Overshoot Values Research Articles

Simulation and Implementation PID Controlling Buck Converter DC

Regulating the output voltage based on the desired set point is useful for many applications. However, getting the optimal value using fast computation with minimal error is still challenging. This paper aims to design, simulate, and implement a second-order Buck-Boost DC-DC converter circuit so that the voltage result according to the desired set point can be achieved. Initially, testing is conducted using Matlab Simulink. Then, Proteus is used to test the computation of the program on embedded systems in which the result is implemented in C. In low voltage power electronics applications, this approach has never been used to determine the output form. To determine the value of Kp, Ki, dan Kd, PID, Ziger Nichos (Guo, 2002). method is used. Meanwhile, tuning is done through Matlab. For simulation on Proteus, the output is tested by setting the setpoint values of 3.0, 2.5, and 1.7 volts. This aims to see the pattern of changes in the simulation. The simulation results with Proteus show that they have similar peak values but with different overshoot values. This is because the simulation must pass the reference voltage before it drops to the desired setpoint value. Proteus simulation can also help to prove embedded system programs are running correctly. On the other hand, the value of 1.7 volts is used as a setpoint in device implementation. This is due to the determination that the setpoint voltage in the implementation does not exceed the value of the source/power supply. The results show that for the rise time value of 378,770 ms, Overshoot and settling time are 11.798% and 0, respectively. This means the result produces an optimal value which is a return to the initial target. The optimal factor is assessed from the ability to minimize existing errors as well as having the shortest possible computational process.

Analysis of Unidirectional Secondary Resonant Single Active Bridge DC–DC Converter

A compact and highly efficient unidirectional DC–DC converter is required as a battery charger for electrical vehicles, which will rapidly become widespread in the near future. The single active bridge (SAB) converter is proposed as a simple and high-frequency isolated unidirectional converter, which is comprised of an active H-bridge converter in the primary side, an isolated high frequency transformer, and a rectifying secondary diode bridge output circuit. This paper presents a novel, unidirectional, high-frequency isolated DC–DC converter called a Secondary Resonant Single Active Bridge (SR–SAB) DC–DC converter. The circuit topology of the SR–SAB converter is a resonant capacitor connected to each diode in parallel in order to construct the series resonant circuit in the secondary circuit. As a result, the SR–SAB converter achieves a higher total power factor at the high frequency transformer and a unity voltage conversion ratio under the unity transformer turns ratio. Small and nonsignificant overshoot values of current and voltage waveforms are observed. Soft-switching commutations of the primary H-bridge circuit and the soft recovery of secondary diode bridge are achieved. The operating philosophy and design method of the proposed converter are presented. Output power control using transformer frequency variation is proposed. The effectiveness of the SR–SAB converter was verified by experiments using a 1 kW, 48 VDC, and 20 kHz laboratory prototype.

Feedback Linearization-Based Control Strategy for Interlinking Inverters of Hybrid AC/DC Microgrids with Seamless Operation Mode Transition

This study proposes an advanced control scheme for the interlinking inverters of the hybrid AC/DC microgrids, which facilitates a seamless transition between grid-connected and stand-alone/islanding modes for the microgrid. Due to a nonlinear relationship between the terminal voltages of the voltage-source inverter (VSI) interfacing through inductor–capacitor (LC) filters with the grid voltages and currents, a feedback linearization technique (FLT) is employed to control the interlinking VSI under both grid-connected and islanding operations. The FLT-based current controllers are applied in the grid-connected mode, in which they adjust the power exchange between the DC and AC subgrids and mitigate the distortion of the grid currents produced by nonlinear loads. Under the stand-alone operation, the AC bus voltages are directly regulated by the FLT-voltage controllers of the interlinking VSI. In order to reduce the inrush currents and voltage overshot at the instant of mode switching, the FLT-based controllers are performed all the time regardless of the operating modes, where the voltage references for the VSI are not changed abruptly. The control performance of the VSI is highly satisfactory with low-transient overshoot values of the voltages and currents and low total harmonic distortion (THD) values of the grid currents and AC bus voltages are about 3.5% and 2.7%, respectively, under the nonlinear load condition. The validity of the new control strategy is verified by the simulation work, which investigates the operation of a hybrid AC/DC microgrid.

