scholarly journals Nonlinear MIMO Control of a Continuous Cooling Crystallizer

2012 ◽  
Vol 2012 ◽  
pp. 1-11
Author(s):  
Pedro Alberto Quintana-Hernández ◽  
Raúl Ocampo-Pérez ◽  
Salvador Tututi-Avila ◽  
Salvador Hernández-Castro
Keyword(s):  
Pid Controller ◽  
Closed Loop ◽  
Crystal Size ◽  
Operating Conditions ◽  
Pid Controllers ◽  
Absolute Value ◽  
The Third ◽  
Operation Conditions ◽  
Metastable Zone ◽  
Third Moment

In this work, a feedback control algorithm was developed based on geometric control theory. A nonisothermal seeded continuous crystallizer model was used to test the algorithm. The control objectives were the stabilization of the third moment of the crystal size distribution (μ3) and the crystallizer temperature (T); the manipulated variables were the stirring rate and the coolant flow rate. The nonlinear control (NLC) was tested at operating conditions established within the metastable zone. Step changes of magnitudes ±0.0015 and ±0.5°C were introduced into the set point values of the third moment and crystallizer temperature, respectively. In addition, a step change of ±1°C was introduced as a disturbance in the feeding temperature. Closed-loop stability was analyzed by calculating the eigenvalues of the internal dynamics. The system presented a stable dynamic behavior when the operation conditions maintain the crystallizer concentration within the metastable zone. Closed-loop simulations with the NLC were compared with simulations that used a classic PID controller. The PID controllers were tuned by minimizing the integral of the absolute value of the error (IAE) criterion. The results showed that the NLC provided a suitable option for continuous crystallization control. For all analyzed cases, the IAEs obtained with NLC were smaller than those obtained with the PID controller.

Optimal tuning of PID controller in time delay system: a review on various optimization techniques

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Thomas George ◽  
V. Ganesan
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Pid Controller ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Delay Systems ◽  
Pid Controllers ◽  
Time Delay Systems ◽  
Process Industries ◽  
First Order

AbstractThe processes which contain at least one pole at the origin are known as integrating systems. The process output varies continuously with time at certain speed when they are disturbed from the equilibrium operating point by any environment disturbance/change in input conditions and thus they are considered as non-self-regulating. In most occasions this phenomenon is very disadvantageous and dangerous. Therefore it is always a challenging task to efficient control such kind of processes. Depending upon the number of poles present at the origin and also on the location of other poles in transfer function different types of integrating systems exist. Stable first order plus time delay systems with an integrator (FOPTDI), unstable first order plus time delay systems with an integrator (UFOPTDI), pure integrating plus time delay (PIPTD) systems and double integrating plus time delay (DIPTD) systems are the classifications of integrating systems. By using a well-controlled positioning stage the advances in micro and nano metrology are inevitable in order satisfy the need to maintain the product quality of miniaturized components. As proportional-integral-derivative (PID) controllers are very simple to tune, easy to understand and robust in control they are widely implemented in many of the chemical process industries. In industries this PID control is the most common control algorithm used and also this has been universally accepted in industrial control. In a wide range of operating conditions the popularity of PID controllers can be attributed partly to their robust performance and partly to their functional simplicity which allows engineers to operate them in a simple, straight forward manner. One of the accepted control algorithms by the process industries is the PID control. However, in order to accomplish high precision positioning performance and to build a robust controller tuning of the key parameters in a PID controller is most inevitable. Therefore, for PID controllers many tuning methods are proposed. the main factors that lead to lifetime reduction in gain loss of PID parameters are described in This paper and also the main methods used for gain tuning based on optimization approach analysis is reviewed. The advantages and disadvantages of each one are outlined and some future directions for research are analyzed.

