Time Domain Specifications Research Articles

Analytic Time Domain Specifications PID Controller Design for a Class of 2nd Order Linear Systems: A Genetic Algorithm Method

In this paper, an analytical approach of a Proportional-Integral-Derivative (PID) controller design for a servo motor position control with precise desired performance demands is presented. When designing linear controllers, the resulting closed-loop system is often considered as an approximation of a standard 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> order system to simplify the gain design process. However, in reality, model discrepancies could exist in such approximation, which inevitably lead to performance mismatches between the actual system's behavior and the desired one. In order to solve this issue, this paper presents an analytical PID controller solution, which is able to achieve desired time domain specifications precisely. In addition, a disturbance is added to the system and the associated PID controller will be designed to reject disturbance. Given a 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> order linear system along with a PID controller, the related analytical solutions are derived first. Next, the associated fitness functions and constraints are constructed under given prescribed time domain specifications. Lastly, the PID control gains are determined using Genetic Algorithm. To demonstrate the effectiveness of the proposed solution, many numerical simulations are performed. A set of control gains is also found using the standard 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> order system formulas in order to prove the accuracy of the presented method. Moreover, a comparison study with respect to the MATLAB PID Tuner is considered to illustrate the advantage of the proposed PID design scheme. The main contributions of this study include precisely satisfying given control performance demands with exact analytical solutions, avoiding the existing model discrepancies between the standard 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> order system and the exact closed-loop model. Simulations firmly prove that the proposed method can fulfill users' different control demands as well as remove the frequently used trial-and-error strategy.

Modeling and control of 3D filament extruder

This article allows a study of the electrical and control parts of a pilot extruder in order to transform polymers in the form of filaments used by the 3D printer. The input materials used are often thermoplastics in the form of granules or plastic waste. This paper aims are to design and manufacture the control part of a filament extruder in order to avoid many existing problems such as a longer settling time, large time constants, and undesirable overshoot. The proposed solution combined with a digital PID corrector, will have improvements in terms of time domain specification, set point tracking and eliminating static error by ensuring optimal system stability.The control method will be simulated and visualized using MATLAB\\Simulink software. In order to proceed with an analysis of the structural integrity of a high voltage electrical cable since the placement of the insulation part in a HV electrical cable is made by an extrusion directly around the conductive core.

Dynamic Performance Improvement of Pitch Angle Control Using PID and PIDA Controllers for Wind Generation Systems

Abstract Recently, wind energy is one of energy sources most have been devoted much awareness as result of shortage of energy. This study shows loads which are formed in the rotating shaft of wind turbine (WT). These loads cause disturbances on the blades, which leads to damage the blades. these loads can be exceeded, and the amount of productive energy can be controlled by using a good control unit that adjusts the angle of the WT blade. For the previous purpose, independent electric motor is used to control blade pitch, this process called pitch control (PC) system. This paper presents a mathematical model of PC system that is controlled by using two different controllers in MATLAB/Simulink; proportional -integral-derivative controller (PID) and proportional -integral-derivative-acceleration (PIDA). In this system three different function are used as reference pitch angle; unit step function, sinewave function and step change signal which are used on control system without any controller and it is found that output system isn’t reached to a reference value for three functions. The steady state error equal to 76% when step function is used, so the controller is needed for a system. When PID and PIDA controllers are used, the time domain specification of output is improved. The steady state error in PID and PIDA controllers is 9% and 0.014% respectively. It is found that the better time domain specification is given by PIDA. PID and PIDA controllers are tested with sinewave and step change, PIDA is also produced the best response.

Optimization Performance Integral Criteria Based on Hybrid Soft Computing for QTS System

This research work proposed MPSO methods for nonlinear complex QTS process. This system is implemented in various process control industries, design, and development of a new controller to increase the better stability and improve the performance of integral criteria. This proposed work goal is to minimize parameters for process controller by statistical Taguchi method combined with mutation particle swarm optimization algorithm for industrial laboratory highly complex nonlinear QTS. The designed value is tested using Simulink model in MATLAB. Using proposed controller values are tested in the real experiment set up and experiment output response is reached. The various controller designed are PID controller for QTS. The result shows that TMPSO technique is provided the good result when compared with other approaches. The TMPSO techniques use for setting controller offers enhanced process specification such as better time domain specifications, smooth error reference tracking, and minimization of error in the nonlinear system.

