Optimal PID Parameters Research Articles

An adaptive hybrid atom search optimization with particle swarm optimization and its application to optimal no-load PID design of hydro-turbine governor

Abstract One metaheuristic algorithm recently introduced is atom search optimization (ASO), inspired by the physical movement of atoms based on the molecular dynamics in nature. ASO displays a unique search ability by employing the interaction force from the potential energy and the constraint force. Despite some successful applications, it still suffers from a local optima stagnation and a low search efficiency. To alleviate these disadvantages, a new adaptive hybridized optimizer named AASOPSO is proposed. In this study, the individual and group cognitive components in particle swarm optimization (PSO) are integrated into ASO to accelerate the exploitation phase, and the acceleration coefficients are introduced to adaptively achieve a good balance between exploration and exploitation. Meanwhile, to improve the search performance of the algorithm, each individual atom possesses its own force constant, which is effectively and adaptively adjusted based on the feedback of the fitness of the atom in some sequential steps. The performance of AASOPSO is evaluated on two sets of benchmark functions compared to the other population-based optimizers to show its effectiveness. Additionally, AASOPSO is applied to the optimal no-load PID design of the hydro-turbine governor. The simulation results reveal that AASOPSO is more successful than its competitors in searching the global optimal PID parameters.

Genetic Algorithm–Based Robust Controller for an Inverted Pendulum Using Model Order Reduction

Abstract Robust stabilization is an important characterization to get improved in the control system to optimize the performance of the desired system. Most of the controllers available suffer from problems such as difficulty in the tuning process, sluggishness in response time, quick and global convergence, etc. This paper considered proportional-integral optimized with genetic algorithm (GA-PID)controller on inverted pendulum for the control of the angle position. A MATLAB script for a GA was developed to obtain optimum PID parameters that would keep the pendulum angle at equilibrium (i.e., returns the pendulum to the desired point as quickly as possible) by minimizing an objective function (integral time absolute error [ITAE]). Furthermore, obtained outcomes confirm the performance of holding on the upright position from the downward direction such that the angle of the pendulum is manipulated to control the inverted position in its erect position in a rapid manner. In the experimental analysis, the developed GA-based PID controller is compared with the conventional PID controller to evaluate the performance of the inverted pendulum. The obtained results show that the GA-based PID controller confirms the enhanced performance indexes by holding minimum settling time and peak overshoot on comparing with the conventional PID controller.

Improvement of Particle Swarm Optimization and its Application for Optimization of PID Parameters on FRIT

Improvement of Particle Swarm Optimization and its Application for Optimization of PID Parameters on FRIT

Autotuning Fuzzy PID Controller for Speed Control of BLDC Motor

The PID control system is widely used for industrial machine control processes. The success of PID control is determined by tuning PID parameters. In PID control the tuning is carried out offline without taking into account changes that occur in the plant and the disturbances that arise. This study aims to optimize PID parameters online by taking into account the changes that occur in the plant and the disturbances that arise using fuzzy logic-based controls and tested on a BLDC motor which is a non-linear system. Set PID parameters with fuzzy logic using a combination of 49 if-then rules. To set proper PID parameters in real time, a two-level control system was built. The first level to define PID parameters by finding the minimum and maximum values of kp, ki and kd by the reaction method curve. The second level is designing the Fuzzy system to automatically set the PID parameters, then formulating a combination of 49 fuzzy if-then rules to get the value kp, ki, kd, error and change in delta error value. Testing of set point changes at BLDC Motor loads with no load and 0.5kg load and changes in speed get a response from the PID control system with an average value of 0.025 seconds rise time, 0.1625 seconds preset time, and 15.98% overshoot. While the Fuzzy PID control produces an average rise time value of 0.0025 seconds, preset time 0.057 seconds, overshoot of 5.42%.

