Reduced Settling Time Research Articles

Evolutionary optimization of sliding mode controller for level control system

This paper accords the level control of single-input-single-output (SISO) level control system based on the fusion of sliding mode control (SMC) and evolutionary techniques or bio-inspired techniques. The non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO) are considered as two evolutionary techniques. Here, a comparative analysis of performances of an optimal proportional–integral (PI) controller, proportional–integral–derivative (PID) controller, conventional SMC, NSGA-II based tuned SMC and SMC parameter tuning using MOPSO algorithm has been carried out through MATLAB/SIMULINK. The objective functions, integral absolute error (IAE), integral squared error (ISE) and an integration of weighted objective function aggregated approach of the error performance indices, IAE and ISE are considered. Realistic conditions are used in a plant for testing the robustness of controller. The stability of the controller is successfully obtained which satisfies the Lyapunov stability criteria. Reduction in long settling time with tiny magnitude variations about an equilibrium point is achieved using bio-inspired techniques. The simulation as well as experimental results reveal that SMC parameter tuning based on NSGA-II algorithm gives a better performance as compared to the other design strategies.

A new self-adjusting PI controller for power control in a wind turbine generator

PurposeThe purpose of this paper is to propose a novel self-adjusting proportional integral (SA-PI) controller, for controlling the active and reactive power of permanent magnet synchronous generator (PMSG) when subjected to variable wind speed and parameter variations.Design/methodology/approachThe proportional and integral gains of the proposed SA-PI controller are based on tan-hyperbolic function and adjust themselves automatically within pre-fixed limits according to the error occurring during transient situations.FindingsThe proposed SA-PI controller is able to evade the problems usually encountered while using a constant gain PI controller, such as lack of robustness, adaptability and a wide range of operation. It also damps out system oscillations faster with reduced settling time and fewer overshoots.Originality/valueSimulation results and comparative studies with conventional PI controller and the differential evolution–optimized PI (DE-PI) controller reveal the effectiveness of the proposed control scheme. MATLAB is used to perform the simulation studies.

A Rapid Dynamic Positioning Method for Settling Time Reduction Through a Macro–Micro Composite Stage With High Positioning Accuracy

A macro–micro composite precision positioning stage is mainly used in microelectronics manufacturing to achieve high-velocity and high-precision positioning. The residual vibration caused by high-speed macromotion will prolong the settling time and influence the working efficiency. This paper proposes a rapid dynamic positioning (RDP) method to quickly reduce the settling time of a macro–micro positioning stage by employing a designed spring-piezoelectric microstage. The main points of the RDP method are that it can start up the microstage at appropriate moment with proper extension to work against the macromotion vibration. Once the stage vibration amplitude is reduced to the piezoelectric element stroke limit, the micromotion is actuated to approach its final position. In this study, the start-up conditions and extension amount of the piezoelectric element were determined for implementing the RDP method. The feasibility of the method was clarified through theoretical analysis, including dynamic modeling, natural frequency analysis, and a vibration reduction and error compensation analysis. The experimental work was carried out, and the results validated the effectiveness of the RDP method in settling time reduction at different movements. With the assistance of the RDP method, the macro–micro high-speed, large-stroke stage can achieve an effective settling time reduction without sacrificing its accuracy.

Implementing Fuzzy Logic Controller and PID Controller to a DC Encoder Motor – “A case of an Automated Guided Vehicle”

It becomes essential to run AGV at a constant speed or RPM in the plant to reduce downtime and lead time. Fuzzy logic controller and PID controller are applied to achieve constant RPM in AGV. AGV contains DC brushed motor with encoder, motor driver, microcontroller and battery. Encoder gives feedback to microcontroller in the form of shaft position. Microcontroller reduces error in the system based on the parameters defined by the algorithms. The first phase of the paper gives brief information about the hardware, software and the algorithms. In the second phase of the paper, methodology for implementing the algorithm to the system is shown. In the final phase of the paper, results and discussions are mentioned based on the applied algorithms. Comparison between PID controller and fuzzy PID controller is also shown. Ziegler-Nichols Algorithms is used to find PID parameters. MATLAB simulink and fuzzy logic tool box are used for simulation. Arduino Microcontroller is used to accept the feedback given by the encoder and to control the speed of motor. In a nut shell, these control strategies help AGV to run at a constant RPM with reduced settling time, steady state error and overshooting.

Landsman Converter Based Particle Swarm Optimization Technique

This paper proposes a novel control technique for landsman converter using particle swarm optimization. The controller parameters are optimized by pso algorithm,the proposed algorithm is compared with pid controller and the comparative results are presented. Simulation results shows the dynamic performance of pso controller. landsman converter reduction in output voltage ripple in the order of mV along with reduced settling time as compared to the conventional pid controller . The simulated results are executed in MATLAB/SIMULINK.