Online Adaptive Control Tuning in a Gas Turbine Hybrid System

2020 ◽  
Author(s):  
Harry Bonilla-Alvarado ◽  
Bernardo Restrepo ◽  
Paolo Pezzini ◽  
Lawrence Shadle ◽  
David Tucker ◽  
...  
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Mass Flow ◽  
Pid Controller ◽  
Standard Procedure ◽  
Full Range ◽  
Test Procedure ◽  
Operating Conditions ◽  
Control Technique ◽  
Pid Controllers

Abstract Proportional integral and derivative (PID) controllers are the most popular technique used in the power plant industry for process automation. However, the performance of these controllers may be affected due to variations in the power plant operating conditions, such as between startup, shutdown, and baseload/part-load operation. To maintain the desired performance over the full range of operations, PID controllers are always retuned in most power plants. During this retuning process, the operator takes control of the manipulated variable to perform a standard procedure based on a bump test. This procedure is generally performed to characterize the relationship between the manipulated variable and the process variable at each operating condition. After the bump test, the operator generally applies basic guidelines to assign new parameters to the PID controller. In this paper, the Model Reference Adaptive Controller (MRAC) control technique was implemented to update the PID controller parameters online without performing the bump test procedure. This approach allows updating the controller response on-the-fly while the power plant is running and without using the standard procedure based on a bump test. The MRAC was developed and demonstrated in the gas turbine hybrid cycle at the National Energy Technology Laboratory (NETL) to retune a critically damped mass flow PID controller into an over-damped response. Results showed stable performance during mass flow setpoint steps and also a stable update of the controller parameters.

A Study of Turbine Engine PID Control Method Based on Closed-Loop Gain Shaping Algorithm

2012 ◽  
Vol 468-471 ◽  
pp. 143-146
Author(s):  
Jie Tang Zhu ◽  
Shi Ying Zhang ◽  
Jiao Chen ◽  
Lei Luo ◽  
Peng Gao
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Closed Loop ◽  
Control Method ◽  
Narrow Range ◽  
Pid Controllers ◽  
Loop Gain ◽  
Turbine Engine ◽  
Engine Control System ◽  
Series Type

This paper aims at the application of closed-loop gain shaping algorithm in turbine engine PID control. It introduces calculation examples, showing how to build a PID controller through parameters with physical significances; it also establishes mathematic models of turbine engine and fuel supply system, in order to test the performances of the PID controller, based on the comparison between PID controllers of series type and closed-loop gain shaping. Simultaneously, simulations are conducted using Matlab. The Simulations indicate no overshoot, proper control time as well as a narrow range of amplitude of oscillation. Therefore, the study succeeds in proving that the closed-loop gain shaping PID controller has excellent performance and good robustness, which is particularly useful for turbine engine control system.

scholarly journals Efficient control of a nonlinear double-pendulum overhead crane with sensorless payload motion using an improved PSO-tuned PID controller

2018 ◽  
Vol 25 (4) ◽  
pp. 907-921 ◽  
Author(s):  
H. I. Jaafar ◽  
Z. Mohamed ◽  
N. A. Mohd Subha ◽  
A. R. Husain ◽  
F. S. Ismail ◽  
...  
Keyword(s):  
Pid Controller ◽  
Pso Algorithm ◽  
Operating Conditions ◽  
Pid Controllers ◽  
Feedback Signal ◽  
Double Pendulum ◽  
Horizontal Distance ◽  
Overhead Crane ◽  
Efficient Performance ◽  
Highly Nonlinear

This paper proposes an efficient proportional–integral–derivative (PID) control of a highly nonlinear double-pendulum overhead crane without the need for a payload motion feedback signal. Optimal parameters of the PID controllers are tuned by using an improved particle swarm optimization (PSO) algorithm based on vertical distance oscillations and potential energy of the crane. In contrast to a commonly used PSO algorithm based on a horizontal distance, the approach resulted in an efficient performance with a less complex controller. To test the effectiveness of the approach, extensive simulations are carried out under various crane operating conditions involving different payload masses and cable lengths. Simulation results show that the proposed controller is superior with a better trolley position response, and lower hook and payload oscillations as compared to the previously developed PSO-tuned PID controller. In addition, the controller provides a satisfactory performance without the need for a payload motion feedback signal.

