely applicable, particularly in micro-tidal regions. Where water renewal rates are dominated by shear-driven circulation and lateral transfer of momentum at the interface between the marina and the adjacent water body (i.e. a mixing layer), there is a strong analogy to groyne fields and other cases involving flows containing quasi-stagnant peripheral areas (dead zones). A series of numerical hydrodynamic models, developed in the TELEMAC system, were used to investigate the potential for the dead zone model of water exchange to provide a better means to guide optimization of basin and entrance geometry under such conditions. Real-world marina case studies were used to identify any constraints affecting the practical implementation of such an approach. The numerical model results demonstrate particular conditions under which the dead zone model of water exchange can be used effectively to optimize marina basin and entrance geometry.

Adaptive Pole Placement Control Algorithm for Nonlinear Systems

1997 ◽  
Vol 05 (02) ◽  
pp. 139-146 ◽  
Author(s):  
Jin Wang ◽  
Wenzhong Gao
Keyword(s):  
Neural Network ◽  
Control Algorithm ◽  
Learning Algorithm ◽  
Recursive Least Squares ◽  
Pole Placement ◽  
Rls Algorithm ◽  
Pole Placement Controller ◽  
Nonlinear Plants ◽  
Adaptive Control Algorithm ◽  
Pole Placement Control

A new adaptive control algorithm for unknown nonlinear plants is presented. The paper first describes a modified neural network(MNN) as well as the associated learning algorithm. The learning algorithm converges considerably faster because of the introduction of recursive least squares(RLS) algorithm. And then designs adaptive pole placement controller based on the modified neural network. Simulation results show that the proposed control algorithm can effectively control nonlinear plants.

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