An isolated photovoltaic power generation system with a novel fractional order PID controller based control strategy

The renewable energy resources such as photovoltaic systems have major role in the development of sustainable energy systems. An efficient controller for standalone photovoltaic system based on fractional calculus is proposed in this work. The power extracted from the PV systems are continuously varies with respect to the dynamic changes of solar irradiance value and climate temperature. Here we introduce a Maximum Power Point Tracking (MPPT) algorithm is which realized with the support of Fractional Order PID (FOPID) controllers to extract the maximum possible power from the Photo Voltaic(PV)modules. The PID controller and FOPID controllers are also ensures the constant dc bus voltage and hence the ac output voltage at become stable. The effectiveness of the controller are compared using various performance time domain specifications like overshoot percentage, rise-time, settling-+time, etc. The various analysis were done under the variation of irradiance and temperature in MATLAB Simulink platform. The FOPID controller give improved performance compare with conventional PID controllers.

Self-Learning Salp Swarm Optimization Based PID Design of Doha RO Plant

In this investigation, self-learning salp swarm optimization (SLSSO) based proportional- integral-derivative (PID) controllers are proposed for a Doha reverse osmosis desalination plant. Since the Doha reverse osmosis plant (DROP) is interacting with a two-input-two-output (TITO) system, a decoupler is designed to nullify the interaction dynamics. Once the decoupler is designed properly, two PID controllers are tuned for two non-interacting loops by minimizing the integral-square-error (ISE). The ISEs for two loops are obtained in terms of alpha and beta parameters to simplify the simulation. Thus designed ISEs are minimized using SLSSO algorithm. In order to show the effectiveness of the proposed algorithm, the controller tuning is also accomplished using some state-of-the-art algorithms. Further, statistical analysis is presented to prove the effectiveness of SLSSO. In addition, the time domain specifications are presented for different test cases. The step responses are also shown for fixed and variable reference inputs for two loops. The quantitative and qualitative results presented show the effectiveness of SLSSO for the DROP system.

Decentralised design of robust multi‐objective PSSs: D ‐decomposition approach

This study addresses the problem of determining the set of all robust three-parameter power system stabilisers having the form . Graphical characterisation of stabilising power system stabilisers (PSSs) is carried out using D-decomposition, whereas the controller–parameter space is subdivided into root-invariant regions. Rather than Hurwitz stability, D-decomposition can parameterise D-stabilising PSSs that enforce pole-clustering in a pre-specified region D to ensure better time-domain specifications. The convex region of D-stabilising PSSs is sketched by mapping the contours from the s-plane onto the controller–parameter plane by two parametric functions and with fixed . The frequency range considered for mapping is initially computed to avoid sweeping over unnecessary frequencies. Based on the geometry of the D-stability region, analytical expressions are derived to compute optimal σ − ζ PSSs for an arbitrary operating point. Parametric uncertainties are captured by an image-set polynomial where the region guarantying robust D-stability of the family is investigated. A computationally effective approach based on stabilising two vertex plants is concluded from the D-stability region. Extension to multi-machine systems is treated where decentralised PSSs are synthesised. An iterative algorithm is suggested to modify a set of initial feasible PSSs sequentially while maximising damping indices. Simulation results confirm the efficacy of the suggested method.

Optimal Reduced Order Model of Single- Shaft Heavy Duty Gas Turbine Power Plants

Design of controller and analyzing the response of higher order system in real time environment would be very complex and expensive. Therefore, an attempt has been made in this paper to obtain the reduced order model of single-shaft Heavy duty gas turbine plants ranging from 18.2 to 106.7 MW by using various model order reduction techniques. The step response of Heavy duty gas turbine model using the reduced order models are compared with that of the original MATLAB/ Simulink model. Various time domain specifications and performance index criteria have been considered for analyzing the responses. The simulation results show that the response obtained by Routh approximation-Pade approximation technique based reduced order model mimics the original, higher order Heavy Duty gas turbine response. It is also proposed in this paper to improve the response by optimizing the co-efficients of reduced order model using Particle Swarm Optimization technique. On comparing the simulation results, Particle Swarm Optimization technique based reduced order model yield better transient and steady state response as close to original higher order system and hence it is identified as an optimal reduced order model for all Heavy Duty gas turbine plants in grid connected operation