LQR and GA based PID Parameter Optimization: Liquid Level Control Application

Bu çalışmada iki farklı metot kullanılarak PID parametre ayarlaması yapılmıştır. İlk olarak Doğrusal Karesel Düzenleyici (LQR) yaklaşımı kullanılarak maliyet fonksiyonu minimize edilmiş ve optimal parametreler elde edilerek LQR tabanlı PID denetleyici tasarlanmıştır. Ardından LQR maliyet fonksiyonunun minimizasyonu için Genetik Algoritma (GA) kullanılmış ve GA tabanlı PID denetleyici tasarlanmıştır. Tasarlanan PID denetleyiciler bir sıvı seviye kontrol sisteminde benzetimsel ve deneysel olarak test edilmiş ve performans karşılaştırmaları yapılmıştır. Deneysel sonuçlar, GA tabanlı PID'nin performansının LQR tabanlı PID'den performans indisleri açısından daha başarılı olduğunu göstermektedir. GA Tabanlı PID için normalize edilmiş ITSE indisi 0.6479 ile daha başarılı performans sergilemiştir.

Research on PID Parameter Tuning Based on Improved Artificial Bee Colony Algorithm

Aiming at the difficulty of tuning industrial PID control parameters, an improved artificial bee colony PID tuning method is proposed. The improved artificial bee colony algorithm (IABC) uses Boltzmann selection mechanism to avoid premature convergence of roulette mechanism; at the same time, the global crossover mechanism is introduced in the domain search, which enhances the direction of the algorithm; and through chaotic avoiding search, the diversity of population is increased and the ability of global search is improved. Finally, the IABC algorithm is applied to PID parameter optimization of second order system. The simulation results show that the IABC algorithm obtains smaller ITAE and adjustment time than the basic artificial bee colony algorithm and Ziegler-Nichols engineering tuning method, and there is no overshoot. The performance of IABC algorithm is obviously improved.

Research on PID Control of Water Level in Pile Legs Based on Improved PSO

Aiming at the problem of poor water level control effect during mud dredging in pile legs, based on the research of traditional PID algorithm and particle swarm algorithm, a PID parameter optimization method based on improved PSO(IPSO)was proposed. This paper adopts a nonlinear dynamic adaptive inertial weight (ω) method and introduces a time factor to adjust the position update time. In this paper, a mathematical model of the water level control system in the leg is established, and the system is simulated by MATLAB / Simulink. By comparing the simulation results, PID controller optimized by improved PSO is better than traditional PID controller. The proposed method provides a theoretical reference for the water level control system during the mud dredging operation in the pile legs.

Optimal Stabilizer PID Parameters Tuned by Chaotic Particle Swarm Optimization for Damping Low Frequency Oscillations (LFO) for Single Machine Infinite Bus system (SMIB)

In this paper, the Power system stabilizer (PSS) and (PID) are enhanced with a Chaotic Particle Swarm Optimization (CPSO) Damping Controller in order to suppression the Low-Frequency Oscillations (LFO) in a Single Machine Infinite Bus (SMIB) power system. Chaotic particle swarm optimization (CPSO) is used to tune the parameters of the PSS-PID. The design damping controller is an optimized lead-lag controller, which extracts the speed deviation of the generator rotor and generates the output feedback signal, which aims to modulate the reference values of the PSS-PID controller to achieve the best damping of LFO. In order to search the better damping option, the damping controller is applied to a series of the PSS-PID and the results are compared in two cases (PSS without PID and PSS with PID). The effectiveness of the proposed controller is achieved by time-domain simulation results in MATLAB environment, using three different operational conditions (Nominal, Light, and heavy). In addition, the results obtained from the PSS-PID were robust and more efficient compared to the PID only in terms of oscillations damping, overshoot minimizing and settling time reducing.

Modification of speed and current limiting performance of BLDC motor based on harmony search optimization method

The brushless DC (BLDC) motor is a multi-variable and non-linear system so that it's required more advanced explaining and controlling set. In this work, an algorithm is proposed based on the harmony search algorithm (HAS) method. HSA mimics music improvisation process to find the optimal solution. In BLDC motor, many constraints are required; speed performance and current limiting control are dominated. HAS is proposed to find the optimal PID parameters for the two speed and current-limiting controllers that are proposed in the drive. By Matlab/Simulink results, a good performance is shown compared with the classical method that absence current-limiting controller.

Fuzzy self-adaptive PID control technique for driving HHO dry cell systems

When the standard operating temperatures are exceeded in hydroxy generators, production performance decreases and power consumption increases. Self-adaptive fuzzy proportional integral derivative systems have been used to prevent this situation and to maintain optimum production conditions. The Fuzzy Logic is provided to tune the optimum PID parameters by using a gain scheduling method. The tuning scheme is demonstrated by a fuzzy decision process, which consists of fuzzification, knowledge and rule base, inference and defuzzification. Results of developed fuzzy proportional integral derivative (FPID), on-off, conventional PID and fuzzy control approach are discussed and compared. The presented result shows that self-adaptive fuzzy PID controllers achieve better control performance than conventional control methods mentioned. The last but not the least, developed approach minimizes the expertise needed to apply pulse width modulation technique.