PERFORMANCE STUDIES ON WATER FLOW CONTROL USING P, PI AND PID CONTROLLERS

The main purpose of this study is to revitalize the concept of wise and controlled supply of water for domestic, industrial and agricultural applications which facilitate sustainable usage of fresh water resources. As Eritrea is striving to manage its water resources, attention paid primarily to enable water flow control mechanisms in municipal water distribution systems. A table top process control trainer (PCT) was tested through proportional(P), integral (I) and derivative (D) control mechanisms using Ziegler-Nichols second method to evaluate the tuning variables. Applying exclusively P control action, critical period of oscillation (𝑃𝑃𝑐𝑐𝑐𝑐) was estimated as 1.4 sec at proportional band value of 9. P, PI and PID controller performance studies were conducted with tuned variables on the water flow control system at different step disturbances between 20 – 50 % and their corresponding responses were characterized. P controller exhibited faster responses with consistent increments in offset, PI controller recorded highest overshoot values with negligible offset and prolonged settling times. PID controller showed less overshoot values and faster response times than PI but it increased chatter on the control output signal. The study revealed that the system can be safely controlled between 0-80 LPH. If the offset is not a major concern, P controller would be reflected suitable with simple design and minimum expenditure, else PI controller makes offset to zero though it possesses higher settling times. In other words, PID controller is complex using more tuning parameters, need expensive maintenance, and has resulted an intermittent noise in the output signal.

Chaotic-based particle swarm optimization algorithm for optimal PID tuning in automatic voltage regulator systems

Introduction. In an electrical power system, the output of the synchronous generators varies due to disturbances or sudden load changes. These variations in output severely affect power system stability and power quality. The synchronous generator is equipped with an automatic voltage regulator to maintain its terminal voltage at rated voltage. Several control techniques utilized to improve the response of the automatic voltage regulator system, however, proportional integral derivative (PID) controller is the most frequently used controller but its parameters require optimization. Novelty. In this paper, the chaotic sequence based on the logistic map is hybridized with particle swarm optimization to find the optimal parameters of the PID for the automatic voltage regulator system. The logistic map chaotic sequence-based initialization and global best selection enable the algorithm to escape from local minima stagnation and improve its convergence rate resulting in best optimal parameters. Purpose. The main objective of the proposed approach is to improve the transient response of the automatic voltage regulator system by minimizing the maximum overshoot, settling time, rise time, and peak time values of the terminal voltage, and eliminating the steady-state error. Methods. In the process of parameter tuning, the Chaotic particle swarm optimization technique was run several times through the proposed hybrid objective function, which accommodates the advantages of the two most commonly used objective functions with a minimum number of iterations, and an optimal PID gain value was found. The proposed algorithm is compared with current metaheuristic algorithms including conventional particle swarm optimization, improved kidney algorithm, and others. Results. For performance evaluation, the characteristics of the integral of time multiplied squared error and Zwe-Lee Gaing objective functions are combined. Furthermore, the time-domain analysis, frequency-domain analysis, and robustness analysis are carried out to show the better performance of the proposed algorithm. The result shows that automatic voltage regulator tuned with the chaotic particle swarm optimization based PID yield improvement in overshoot, settling time, and function value of 14.41 %, 37.91 %, 1.73 % over recently proposed IKA, and 43.55 %, 44.5 %, 16.67 % over conventional particle swarm optimization algorithms. The improvement in transient response further improves the automatic voltage regulator system stability for electrical power systems.

Modified Posicast Control Design Method Based on the Parameters of a Fractional Order System

Abstract In this study, a novel design method for half-cycle and modified posicast controller structures is proposed for a class of the fractional order systems. In this method, all required design variable values, namely, the input step magnitudes and their application times are obtained as functions of fractional system parameters. Moreover, empirical formulas are obtained for the overshoot values of the compensated system with half-cycle and modified posicast controllers designed utilizing this method. The proposed design methodology has been tested via simulations and ball balancing real-time system. It is observed that the derived formulas are in coherence with outcomes of the simulation and real-time application. Furthermore, the performance of modified posicast controller designed using proposed method is much better than other posicast control method.