scholarly journals PID Controller optimization using Metahuristic Controller with Different Nonlinearities

2021 ◽  
Vol 12 (2) ◽  
pp. 764-771
Author(s):  
G. Sundari, Et. al.
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Closed Loop ◽  
Error Function ◽  
Second Order ◽  
Settling Time ◽  
Order System ◽  
Pid Controllers ◽  
Dynamic Performances ◽  
Conventional Methods

This paper mainly explains the application of Metaherustic controller for tuning the parameter of PID controller. The minimization of error function has been done by improving the static and dynamic performances of the system like steady state error, Peak Overshoot, and Settling Time. This could be possible by means of applying metaherustic controller like GA in tuning the PID controllers under different Nonlinearities. The main intention of this paper is to support the specifications of PID controller at various Nonlinearities such as sinusoidal and saw tooth noise. The projected scheme derives the wonderful closed-loop response of second order system and then, it provides the effectiveness of the proposed method compared to the conventional methods.

scholarly journals How A PID Controlling A Nonlinear Plant

2020 ◽  
Vol 188 ◽  
pp. 00025
Author(s):  
Timbang Pangaribuan ◽  
Sahat Parulian Siahaan ◽  
Shyh Leh Chen
Keyword(s):  
Pid Controller ◽  
Closed Loop ◽  
Inverted Pendulum ◽  
Feedback Controller ◽  
Pid Controllers ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Best Parameter ◽  
And Performance ◽  
Nonlinear Plant

This paper investigates the weakness of feedback controller to find the best parameter of PID controller of a nonlinear inverted pendulum system (NL-IPS). Stability and performance analysis of a NL-IPS are carried out with combination of feedback and PID controllers. It is found that the NL-IPS which was stabilized by feedback controller provides some weakness. By addition of PID controller on closed loop NL-IPS will provide better tracking and response on zero steady state error.

scholarly journals Comparative Study of PID Based VMC and Fuzzy Logic Controllers for Flyback Converter

2011 ◽  
pp. 134-141
Author(s):  
P. Rajesh Kumar ◽  
S. L. V. Sravan Kumar
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Pid Controllers ◽  
Trial And Error ◽  
Flyback Converter ◽  
Wide Range ◽  
Performance Variations

In this paper performance of flyback converter by using PID controller and Fuzzy controller are studied, compared and analyzed. The above study is done for 200W, 230V A.C input 48V DC output. Design of fuzzy controller is based on the heuristic knowledge of converter behaviour, and tuning of fuzzy inference requires some expertise to minimize unproductive trial and error. The design of PID control is based on the frequency response of the converter. For the DC-DC converters, the performance of the fuzzy controller was superior in some respects to that of the PID controller. The fuzzy controller is easily to develop, they cover a wide range of operating conditions, and they are more readily customizable in natural language terms. Simulation is done in Matlab environment to show the performance variations of above mentioned converters using both Fuzzy & PID controllers.

scholarly journals Genetic Algorithm Optimisation of PID Controllers for a Multivariable Process

2017 ◽  
Vol 5 (1) ◽  
pp. 77 ◽  
Author(s):  
Wael Alharbi ◽  
Barry Gomm
Keyword(s):  
Genetic Algorithms ◽  
Objective Function ◽  
Time Domain ◽  
Pid Controller ◽  
Closed Loop ◽  
Pid Controllers ◽  
Controller Tuning ◽  
Single Input Single Output ◽  
Performance Specifications ◽  
Tuning Methods

