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Malek Ghanavati,Karim Salahshoor,Mohammad Reza Jahed Motlagh,Amin Ramazani,Ali Moarefianpour 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.2
Nowadays, there is a great interest in using active control methods to increase the compressor working range. The advantage of this controlling method is that the performance point can be located in the vicinity of maximum pressure and efficiency. However, most of the existing controllers require an awareness of compressor characteristic, disturbance upper bound, throttle gain, and throttle valve feature; this is why they are limited in engineering applications. In order to overcome the weakness of the existing controllers, this research employs a novel combined controlling method based on robust adaptive control, which is designed using backstepping technique because the compressor behavior is nonlinear. The increased efficiency and improved operational area for the compressor are provided by this controller without requiring any knowledge or information regarding the compressor characteristic, disturbance upper bound, throttle gain, and throttle valve feature. The adaptive controller has been used to compensate for uncertainties of the compressor characteristic and throttle valve as well as the un-modeled dynamics. Also, the controller robustness is a barrier against the time-varying disturbances in flow and pressure applied to the system. Finally, simulation results showed that the designed controller, in addition to assure the system stability, developed the compressor working range, and the convergence of system states was achieved after applying disturbance in flow and pressure.
Ebrahim Moradi,Karim Salahshoor,Mehdi Rezagholizadeh 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
This paper presents a new methodology to design an instrumentation sensor network for nonlinear processes. The goal is to design a high performance and low price sensor network. The proposed approach utilizes constrained state estimation based on the unscented Kalman filter (UKF) approach to cater for some known signal information which is often either ignored or dealt with heuristically. The approach employs a clipping methodology to implement the constraints, leading to an optimal sensor network with less number of sensors. A benchmark continuous stirred tank reactor (CSTR) is used to evaluate the performance of the new method. The obtained simulation results validate the effectiveness of the new method.
A Novel Real-time Fuzzy Adaptive Auto-Tuning Scheme for Cascade PID Controllers
Ali Fadaei,Karim Salahshoor 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.5
This paper presents a novel fuzzy auto-tuning methodology to continuously adapt PID control actions without interrupting the normal process operation. New auto-tuning rules are introduced to schedule a gradual and guided activation of each individual P, I and D control mode in three adjustable functional control zones. An auto-scaling procedure has been incorporated to generalize the auto-tuning scheme to efficiently respond to any set-point change outside a pre-defined operating span. In contrast to existing auto-tuning algorithms, the proposed scheme is not an on-demand auto-tuning methodology and hence does not require alertness of an experienced engineer to initiate and supervise its initial operation in a separate commissioning identification pre-test. This interesting feature provides a new perspective on PID auto-tuning approaches. Performance of the proposed auto-tuning scheme is practically evaluated in a real pilot plant within a networked control system (NCS) configuration, realized by industrial Ethernet and Foundation Fieldbus technologies. An extensive series of test scenarios has been conducted to explore efficiency of the proposed auto-tuning methodology to cope with fixed and varying operating set-points under uncertain and variable network transmission time delays and external disturbance.
Reza Sobhani Ahmadgurabi,Mohammad Ali Nekoui,Karim Salahshoor 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
Predictive controller based on model has been known as a reliable and robust controller in the last 20 years. This paper presents a new idea of design and implementing an adaptive model predictive controller on an industrial "dynamic" and "nonlinear" plant in an integrated software environment using Hysys and Matlab packages. The model predictive controller formation is based on an adaptive state-space prediction model of the system response to obtain the control action by minimizing an objective function. The designed MPC controller is utilized to regulate a gaseous industrial plant, simulated in Hysys. The objective of controlling the plant is to compensate for the pressure variations in topside output of the vessel in on-line form. In this paper, the opening value percentage (OP) of a valve in the output is randomly excited in a given interval to identify the output pressure in the plant, called as Process Variable (PV). The predicted and desired outputs are then employed in the designed model predictive controller to determine the control actions in the prediction horizon. The simulation results obtained in the developed integrated Hysys-Matlab environment, demonstrate the capability of the proposed approach to efficiently monitor and control an industrial gaseous plant in a real and practical manner.