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.

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.

scholarly journals Takagi-Sugeno Fuzzy Modeling and PSO-Based Robust LQR Anti-Swing Control for Overhead Crane

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Xuejuan Shao ◽  
Jinggang Zhang ◽  
Xueliang Zhang
Keyword(s):  
Linear Quadratic Regulator ◽  
Pso Algorithm ◽  
Fuzzy Modeling ◽  
Linear Matrix ◽  
Feedback Gain ◽  
Overhead Crane ◽  
Linear Quadratic ◽  
Highly Nonlinear ◽  
The Stability ◽  
Takagi Sugeno

The dynamic model of overhead crane is highly nonlinear and uncertain. In this paper, Takagi-Sugeno (T-S) fuzzy modeling and PSO-based robust linear quadratic regulator (LQR) are proposed for anti-swing and positioning control of the system. First, on the basis of sector nonlinear theory, the two T-S fuzzy models are established by using the virtual control variables and approximate method. Then, considering the uncertainty of the model, robust LQR controllers with parallel distributed compensation (PDC) structure are designed. The feedback gain matrices are obtained by transforming the stability and robustness of the system into linear matrix inequalities (LMIs) problem. In addition, particle swarm optimization (PSO) algorithm is used to overcome the blindness of LQR weight matrix selection in the design process. The proposed control methods are simple, feasible, and robust. Finally, the numeral simulations are carried out to prove the effectiveness of the methods.

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.

scholarly journals Speed control of switched reluctance motor using genetic algorithm and ant colony based on optimizing PID controller

2018 ◽  
Vol 16 ◽  
pp. 01001 ◽  
Author(s):  
Hassan El-Sayed Ahmed Ibrahim ◽  
Mohamed Said Sayed Ahmed ◽  
Khaled Mohamed Awad
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Switched Reluctance Motor ◽  
Operating Conditions ◽  
Ant Colony ◽  
Proportional Integral Derivative ◽  
Switched Reluctance ◽  
Proportional Integral ◽  
Highly Nonlinear ◽  
Reluctance Motor

Proportional-Integral-Derivative control is the most used kind of control which provides the simplest and most effective solution to different kinds of control engineering applications. But until now PID controller is poorly tuned in real life and online applications. While most of PID tuning is done manually. Switched reluctance motor (SRM) has highly nonlinear characteristics since the developed/produced torque of the motor has a nonlinear function on both phase current and rotor position. These nonlinearities of the SRM drives make the conventional PID (proportional + integral + Derivative) controller a poor choice for application where high dynamic performance is desired under all motor operating conditions. research paper comes up with two artificial and hybrid techniques involving Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Those techniques where used to tune the PID parameters for the switched reluctance motor (SRM) and its performance were compared with the conventional method of “Ziegler Nichols. The results obtained reflects that, the use of those algorithms based controller improves the performance of the whole process in terms of a fast set point tracking and regulatory changes and also provides an optimum stability for the system itself with a minimum overshoot on the output signal.

DESIGN OF ADAPTIVE FUZZY FRACTIONAL ORDER PID CONTROLLER FOR AUTONOMOUS UNDERWATER VEHICLE (AUV) IN HEADING AND DEPTH ATTITUDES

2021 ◽  
Vol 158 (A1) ◽  
Author(s):  
M H Khodayari ◽  
S Balochian
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Autonomous Underwater Vehicle ◽  
Path Following ◽  
Transient State ◽  
Pid Controllers ◽  
Adaptive Fuzzy ◽  
Highly Nonlinear ◽  
Self Tuning ◽  
Fractional Order Pid

This paper deals with the design of new self-tuning Fuzzy Fractional Order PID (AFFOPID) controller based on nonlinear MIMO structure for an AUV in order to enhance the performance in both transient state and steady state of traditional PID controller. It is particularly advantageous when the effects of highly nonlinear processes, like high maneuver, parameters variation, have to be controlled in presence of sensor noises and wave disturbances. Aspects of AUV controlling are crucial because of Complexity and highly coupled dynamics, time variety and difficulty in hydrodynamic modeling. In this try, the comprehensive nonlinear model of AUV is derived through kinematics and dynamic equations. The scaling factor of the proposed AFFOPID Controller is adjusted online at different underwater conditions. Combination of adaptive fuzzy methods and PID controllers can enhance solving the uncertainty challenge in the PID parameters and AUV parameter uncertainty. The simulation results show that developed control system is stable, competent and efficient enough to control the AUV in path following with stabilized and controlled speed. Obtained results demonstrate that the proposed controller has good performance and significant robust stability in comparison to traditional tuned PID controllers.