A hybrid chemical reaction-particle swarm optimisation technique for automatic generation control

In this paper, a novel hybrid chemical reaction optimisation and particle swarm optimisation (HCROPSO) optimised PI controller has been proposed for automatic generation control (AGC) problem. A two area reheat thermal-hydro system with non-linearities such as governor dead band (GDB), generation rate constraints (GRC) and boiler dynamics is considered. The parameters of PI controller are optimised employing HCRO-PSO technique. The superiority of the proposed approach is shown by comparing the results with PSO, CRO and fuzzy logic control (FLC). Improvement in system performance is obtained in terms of reduced settling time, overshoot and undershoot of frequency deviation and tie line power deviation with proposed controller. Investigation is performed with variation in inter rate and inertia weight parameters. Sensitivity analysis is performed by varying the system parameters and generation rate constraints from their nominal values. Analysis reveals that HCRO-PSO optimized PI gains obtained at nominal are quite robust and need not be reset for wide changes in system parameters.

Intelligent control strategy in the islanded network of a solar PV microgrid

In the islanded mode of MG network, due to the lack of inertia and under performance of PI based inverter control, variation in power and frequency level can be expected more during the transient conditions as compared to the grid connected mode. Thus, in this study, a Particle Swarm Optimization (PSO) algorithm with the proposed cost function was implemented in the Grid-support grid-forming (GsGfm) type Voltage Source Inverter (VSI) of the DG sources (solar PV and battery unit) for the islanded photovoltaic (PV) based MG model (built in Matlab-Simulink software environment) to reduce the variation in power and frequency level. The islanded MG model was also implemented with a reverse droop based on virtual impedance control strategy for the VSI and power management control strategy to ensure better power sharing among DG sources with regulation of frequency level and power balance with co-ordinated control operation of DG sources. Implementation of PSO based intelligent control strategy for the inverters of DG units, showed substantial improvement in the performance of controller in terms of reduced settling time and overshoot in power level along with the significant reduction of the power variation and frequency variation during the transient conditions (change in load and change in solar irradiance of PV units). Also proposed PSO control strategy ensured the frequency level to be within the acceptable operating range (Australian network standard) in the islanded MG network.

Tracking Control and Vibration Reduction of Flexible Cable-Suspended Parallel Robots using a Robust Input Shaper

The control of flexible cable-driven parallel robots usually requires not only the feedback from the joints, but the feedback from the end-effector pose or cable tension. This paper presents a new approach for reducing the vibration of flexible cable-suspended robots, using only the feedback from the joints. First, the dynamic equations of a 6DOF cable-suspended parallel robot with elastic cables were derived by Gibbs-Appel formulation. Subsequently, three different control approaches were investigated based on the computation load and required sensors. As a result, a feedback linearization method based on the rigid model of the system was selected. In order to reduce the vibration, a robust input shaping method was employed to prevent excitation of natural modes. Simulation results revealed that the proposed approach leads to a noticeable vibration and settling time reduction in cases of low and high cable stiffness, respectively. Moreover, another simulation compares the presented approach with a composite controller, which uses the feedbacks from the end-effector and actuators. Thereafter, the performance of the approach in vibration reduction is quantitatively shown. Finally, experimental validation of the approach was accomplished by frequency analysis of the vibration obtained from the IMU sensor, attached to the end-effector.

A 0.26-nJ/node, 400-kHz Tx Driving, Filtered Fully Differential Readout IC With Parasitic RC Time Delay Reduction Technique for 65-in $169 \times 97$ Capacitive-Type Touch Screen Panel

This paper presents a readout method and circuit for large, capacitive-type touch-screen panels (TSPs). Despite the considerable amount of RC time delay of large-area TSPs, the proposed readout method with a receiver (Rx) input seriescapacitor improves the settling speed of signals transferred from the transmitter (Tx) to the Rx, by reducing the RC time delay. Combined with the Rx input series-capacitor, a capacitive-input fully differential filtered charge integrator effectively cancels out the display noise and reduces the self-noise in capacitive-type TSPs. The proposed Rx circuit was implemented using 0.35-μm CMOS. Using a 65-in metal-mesh TSP with 169 Tx and 97 Rx electrodes mounted on a liquid-crystal display for testing, the proposed readout method achieved 65% reduction of signal settling time within an accuracy of ≥3τ for the longest signal path of the TSP. Using the RC time delay reduction technique, the Tx driving frequency could be boosted by as much as 400 kHz, and the measured signal-to-noise ratio of 43.5 dB was obtained for finger touch at a 120-Hz scan rate, resulting in a figureof-merit of 0.26 nJ/node, while the overall power consumption was 76 mW.