Optimal Fuzzy PIDF Load Frequency Controller for Hybrid Microgrid System Using Marine Predator Algorithm

This paper presents a fully optimized fuzzy proportional-integral-derivative with filter (FPIDF) load frequency controller (LFC) for enhancing the performance of a hybrid microgrid system. The Marine Predator Algorithm (MPA), a recent optimization algorithm, is used to optimize the gains as well as the input scaling factors and membership functions of the proposed fuzzy PIDF controller. The controller performance is tested on a two-area hybrid microgrid system containing various renewable energy sources and energy storage devices. The effectiveness of the MPA based FPIDF controller is compared with conventional PIDF and FPIDF controllers based on other heuristic techniques presented in literatures. Moreover, different scenarios are implemented in this study to verify the robustness and sensitivity of the proposed controller to different step load perturbations, system parameters variations, wind speed fluctuation and solar irradiance variation. The dynamic response of the system is compared using different controllers in terms of settling time, maximum overshoot and undershoot values. The results are presented in the form of time domain simulations conducted via MATLAB/SIMULINK.

Offline ANN-PID Controller Tuning on a Multi-Joints Lower Limb Exoskeleton for Gait Rehabilitation

This paper presents Artificial Neural Network (ANN) as an optimization tool in tuning Proportional-Integral-Derivative (PID) controller's gain of a multi-joints Lower Limb Exoskeleton (LLE) for gait rehabilitation. The interest in wearable post-stroke and spinal cord injury rehabilitation devices such as LLE has been increasing due to the demand for assistive technologies for paralyze patients and to meet the concerns in the increasing number of ageing society. The dynamic of three degree of freedom LLE was determined using Euler-Lagrange equation, and PID parameters were initially tuned using the Ziegler-Nichols (ZN) method. The paper compares different ANN-based algorithms in tuning PID controller's gain for LLE applications. The method compared and evaluated with other methods and dynamic systems in the literature. ANN-based algorithms, Gradient Descent, Levenberg-Marquardt, and Scaled Conjugate Gradient, are utilized for PID tuning of each joint in the LLE model. The result shows faster convergence and improves step response characteristics for each controlled joint model. The overshoot values found to be 0.3126%, 0.6335%, and 0.2619% compared to the ZN method with 10.5582%, 15.1643%, and 11.8511% for hip, knee, and ankle joints, respectively. It can be ascertained that the PID controlled of LLE has been optimally tuned significantly by different ANN methods, which reduced its steady-state errors.

Transient Dynamics of a Miura-Origami Tube during Free Deployment

With excellent folding-induced deformability and shape reconfigurability, origami-based designs have shown great potentials in developing deployable structures. Noting that origami deployment is essentially a dynamic process, while its dynamical behaviors remain largely unexplored owing to the challenges in modeling. This research aims at advancing the state of the art of origami deployable structures by exploring the transient dynamics under free deployment, with the Miura-origami tube being selected as the object of study because it possesses relatively simple geometry, exceptional kinematic properties, and wide applications. In detail, a preliminary free deployment test is performed, which indicates that the transient oscillation in the transverse direction is nonnegligible and the tube deployment is no longer a single-degree-of-freedom (SDOF) mechanism. Based on experimental observations, four assumptions are made for modeling purposes, and a 2N-DOF dynamic model is established for an N-cell Miura-origami tube to predict the transient oscillations in both the deploying and the transverse directions. Employing the settling times and the overshoot values as the transient dynamic indexes, a comprehensive parameter study is then carried out. It reveals that both the physical and geometrical parameters will significantly affect the transient deploying dynamics, with some of the parameter dependence relationships being counter-intuitive. The results show that the relationships between the transient dynamic behaviors and the examined parameters are sometimes contradictory in the deploying and the transverse directions, suggesting the necessity of a compromise in design.