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.

scholarly journals Design of a discrete PID controller based on identification data for a simscape buck boost converter model

2019 ◽  
Vol 10 (4) ◽  
pp. 1797
Author(s):  
Mohammed Almaged ◽  
Salam Ibrahim Khather ◽  
Abdulla I. Abdulla
Keyword(s):  
Pid Controller ◽  
Boost Converter ◽  
Pid Controllers ◽  
Power Electronic ◽  
New Approach ◽  
Highly Nonlinear ◽  
Digital Pid ◽  
Constant Output ◽  
Complex Mathematical Model ◽  
Load Perturbations

<span>This work shows the design and tuning procedure of a discrete PID controller for regulating buck boost converter circuits. The buck boost converter model is implemented using Simscape Matlab library without having to derive a complex mathematical model. A new tuning process of digital PID controllers based on identification data has been proposed. Simulation results are introduced to examine the potentials of the designed controller in power electronic applications and validate the capability and stability of the controller under supply and load perturbations. Despite controller linearity, the new approach has proved to be successful even with highly nonlinear systems. The proposed controller has succeeded in rejecting all the disturbances effectively and maintaining a constant output voltage from the regulator.</span>

scholarly journals Analysis of Proportional Integral Derivative Controller Parameters for CSTR

2021 ◽  
Vol 16 ◽  
pp. 387-395
Author(s):  
T. Sudha
Keyword(s):  
Pid Controller ◽  
Chemical Engineering ◽  
Vital Role ◽  
Pid Controllers ◽  
Nonlinear Behaviour ◽  
Continuous Stirred Tank Reactor ◽  
Proportional Integral Derivative ◽  
Highly Nonlinear ◽  
Continuous Stirred Tank ◽  
Wide Operating

Continuous Stirred Tank Reactor (CSTR) plays a vital role and presents a various scope of researchers in the field of control and chemical engineering which exhibits of highly nonlinear behaviour and has wide operating ranges. Different control methods have been implemented on CSTR to control these parameters. Tragically, in the realcase, the behaviour of the CSTR is very different from that expected ideal CSTR which leads to the outcomes of the wrong product. However, it is a challenging task for every engineer to control the CSTR.PID controller has been proposed for adjust enhanced PID parameters in a CSTR operation utilizing a weighted mix of target capacities. Streamlining of PID controller parameters is the key objective of concoction and biochemical businesses. PID controllers have restricted the working scope of procedures with effective nonlinearity. This work considers some issues in CSTR and presents the efforts of existing researchers and it comes into view as an essential new method to adjust the control parameters. This work plans to investigate the various techniques in CSTR along with its solutions and these schemes have been surveyed in this work. This survey presents the comparison of various methods for optimizing parameters in CSTR are employed and compared with certain parameters.

Optimal Control of DC Motors Using PSO Algorithm for Tuning PID Controller

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Arnisa Myrtellari ◽  
Petrika Marango ◽  
Margarita Gjonaj
Keyword(s):  
Pid Controller ◽  
High Performance ◽  
Industrial Process ◽  
Speed Control ◽  
Pso Algorithm ◽  
Dc Motor ◽  
Step Response ◽  
Pid Controllers ◽  
Motor Speed ◽  
Dc Motors

The DC motors are widely used in the mechanisms that require control of speed. Different speed can be obtained by changing the field voltage and the armature voltage. The classic PID controllers are widely used in industrial process for speed control. But they aren’t suitable for high performance cases, because of the low robustness of PID controller. So many researchers have been studying various new control techniques in order to improve the system performance and tuning PID controllers. This paper presents particle swarm optimization (PSO) method for determining the optimal PID controller parameters to find the optimal parameters of DC Motor speed control system. The DC Motor system drive is modeled in MATLAB/SIMULINK and PSO algorithm is implemented using MATLAB toolbox. The results obtained through simulation show that the proposed controller can perform an efficient search for the optimal PID controller. Simulation results show performance improvement in time domain specifications for a step response (no overshoot, minimal rise time, steady state error = 0).

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.

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