Design and performance analysis of robust conventional power system stabiliser using cuckoo search algorithm

This article presents robust design of conventional power system stabiliser (CPSS) by using metaheuristic cuckoo search algorithm (CSA). The free coefficients of the CPSS are optimised using CSA connected with a single-machine infinite-bus (SMIB) power system at nominal operating condition. The performance of such optimised controller (CSA-CPSS) is compared with the performance of well established H∞-based power system stabiliser (H∞-PSS) over a wide range of operating conditions of the SMIB power system. The superiority of the proposed CSA-CPSS is validated with least value of settling time and the performance indices as ITAE, IAE and ISE of speed response over the H∞-PSS. Moreover, the superiority is proved by eigenvalue plot for considered 209 plants as a fan-shaped structure in left side of s-plane with damping factor as more than 0.1. The performance of CSA-CPSS is also considered for the multimachine power system. The CSA-CPSS outperforms the CDCARLA-CPSS, BFOA-CPSS and SPEA-CPSS in terms of reduced settling time, overshoot and performance indices.

Design and performance analysis of robust conventional power system stabiliser using cuckoo search algorithm

This article presents robust design of conventional power system stabiliser (CPSS) by using metaheuristic cuckoo search algorithm (CSA). The free coefficients of the CPSS are optimised using CSA connected with a single-machine infinite-bus (SMIB) power system at nominal operating condition. The performance of such optimised controller (CSA-CPSS) is compared with the performance of well established H∞-based power system stabiliser (H∞-PSS) over a wide range of operating conditions of the SMIB power system. The superiority of the proposed CSA-CPSS is validated with least value of settling time and the performance indices as ITAE, IAE and ISE of speed response over the H∞-PSS. Moreover, the superiority is proved by eigenvalue plot for considered 209 plants as a fan-shaped structure in left side of s-plane with damping factor as more than 0.1. The performance of CSA-CPSS is also considered for the multimachine power system. The CSA-CPSS outperforms the CDCARLA-CPSS, BFOA-CPSS and SPEA-CPSS in terms of reduced settling time, overshoot and performance indices.

A novel approach for mitigating the effects of pre-rolling/pre-sliding friction on the settling time of rolling bearing nanopositioning stages using high frequency vibration

Nanopositioning stages are used for ultra-precise positioning in many different applications. Among the bearing options available for long-range nanopositioning stages, rolling bearings are the most cost effective. However, rolling bearing nanopositioning (RB-NP) stages are well known to take a long time to reach their target positions in point-to-point positioning tasks due to pre-rolling/pre-sliding friction. This paper presents vibration assisted nanopositioning (VAN) – a novel approach for reducing the settling time of RB-NP stages using high frequency vibration (aka dither). VAN synergistically combines the electromechanical design and control of RB-NP stages to mitigate pre-rolling/pre-sliding friction using dither, without jeopardizing positioning precision. It is shown in simulations to exhibit superior positioning performance and robustness compared to model-based friction compensation methods. Experiments carried out on a prototype stage incorporating the VAN approach show a 52% reduction of mean settling time, based on 50 trials, when compared to a case without VAN. Moreover, the heat and potential wear induced by dither are shown to be practically insignificant.

AN ALGORITHM FOR AUTOMATIC GENERATION CONTROL OF IRAQI POWER SYSTEM USING FUZZY LOGIC TECHNIQUE

This work proposes an algorithm based on Fuzzy Logic technique for the AGC of a power system controller to enhance the performance of the conventional controller during normal and abnormal condition (variation of load). The dynamic responses of Iraqi super grid network (400 kV) under normal and 10% step load increase (as a severe condition) to investigate using the fuzzy logic -PID controller and a conventional PID controller in MATLAB/SIMULINK environment. The obtained results show the proposal intelligent controller and have improved the dynamic response of the Iraqi grid, and at the same time, It is faster than the conventional PID controller in terms of reducing settling time, overshoot and oscillations.

Proportional-derivative linear quadratic regulator controller design for improved longitudinal motion control of unmanned aerial vehicles

This study investigates the longitudinal motion control of unmanned aerial vehicles through a simulation in MATLAB. The linear model of an unmanned aerial vehicle is applied to controllers to explicate the longitudinal motion of the unmanned aerial vehicle. The ideal performance for an unmanned aerial vehicle is to achieve the desired response instantly with 100% precision. However, currently available controllers need further improvements. Thus, a proportional-derivative linear quadratic regulator controller is developed and compared with a proportional-integral-derivative controller, a linear quadratic regulator controller, and a proportional linear quadratic regulator controller. The proportional-derivative linear quadratic regulator controller enhances the response of the system by reducing settling time by more than 95% compared with other available controllers. Additionally, the proportional-derivative linear quadratic regulator improves the root mean square error by almost 50% compared with the proportional linear quadratic regulator controller and improves rise time by almost 96% with reasonable overshoot.

