Comparison of the self-tuning generalized predictive controller and pole placement controller

2002 ◽  
Author(s):  
I. Santro ◽  
N. Peric ◽  
I. Petrovic
Keyword(s):  
The Self ◽  
Pole Placement ◽  
Self Tuning ◽  
Predictive Controller ◽  
Pole Placement Controller

A dual-rate self-tuning pole-placement controller

1993 ◽  
Vol 40 (1) ◽  
pp. 116-129 ◽  
Author(s):  
C.C. Hang ◽  
Y.S. Cai ◽  
K.W. Lim
Keyword(s):  
Pole Placement ◽  
Self Tuning ◽  
Pole Placement Controller

Soma Evolutionary Algorithm Used for Chromium Sludge Regeneration Process

2013 ◽  
Vol 791-793 ◽  
pp. 1333-1336
Author(s):  
David Novosad ◽  
Lubomír Macků
Keyword(s):  
Flow Rate ◽  
Filter Cake ◽  
Exothermic Reaction ◽  
Cooling Water ◽  
The Self ◽  
Pole Placement ◽  
Process Time ◽  
Cooling Water Temperature ◽  
Whole Process ◽  
Pole Placement Controller

Two different approaches are used to control a semi-batch nonlinear reactor dealing with the significant exothermic reaction. This paper compares evolutionary approach represented by the Self - Organizing Migrating Algorithm (SOMA) with PID pole placement controller (PIDPP). The aim of controlled process is to regenerate the largest amount of chromium filter cake (chromium sludge) in the shortest possible time. For safety reasons the temperature inside the reactor should not exceed 100 °C. In this study the reactor is controlled by two manipulating inputs: filter cake feeding flow rate and cooling water temperature. The speed of the whole process depends on the filter cake feeding flow rate in case of a large amount filter cake addition a sharp temperature rise follows. The controller must be able to find optimal strategy between the filter cake dosing and the cooling temperature to reach the shortest possible process time. The SOMA optimization algorithm was created in Mathematica, PIDPP in Matlab/Simulink.

scholarly journals Improved Self-Sensing Speed Control of IPMSM Drive Based on Cascaded Nonlinear Control

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2205
Author(s):  
Muhammad Usama ◽  
Jaehong Kim
Keyword(s):  
Fuzzy Logic Controller ◽  
Control Design ◽  
Speed Control ◽  
Current Control ◽  
The Self ◽  
Pole Placement ◽  
Motor Drive ◽  
Control Performance ◽  
Control Loop ◽  
Maximum Torque

This paper presents a nonlinear cascaded control design that has been developed to (1) improve the self-sensing speed control performance of an interior permanent magnet synchronous motor (IPMSM) drive by reducing its speed and torque ripples and its phase current harmonic distortion and (2) attain the maximum torque while utilizing the minimum drive current. The nonlinear cascaded control system consists of two nonlinear controls for the speed and current control loop. A fuzzy logic controller (FLC) is employed for the outer speed control loop to regulate the rotor shaft speed. Model predictive current control (MPCC) is utilized for the inner current control loop to regulate the drive phase currents. The nonlinear equation for the dq reference current is derived to implement the maximum torque per armature (MTPA) control to achieve the maximum torque while using the minimum current values. The model reference adaptive system (MRAS) was employed for the speed self-sensing mechanism. The self-sensing speed control performance of the IPMSM motor drive was compared with that of the traditional cascaded control schemes. The stability of the sensorless mechanism was studied using the pole placement method. The proposed nonlinear cascaded control was verified based on the simulation results. The robustness of the control design was ensured under various loads and in a wide speed range. The dynamic performance of the motor drive is improved while circumventing the need to tune the proportional-integral (PI) controller. The self-sensing speed control performance of the IPMSM drive was enhanced significantly by the designed cascaded control model.

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.

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