On-Line PID Parameters Optimization Control for Wind Power Generation System Based on Genetic Algorithm

An on-line PID parameter optimization control for the wind power generation system based on a genetic algorithm is proposed in this paper. Firstly, the anti-saturation PID control strategy is involved with considering the instability and complexity of the wind power source. Further, a genetic algorithm is introduced for an on-line optimization of the PID parameters. The simulation studies are carried out on a control model of wind power, using MATLAB simulation system. It is demonstrated that the proposed control strategy can not only solve the integral saturation, but also suppress the harmonics in the output waveform and enhance the power factor of system.

Control Design of the Wave Compensation System Based on the Genetic PID Algorithm

The transfer function of the wave compensation system is deduced. The interference signal acting on the system is eliminated by the feed-forward compensation correction method. The pole assignment of the system is carried out after eliminating the interference signal. The genetic PID algorithm is proposed, and the genetic PID controller is designed. The control block diagram of the wave compensation system based on the genetic PID control algorithm is established, and the optimal index and PID parameters are optimized by the crossover and mutation operators of the genetic particle swarm optimization algorithm. The simulations and experiments of the system show that the control performance of the wave compensation system based on the genetic PID algorithm is greatly improved. The higher control precision is obtained. The anti-interference ability and the robustness of the system are increased. The accuracy of the control method is verified.

Optimization of the Power Generation Control Process of Hydraulic Turbine Set Based on the Improved BFO-PSO Algorithm

Gong, X., 2019. Optimization of the power generation control process of hydraulic turbine set based on the improved BFO-PSO algorithm. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 227–231. Coconut Creek (Florida), ISSN 0749-0208.In light of the problem that it is hard to analyze the non-linear and time-varying model in the traditional hydro-generator system identification, based on the PID control parameters, this paper proposes a hydro-turbine governing system using the improved BFO-PSO algorithm, and introduces the sliding mode variable structure into the proposed improved governing system. The research results show that: the proposed BFO-PSO model has integrated the advantages of the two algorithms and has been successfully applied in the parameter optimization of the hydraulic turbine set. This paper also studies the selection of indices for optimization of PID parameters. Considering the deficiencies in the PID parameters in previous research, this paper proposes an improved fitness evaluation method, and also puts forward the concepts of stability and instability parameter sets and applies them in the stable search strategy, which effectively improves the local search capability of the model algorithm, and guarantees the stability and accuracy of the hydro-generator model. The design of multi-control-input hydro-turbine state equations can effectively solve the steady-state errors in the simulation process and explain the generation mechanism of such errors. The simulation results show that the optimization result of this algorithm significantly shortens the ITAE transition rising time of the hydro-turbine set and that the target population has been moving towards the global optimal solution, thus increasing the searching ability of the algorithm. The curve fluctuates slightly and reaches the steady state in a very short time.

A dsPIC based optimal sizing of solar PV plant using ultra capacitors for transient power delivery

Solar PV sources are being increasingly implemented in many applications due to the growing concern of environmental pollution. The capacity of solar PV depends both on the transient power and nominal power required by any type of motor loads. The present investigation reports on a method to optimize the required capacity of Solar Panel by augmenting an Ultra capacitor bank for powering the transient needs of BLDC Motor. A PID based high quality dynamic response characteristics controller was designed to improve the speed transient response of the BLDC motor thereby reducing the transient energy requirement of the BLDC Motor. Tuning of PID parameters is critical to optimise the transient behaviour of the motor. The under damped step response tuning method has achieved an optimal PID parameters without any loss in speed transients when compared with other major tuning methods. PID controller is programmed in dsPIC controller that has high-resolution control and minimal control loop delays, thereby reduces torque ripples, harmonics and improves the dynamic behaviour in all speed ranges. The proposed optimal design of PV system augmented with Ultra capacitor for transient power delivery has been modelled and simulated in MATLAB/Simulink, which resulted in a reduction of plant size by 50 percent. The results obtained in simulation are verified experimentally.