<p>This project is about the design of PID controllers and the improvement of outputs in multivariable processes. The optimisation of PID controller for the Shell oil process is presented in this paper, using Genetic Algorithms (GAs). Genetic Algorithms (GAs) are used to automatically tune PID controllers according to given specifications. They use an objective function, which is specially formulated and measures the performance of controller in terms of time-domain bounds on the responses of closed-loop process.</p><p>A specific objective function is suggested that allows the designer for a single-input, single-output (SISO) process to explicitly specify the process performance specifications associated with the given problem in terms of time-domain bounds, then experimentally evaluate the closed-loop responses. This is investigated using a simple two-term parametric PID controller tuning problem. The results are then analysed and compared with those obtained using a number of popular conventional controller tuning methods. The intention is to demonstrate that the proposed objective function is inherently capable of accurately quantifying complex performance specifications in the time domain. This is something that cannot normally be employed in conventional controller design or tuning methods.</p><p>Finally, the recommended objective function will be used to examine the control problems of Multi-Input-Multi-Output (MIMO) processes, and the results will be presented in order to determine the efficiency of the suggested control system.</p>

Monte Carlo Algorithms for Moments of Transition Arrays

1988 ◽  
Vol 102 ◽  
pp. 79-81
Author(s):  
A. Goldberg ◽  
S.D. Bloom
Keyword(s):  
Monte Carlo ◽  
State Vector ◽  
Basis Vector ◽  
Collective State ◽  
Dispersion Characteristics ◽  
Dipole Strength ◽  
The Third ◽  
Monte Carlo Algorithms ◽  
Third Moment ◽  
Very High

AbstractClosed expressions for the first, second, and (in some cases) the third moment of atomic transition arrays now exist. Recently a method has been developed for getting to very high moments (up to the 12th and beyond) in cases where a “collective” state-vector (i.e. a state-vector containing the entire electric dipole strength) can be created from each eigenstate in the parent configuration. Both of these approaches give exact results. Herein we describe astatistical(or Monte Carlo) approach which requires onlyonerepresentative state-vector |RV&gt; for the entire parent manifold to get estimates of transition moments of high order. The representation is achieved through the random amplitudes associated with each basis vector making up |RV&gt;. This also gives rise to the dispersion characterizing the method, which has been applied to a system (in the M shell) with≈250,000 lines where we have calculated up to the 5th moment. It turns out that the dispersion in the moments decreases with the size of the manifold, making its application to very big systems statistically advantageous. A discussion of the method and these dispersion characteristics will be presented.

Grasshopper Algorithm Optimized Fractional Order Fuzzy PID Frequency Controller for Hybrid Power Systems

2019 ◽  
Vol 12 (6) ◽  
pp. 519-531
Author(s):  
Deepak Kumar Lal ◽  
Ajit Kumar Barisal
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fractional Order ◽  
Pid Controller ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Hybrid Power ◽  
Increasing Demand

Background: Due to the increasing demand for the electrical power and limitations of conventional energy to produce electricity. Methods: Now the Microgrid (MG) system based on alternative energy sources are used to provide electrical energy to fulfill the increasing demand. The power system frequency deviates from its nominal value when the generation differs the load demand. The paper presents, Load Frequency Control (LFC) of a hybrid power structure consisting of a reheat turbine thermal unit, hydropower generation unit and Distributed Generation (DG) resources. Results: The execution of the proposed fractional order Fuzzy proportional-integral-derivative (FO Fuzzy PID) controller is explored by comparing the results with different types of controllers such as PID, fractional order PID (FOPID) and Fuzzy PID controllers. The controller parameters are optimized with a novel application of Grasshopper Optimization Algorithm (GOA). The robustness of the proposed FO Fuzzy PID controller towards different loading, Step Load Perturbations (SLP) and random step change of wind power is tested. Further, the study is extended to an AC microgrid integrated three region thermal power systems. Conclusion: The performed time domain simulations results demonstrate the effectiveness of the proposed FO Fuzzy PID controller and show that it has better performance than that of PID, FOPID and Fuzzy PID controllers. The suggested approach is reached out to the more practical multi-region power system. Thus, the worthiness and adequacy of the proposed technique are verified effectively.

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