Convective boundary mixing in low- and intermediate-mass stars – I. Core properties from pressure-mode asteroseismology

ABSTRACT Convective boundary mixing (CBM) is ubiquitous in stellar evolution. It is a necessary ingredient in the models in order to match observational constraints from clusters, binaries, and single stars alike. We compute ‘effective overshoot’ measures that reflect the extent of mixing and which can differ significantly from the input overshoot values set in the stellar evolution codes. We use constraints from pressure modes to infer the CBM properties of Kepler and CoRoT main-sequence and subgiant oscillators, as well as in two radial velocity targets (Procyon A and α Cen A). Collectively, these targets allow us to identify how measurement precision, stellar spectral type, and overshoot implementation impact the asteroseismic solution. With these new measures, we find that the ‘effective overshoot’ for most stars is in line with physical expectations and calibrations from binaries and clusters. However, two F-stars in the CoRoT field (HD 49933 and HD 181906) still necessitate high overshoot in the models. Due to short mode lifetimes, mode identification can be difficult in these stars. We demonstrate that an incongruence between the radial and non-radial modes drives the asteroseismic solution to extreme structures with highly efficient CBM as an inevitable outcome. Understanding the cause of seemingly anomalous physics for such stars is vital for inferring accurate stellar parameters from TESS data with comparable timeseries length.

Fully Distributed Low-Complexity Control for Nonlinear Strict-Feedback Multiagent Systems With Unknown Dead-Zone Inputs

In this paper, the distributed control problem of nonlinear strict-feedback multiagent systems is addressed under directed and time-invariant communication graphs. With the utilization of the prescribed performance control methodology, a control algorithm is proposed to ensure predefined bounds of overshoot, convergence rates, and steady-state values of the neighborhood synchronization errors in the presence of unknown dead-zone inputs. The algorithm is fully distributed in the sense that the control input for each agent is independent of any global information of the communication graph and is solely based on local relative output information from its neighborhood set. The approximating structures, e.g., neural networks or fuzzy systems, and the command filters that are typically incorporated to avoid the need for analytical derivatives in the backstepping design are not employed here, resulting in a low-complexity design. Simulation results are included to verify the algorithm.

Multi-objective optimization of a sports car suspension system using simplified quarter-car models

In this paper, first, the vibrational governing equations for the suspension system of a selected sports car were derived using Lagrange's Equations. Then, numerical solutions of the equations were obtained to find the characteristic roots of the oscillating system, and the natural frequencies, mode shapes, and mass and stiffness matrices were obtained and verified. Next, the responses to unit step and unit impulse inputs were obtained. The paper compares the effects of various values of the damping coefficient and spring stiffness in order to identify which combination causes better suspension system performance. In this regard, we obtained and compared the time histories and the overshoot values of vehicle unsprung and sprung mass velocities, unsprung mass displacement, and suspension travel for various values of suspension stiffness (KS ) and damping (CS ) in a quarter-car model. Results indicate that the impulse imparted to the wheel is not affected by the values of CS and KS . Increasing KS will increase the maximum values of unsprung and sprung mass velocities and displacements, and increasing the value of CS slightly reduces the maximum values. By increasing both KS and CS we will have a smaller maximum suspension travel value. Although lower values of CS provide better ride quality, very low values are not effective. On the other hand, high values of CS and KS result in a stiffer suspension and the suspension will provide better handling and agility; the suspension should be designed with the best combination of design variables and operation parameters to provide optimum vibration performance. Finally, multi-objective optimization has been performed with the approach of choosing the best value for CS and KS and decreasing the maximum accelerations and displacements of unsprung and sprung masses, according to the TOPSIS method. Based on optimization results, the optimum range of KS is between 130 000–170 000, and the most favorable is 150, and 500 is the optimal mode for CS .