Improved Grey Particle Swarm Optimization and New Luus‐Jaakola Hybrid Algorithm Optimized IMC‐PID Controller for Diverse Wing Vibration Systems

The PID control plays important role in wing vibration control systems. However, how to efficiently optimize the PID parameters for different kinds of wing vibration systems is still an open issue for control designers. The problem of PID control optimization is first converted into internal mode control based PID (IMC‐PID) parameters optimization problem for complex wing vibration systems. To solve this problem, a novel optimization technique, called GNPSO is proposed based on the hybridization of improved grey particle swarm optimization (GPSO) and new Luus‐Jaakola algorithm (NLJ). The original GPSO is modified by using small population size/iteration number, employing new grey analysis rule and designing new updating formula of acceleration coefficients. The hybrid GNPSO benefits improved global exploration of GPSO and strong local search of new Luus‐Jaakola (NLJ), so as to avoid arbitrary and inefficient search of global optimum and prevent the trap in local optimum. Diverse wing vibration systems, including linear system, nonlinear system and multiple‐input‐multiple‐output system are considered to verify the effectiveness of proposed method. Simulation results show that GNPSO optimized method obtains improved vibration control performance, stronger robustness and wide applicability on all system cases, compared to existing evolutionary algorithm based tuning methods. Enhanced optimization convergence and computation efficiency obtained by GNPSO tuning technique are also verified by statistical analysis.

WITHDRAWN: Tabu search based optimization of PID parameters for temperature control of non-isothermal CSTR

WITHDRAWN: Tabu search based optimization of PID parameters for temperature control of non-isothermal CSTR

XY-Stage with Bimorph Piezoelectric Actuators

The paper provides results of development and study of the XY microscope stage with piezoelectric actuators. Analysis of devices of the multi-axis platform for micropositioning objects is presented. A principle operation of XY microscope stage with parallel kinematics with bimorph piezoelectric actuators (BPA) is described. The dependencies of the displacement stage for the X and Y axes of on the voltages, which were applied to the BPA are determined. The results of the experimental research in the XY-stage are given and conclusions about their using are presented. Equations of motion and transfer functions of movement for the module of control actions for the linearized model are obtained. The impact of non-linearity with hysteresis by means of computer simulation in Simulink, resulting into development of block diagrams of the control system with PID controllers on the X and Y axes is investigated. Necessary requirements in terms of accuracy and performance solutions for precise positioning tasks with feedback on moving and optimal tuning PID parameters are suggested.

Design of advanced control experimental platform for main steam pressure based on Matlab

In the field of process control, MATLAB is used for system simulation because of its powerful data processing functions. The subject of this thesis is to optimize PID parameters based on various optimization algorithms. The purpose of cascade PID controller is to control the main steam pressure, simulate the control system by MATLAB and connect Simulink with GUI interface. The parameters are set in the interface, and all the parameters are input and displayed in the GUI interface, which makes the user clear and convenient to optimize the operation interface and get the optimal value. The result of Simulink simulation was optimized and modified to achieve a complete control platform.

Design of Solar System by Implementing ALO Optimized PID Based MPPT Controller

This paper is a strive approach to design offgrid solar system in association with DC-DC boost converter and MPPT. The tuned PID based MPPT technique is adopted to extract maximum power from the solar system under certain circumstances (temperature and irradiance). The design parameters of PID controller play an imperative aspect to enhance the performance of the system. Ant lion Optimizer (ALO) algorithm is adopted to optimize PID parameters to contribute relevant duty cycle for DC-DC boost converter to maximize output power and voltage. P and O based MPPT technique is implemented to validate the supremacy of PID based MPPT to enhance the response of the system. In this paper, the proposed ALO optimized PID controller based MPPT technique is performed better over conventional P & O technique by conceding the oscillation, time response, settling time and maximum values of voltage, current and power of the solar system. Citation: SAHU, R. K., and Shaw, B. (2018). Design of Solar System by Implementing ALO Optimized PID Based MPPT Controller. Trends in Renewable Energy, 4, 44-55. DOI: 10.17737/tre.2018.4.3.0049

Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization

Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey- Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the particle velocity limit and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO- PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Furthermore, the physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning method responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a tuning method in the hydraulic positioning system.