Optimal design of robust resilient automatic voltage regulators

Uncertainties in the plant model parameters and perturbations in the controller gains imposed by implementation errors represent a challenge to ensure robust stability and controller non-fragility simultaneously. Optimal design of robust non-fragile proportional–integral–derivative (PID) controller is presented for an automatic voltage regulator (AVR). The PID design relies basically on Kharitonov theorem and optimization by future search algorithm (FSA). The proposed algorithm has low computational complexity and fast convergence rate because it utilizes both local and global search methods. Further, FSA can improve the exploration characteristic and prevent trapping in local optima by updating its random initial. The PID controller is optimized by FSA to cope with expected parametric uncertainties of the plant model and tolerate its gain perturbations such that robust stability and controller non-fragility are simultaneously met. An interval plant model is suggested to account for model uncertainties where only eight extreme plants derived by Kharitonov theorem are considered in design. FSA-based PID optimization is constrained by the stability conditions of Kharitonov’s plants derived using Routh–Hurwitz. A new figure-of-demerit (FoD) based performance index is suggested to enforce simultaneous minimization of the time domain specifications. The suggested objective function is represented by a weighted sum of FoD of nominal response and the sum of reciprocals of the perturbation radii of PID gains. The output results of the recommended design are compared to that of artificial bee colony (ABC) algorithm and teaching–learning based optimization (TLBO) algorithm, multi-objective extremal optimization (MOEO), and non-dominated sorting genetic algorithm II (NSGA II). The results can confirm better response of the suggested technique measured up to other techniques where robustness and non-fragility are simultaneously ensured.

Closed loop control of DC-DC converters using PID and FOPID controllers

Fractional order controllers are nowadays used in various power electronic converters as it is giving superior control performance compared with conventional PID controllers. This paper presents the closed loop control of different DC-DC converters using PID controllers and Fractional Order PID (FOPID) controllers. The closed loop control of the basic converters such as buck, boost, buck-boost converters and dual input single output DC-DC converters were designed, modeled and analyzed using conventional PID controller and FOPID controllers. The performance of the controllers are compared in terms of the different time domain specifications like overshoot, rise time, settling time, etc. and simulated in MATLAB Simulink platform. For all types of the DC-DC converters, FOPID controller gives far better performance compared with conventional PID controllers.

Feedback controller for restoring the basal hemodynamic condition with a rotary blood pump used as left ventricular assist device

This work deals with the use of pulsatility indices in designing a ventricular assist device (VAD) control system. The control objective is to restore the patient's basal hemodynamic energy. The proposed control system structure comprises a hierarchy of cascaded control loops. At the highest level, there is the pressure feedback control loop, and at the lowest level, there are feedback control loops for both the rotational speed and the armature current. The reference signal for the high-level controller has a pulsatile profile. The generation of this pulsatile profile employs a procedure that takes into account the fulfillment of physiological specifications. Among the considered physiological requirements, there is the mean arterial pressure (MAP), the energy equivalent pressure (EEP), or the surplus hemodynamic energy (SHE). The gains of the low-level controllers are calculated based on the time-domain specification and the VAD mathematical model parameters. On the other hand, high-level controller gains are determined by using integral performance error criteria as tuning rule. The results obtained in silico indicate the feasibility of the proposed control system as well as its related design procedure. With the generated reference pump profile, it is possible to restore the basal hemodynamic condition for a heart failure patient. Besides, the restored basal hemodynamic condition is quite robust since it is maintained even under variations of the systemic resistance and heartbeat rate.

Polynomial Controller Design and Its Application: Experimental Validation on a Laboratory Setup of Nonideal DC–DC Buck Converter