Momentum and heat transfer of a special case of the unsteady stagnation-point flow

This paper investigates the unsteady stagnation-point flow and heat transfer over a moving plate with mass transfer, which is also an exact solution to the unsteady Navier-Stokes (NS) equations. The boundary layer energy equation is solved with the closed form solutions for prescribed wall temperature and prescribed wall heat flux conditions. The wall temperature and heat flux have power dependence on both time and spatial distance. The solution domain, the velocity distribution, the flow field, and the temperature distribution in the fluids are studied for different controlling parameters. These parameters include the Prandtl number, the mass transfer parameter at the wall, the wall moving parameter, the time power index, and the spatial power index. It is found that two solution branches exist for certain combinations of the controlling parameters for the flow and heat transfer problems. The heat transfer solutions are given by the confluent hypergeometric function of the first kind, which can be simplified into the incomplete gamma functions for special conditions. The wall heat flux and temperature profiles show very complicated variation behaviors. The wall heat flux can have multiple poles under certain given controlling parameters, and the temperature can have significant oscillations with overshoot and negative values in the boundary layers. The relationship between the number of poles in the wall heat flux and the number of zero-crossing points is identified. The difference in the results of the prescribed wall temperature case and the prescribed wall heat flux case is analyzed. Results given in this paper provide a rare closed form analytical solution to the entire unsteady NS equations, which can be used as a benchmark problem for numerical code validation.

Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System

This paper proposes a novel tuning design of proportional integral derivative (PID) controller via an improved kidney-inspired algorithm (IKA) with a new objective function. The main objective of the proposed approach is to optimize the transient response of the AVR system by minimizing the maximum overshoot, settling time, rise time and peak time values of the terminal voltage, and eliminating the steady state error. After obtaining the optimal values of the three gains of the PID controller (KP, KI, and KD) with the proposed approach, the transient response analysis was performed and compared with some of the current heuristic algorithms-based approaches in literature to show the superiority of the optimized PID controller. In order to evaluate the stability of the automatic voltage regulator (AVR) system tuned by IKA method, the pole/zero map analysis and Bode analysis are performed. Finally, the robustness analysis of the proposed approach has been carried out with variations in the parameters of the AVR system. The numerical simulation results demonstrated that the proposed IKA tuned PID controller has better control performances compared to the other existing approaches. The essence of the presented study points out that the proposed approach may successfully be applied for the AVR system.

A low-complexity tracker design for uncertain nonholonomic wheeled mobile robots with time-varying input delay at nonlinear dynamic level

A low-complexity design problem of tracking scheme for uncertain nonholonomic mobile robots is investigated in the presence of unknown time-varying input delay. It is assumed that nonlinearities and parameters of robots and their bounds are unknown. Based on a nonlinear error transformation, a tracking control scheme ensuring preassigned bounds of overshoot, convergence rate, and steady-state values of a tracking error is firstly presented in the absence of input delay, without using any adaptive and function approximation mechanism to estimate unknown nonlinearities and model parameters and computing repeated time derivatives of certain signals. Then, we develop a low-complexity tracking scheme to deal with unknown time-varying input delay of mobile robots where some auxiliary signals and design conditions are derived for the design and stability analysis of the proposed tracking scheme. The boundedness of all signals in the closed-loop system and the guarantee of tracking performance with preassigned bounds are established through Lyapunov stability analysis. The validity of the proposed theoretical result is shown by a simulation example.

Predesignated fault-tolerant formation tracking quality for networked uncertain nonholonomic mobile robots in the presence of multiple faults

This paper presents a fault-tolerant formation tracking (FTFT) scheme ensuring predesignated bounds of overshoot, convergence rate, and steady-state values of distributed formation errors for networked nonholonomic mobile robots in the presence of unexpected multiple actuator and system faults. It is assumed that (i) nonlinearities and multiple faults of follower models and their bounds are unknown, and (ii) the time-varying posture information of the leader robot is accessible to only a small fraction of follower robots under directed networks. A continuous local controller for each follower is designed without utilizing any adaptive and function approximation mechanism to compensate for unexpected actuator and nonlinear system faults and computing repeated time derivatives of certain signals. Compared with the related results in the literature, this feature enables the proposed FTFT scheme to be implementable with remarkably low complexity. Theoretical and simulation verifications of our control strategy guaranteeing that the distributed FTFT errors remain within preassigned bounds regardless of the occurrence of unexpected faults are studied in a rigorous manner.