The transient response control is one of the most important tasks in the control system design. The transient response has characterized based on the relationship between characteristic ratios and time domain specifications. The characteristic ratios are the design parameters of the characteristic ratio assignment (CRA) approach. This article presents a novel polynomial controller for all types of linear second-order systems. The proposed controller is designed using CRA. The important features of this controller are that it has simple design steps, set-point tracking, and disturbance rejection capabilities. Initially, the proposed controller is designed for an unstable nonminimum-phase second-order system to demonstrate the performance and robustness. Subsequently, the presented controller is analyzed and validated on the nonideal dc–dc buck converter. The buck converter is highly sensitive to the suddenly changing load conditions. The major issue of output voltage control in the dc–dc buck converter is addressed in this article. In addition, the robustness and performance of the proposed controller are verified for the sudden change in supply input voltage, the sudden change in the reference voltage, the parametric uncertainty in inductor ( $L$ ) and capacitor ( $C$ ), and the sudden change in load. Furthermore, the efficacy of the proposed controller is evaluated by comparing it with the recently published control schemes for this converter. The proposed controller is implemented using dSPACE 1104 real-time controller. Applicability of the presented controller is corroborated experimentally on the nonideal dc–dc buck converter. The simulation as well as hardware results recommend that the proposed controller is suited for the nonideal dc–dc buck converter under such conditions.

Robust multi-objective PSSs design via complex Kharitonov's theorem

This paper represents a step toward shooting an optimal robust three-parameter power system stabilizer (PSS) with the common form of (x1+x2s)/(1+x3s). The whole set of stabilizing PSSs is graphically characterized using d-decomposition with which the controller-parameter space is subdivided into root-invariant regions. Design is accomplished using the bench mark model of single machine-infinite bus system (SMIB). Rather than Hurwitz stability, d-decomposition is extended to consider d-stability where D refers to a pre-specified damping cone in the open left half of the complex s-plane to enhance time-domain specifications. Pole clustering in damping cone is inferred by enforcing Hurwitz stability of a complex polynomial accounting for the geometry of such cone. Parametric uncertainties of the model imposed by continuous variation in load patterns is captured by an interval polynomial. As a result, computing the set of all robust d-stabilizing PSSs calls for Hurwitz stability of a complex interval polynomial. The latter is tackled by a complex version of Kharitonov's theorem. A less-conservative and computationally effective approach based on only two extreme plants is concluded from the geometry of the stability region in the controller parameter plane. Simulation results affirm the robust stability and performance with the proposed PSSs over wide range of operating points.

Analysis on Advanced Controllers for Mean Arterial Pressure

Control of hemodynamic variables such as Mean Arterial Pressure (MAP) has been approached using single drug Noradrenaline by various control algorithms and compared the results with patient model obtained using single drug Dopamine in the literature. This paper presents the design and implementation of the controllers such as Proportional Integral (PI), Proportional Integral Derivative (PID), Smith Predictive Controllers for the patient model which is developed by the readings obtained during Cardiovascular surgery. Implementation of these controllers is necessary to improve and automatically maintain the patient safety and minimum recurring time. The controlled Mean Arterial Pressure is compared, and time domain specifications are determined. Simulation results are obtained using MATLAB Software.

Design and implementation of a current controlled grid connected inverter for thermoelectric generator sources

This paper presents the digital implementation of a current controlled grid connected inverter for Thermoelectric Generator (TEG) sources. Considering the electrical characteristics of a TEG source, several important aspects that a designer has to consider in selecting the rating of power converters for the grid connected operation of TEG source are discussed. The closed loop control of a TEG fed grid connected voltage source inverter (VSI) requires line current control to regulate the power pumped into the grid. Considering the inverter, current sensor and line inductor models, a simplified method is espoused to determine the parameters of the digital current controller. An Altera Cyclone II FPGA board is used to implement the current control strategy in VSI fed with TEG power source. The proposed design approach is validated using simulations and experiments and verified with the time domain specifications.

Heuristic Algorithm Assisted Controller Design for Nonlinear Type Liquid Level Process

In process control industries, controlling the liquid inside the non-linear tanks such as a conical tank, hopper tank and spherical tank is a highly challenging task due to the change in the cross section area of the tank. The aim of this project is to design a suitable controller to control the level of the hopper type tank by using conventional controllers like Ziegler-Nichols tuning method (ZN) and computational controllers using metaheuristic algorithms such as Bacteria Foraging Optimization (BFO) algorithm, Particle Swarm Optimization (PSO) algorithm and Firefly Algorithm (FA). This controller can be used for the industries that deal with this nonlinear type of process. The mathematical model for the conical tank was done to identify the transfer function of the system. The conventional and computational controllers were designed and implemented using MATLAB/Simulink to choose the best controller for the conical/hopper type tank liquid level process based on the time domain specifications such as rise time, settling time and peak overshoot percentage. Moreover, the performance of the system was analyzed based on the error indices such as Integral Square Error (ISE), Integral Absolute Error (IAE), Integral Time Square Error (ITSE) and Integral Time Absolute Error (ITAE). Also, servo and regulatory operations were tested for the chosen best controller.

Modeling and optimized controller for cardiac drug infusion system

Background: Manual drug infusion during surgeries is inaccurate and timeconsuming which has been adopted technique in most of the hospitals. Methods: Based on clinical data, it is evident that the manual control is inaccurate and takes prolonged time to bring into effect, if any change in infusion rate is required during clinical practice. Considering this drawback, the modeling of cardiovascular system (CVS) and baroreceptor (BR) is developed using miscellaneous differential equations based on compartmental approach. The control variables are mean arterial pressure (MAP) and cardiac output (CO) obtained from CVS-BR model. Findings: The manipulated variables are noradrenaline (NAR) and nitroglycerine (NG) infusion rate which is modeled using the relationship between volume and drug mass effect equations on CVS-BR model. For the open loop transfer function derived from the model, relative gain array (RGA) analysis is performed to identify the influence of maximum effect of manipulated variables on the physiological parameters. The simulation results obtained from MATLAB are correlated using time domain specifications and error criteria. The performance index reveals the least error and facilitates in accurate infusion of drugs to the patient during cardiovascular surgeries. Novelty: The automatic controller during surgery provides safe operating condition and speedy recovery of the patients and also helps the anaesthetist to monitor and regulate the physiological variables. Keywords: Control strategy; Error criteria; Drug infusion; Modeling; Relative gain array; Simulation

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

Nowadays, the PID controller is very common controller as well as very important controller in industrial utilizations. In the paper, proposed an ALO algorithm and ANN controller is utilized to enhance PID controller performance and control the tuning of TDS. TDS stands for Time delay system. ALO stands for Ant lion optimizer and ANN stands for Artificial neural network. In terms of parameters controlling, the time delay system is controlled and for different delay events low overshoot and fast time settling is reached. The novelty of the presented method is enhancing the PID controller performance by optimizing the PID gain parameters and controlling the highorder TDS. The performance of time delay system can be enhanced through decreasing error, tracking, time delay &amp; error, rapid and exactly for their corresponding reference values. For parameter controlling of time delay system along optimal values, can be significantly enhanced the performance. To analyze the characteristics of the presented method, the various time delay systems are analyzed. The input and gain parameters were utilized to evaluate the objective function from tuning system. Based on proposed method, the optimal result is achieved and evaluated the increae time, settling time, overshoot as well as steady state error in TDS. The suggested controller is executed in MATLAB/Simulink work site and the presented technique performance examined through performance indexes and time domain specifications are evaluated using presented method compared to previous methods like ABC (Artificial Bee colony) algorithm, GSA (Gravitational Search Algorithm) ,FA (Firefly Algorithm).

Design of High Performance Converter for PMSM Applied to Flywheel Energy Storage Array

A multi-objective visual design method of permanent magnet synchronous motor (PMSM) drive system which is applied to flywheel energy storage array is proposed. D-partition technique is applied to obtain the parameters stable region. Besides, frequency-domain specifications such as gain margin and phase margin, time-domain specifications such as overshoot and settling time are considered. Furthermore, a parameters design method is proposed and the optimized performance can be derived which meets the time- and frequency-domain specifications simultaneously. Simulation and experimental results verify the effectiveness and practicability.

An empirical Study Investigation of Task Allocation Process Barriers in the Context of Offshore Software Development Outsourcing: An Organization Size Based Analysis

This research presented a holistic approach in determining the trade-off optimized Proportional-Integral-Derivative (PID) tunings for both servo and regulatory controls of the cascade control loop by using Genetic Algorithm (GA). Performance of GA-based PID tunings was significantly compared with the IMC-based single loop tunings and conventional cascade control tunings. GA-based PID tunings eliminated the complicated mathematic calculations in obtaining the correlation PID tuning values and also reduce the dependency on engineering knowledge, experience, and skills. The performance of transient and steady-state responses was compared through time domain specification, performance index, and process response curve. It is concluded that the GA-based PID tunings for the cascade control loop had produced the best result for both servo and regulatory control objectives, which is eventually determined.