Low-Dimensional Modeling of Transient Two-Phase Flow in Pipelines

Presented are reduced-order models of one-dimensional transient two-phase gas–liquid flow in pipelines. The proposed model is comprised of a steady-state multiphase flow mechanistic model in series with a transient single-phase flow model in transmission lines. The steady-state model used in our formulation is a multiphase flow mechanistic model. This model captures the steady-state pressure drop and liquid holdup estimation for all pipe inclinations. Our implementation of this model will be validated against the Stanford University multiphase flow database. The transient portion of our model is based on a transmission line modal model. The model parameters are realized by developing equivalent fluid properties that are a function of the steady-state pressure gradient and liquid holdup identified through the mechanistic model. The model ability to reproduce the dynamics of multiphase flow in pipes is evaluated upon comparison to olga, a commercial multiphase flow dynamic code, using different gas volume fractions (GVF). The two models show a good agreement of the steady-state response and the frequency of oscillation indicating a similar estimation of the transmission line natural frequency. However, they present a discrepancy in the overshoot values and the settling time due to a difference in the calculated damping ratio. The utility of the developed low-dimensional model is the reduced computational burden of estimating transient multiphase flow in transmission lines, thereby enabling real-time estimation of pressure and flow rate.

A Study on Influence of System Parameters on Servo Pneumatic System and Multi-Response Optimization Using Taguchi – Grey Methodology

Servo pneumatics is a mechatronic approach that enables accurate position control of pneumatic drives with high speed. Simulation model of the servo pneumatic system with fuzzy PD controller has been created in Matlab-Simulink software using nonlinear mathematical model of the system. The influence of supply pressure and size of the cylinder on the positioning accuracy and speed has been studied. It is observed that the supply pressure is the most influencing factor in positioning accuracy and speed compared to the size parameters of the cylinders. Further a multi-response optimization of the system parameters minimize settling time, overshoot and ITAE (Integral of time-weighed absolute error) values has been carried out using Taguchi based Grey relational analysis methodology. The optimal system characteristics have been observed when supply pressure is 0.2 MPa, diameter of the cylinder is 0.05 m and length of the cylinder is 0.15 m.

Neuromorphic Multiple-Fault Diagnosing System Based on Plant Dynamic Characteristics

In many cases, multiple-fault diagnosis of plant-wide systems based on steady-state data is impossible. To solve this problem, a new diagnosis strategy based on neural networks has been proposed. In the suggested framework, the neural network is used as the diagnoser trained by a hybrid set of steady and dynamic characteristic data of the system. The dynamic characteristic data include overshoot and undershoot values of measured variables and their corresponding occurrence times. To evaluate its performance, the proposed scheme was used in the diagnosis of the concurrent faults of the Tennessee Eastman (TE) process. Various combinations of concurrent faults were considered in this assessment. The results indicate the generality, flexibility, and accuracy of the proposed algorithm such that it is capable of diagnosing various combinations (from single to sextuple) of simultaneous faults, whereas the other diagnosing methods used for the TE process are capable of distinguishing at most three simultaneous faults.

OPTIMAL CONTROL ALGORITHMS FOR SECOND ORDER SYSTEMS

Proportional Integral Derivative (PID) controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain good settling time, rise time and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances. Remarkable findings are obtained through the use of Artificial Intelligence techniques as Fuzzy Logic, Genetic Algorithms and Neural Networks. The combination of these theories can give good results in terms of settling time, rise time and overshoot. In this study, suitable controllers able of improving timing performance of second order plants are proposed. The results show that the PID controller has good overshoot values and shows optimal robustness. The genetic-fuzzy controller gives a good value of settling time and a very good overshoot value. The neural-fuzzy controller gives the best timing parameters improving the control performances of the others two approaches. Further improvements are achieved designing a real-time optimization algorithm which works on a genetic-neuro-fuzzy controller.