Development of a magnetic coagulant based on Moringa oleifera seed extract for water treatment.

In this work, to evaluate the effectiveness of the coagulation/flocculation using a natural coagulant, using Moringa oleifera Lam functionalized with magnetic iron oxide nanoparticles, producing flakes that are attracted by an external magnetic field, thereby allowing a fast settling and separation of the clarified liquid, is proposed. The removal efficiency of the parameters, apparent color, turbidity, and compounds with UV254nm absorption, was evaluated. The magnetic functionalized M. oleifera Lam coagulant could effectively remove 90% of turbidity, 85% of apparent color, and 50% for the compounds with absorption at UV254nm, in surface waters under the influence of an external magnetic field within 30min. It was found that the coagulation/flocculation treatment using magnetic functionalized M. oleifera Lam coagulant was able to reduce the values of the physico-chemical parameters evaluated with reduced settling time.

Generalized Predictive Control of Temperature on an Atomic Layer Deposition Reactor

This brief establishes a closed-loop control system for a radiant heating atomic layer deposition (ALD) reactor using generalized predictive control (GPC). The GPC-based closed-loop control system can rapidly and precisely stabilize the temperature in the presence of external disturbances. Compared with the conventional open-loop control and the proportional–integral–differential control, the closed-loop GPC system enhances the processing efficiency between every ALD run by substantially reducing settling time with impact by external disturbances. The attenuated temperature fluctuation leads to more uniform thin-film morphologies that fulfill the technical requirements of ALD processes.

Reduction of Settling Time and Overshoot for Flyback Converter by Using Modern Optimization Based PI Controller Driven DC Servo Motor

In this study, a simple PI controller is presented for regulation of the output voltage of the DC to DC fly back converter driven DC Servo motor with constant frequency. Here a new PI control algorithm implemented in FPGA has been proposed for optimizing the PI parameters using PSO and ABC optimization techniques. A comparison has been made between the two optimization algorithms across different load and voltage variations and their effectiveness in reduction of overshoot and settling time of fly back converter in DC Servo motor drive have been evaluated.

Optimal Generation Control of Interconnected Power System Including DFIG-Based Wind Turbine

ABSTRACTThe impact of wind power with higher size of penetration becomes significant for frequency control problem due to its inconsistent nature and lack of frequency support from the wind turbine units. The frequency can be managed using enhanced control of inertia and droop characteristics. However, at very low and high speeds, the adjustment of pitch angle of wind turbine is necessary so that the aerodynamic power produced remains within the designed limits. This paper discloses the design of proportional integral (PI) control algorithm to adjust pitch angle of doubly fed induction generator (DFIG)-based wind turbine (WT) integrated with two-area-interconnected power system. Here, a heuristic gravitational search algorithm (GSA) is employed to optimize the gains of PI controllers used for pitch angle adjustment and governor speed control of wind turbine, frequency regulation, and tie-line power flow control. The influence of optimal gains by GSA is compared with genetic algorithm (GA) and ant colony optimization (ACO) approaches. Finally, the effectiveness of GSA-optimized controllers is demonstrated in terms of reduced settling time, overshoot, eigenvalues, and oscillations. The competency of proposed controller is also studied by considering the variation of wind power source from 10% to 40% in the power system and also the real-time physical constraints like generation rate, time delay, and governor deadband.

Analysis of Deadbeat Control for an Integer-N Charge-pump PLL

Abstract The conventional method to decrease the settling time of oscillators is to increase the bandwidth, which in turn results in an increase in the spur content, affecting the transient performance of the PLL. Even though several architectural variations have been suggested to reduce the lock time, a novel method to reduce the settling time is “Deadbeat control”, in which an additional system is implemented in feedback with the PLL. This method accomplishes the reduced settling time without any change in the design of the forward gain components. Before the implementation of the deadbeat control, the concepts of controllability and observability have to be satisfied for the PLL. In this particular work, these tests are carried out on an integer-N charge-pump PLL, and then the deadbeat control is verified. The settling time and the overshoot are deduced from the step-response of the PLL, by means of MATLAB simulation.

Design and implementation of fractional order PI<SUP align="right">λ</SUP>D<SUP align="right">μ</SUP> controller for thermal process using stability boundary locus

Fractional order control is a new technique that uses fractional order calculus in the control applications. By introducing the fractional terms in basic control equations, we can achieve more satisfactory results with high precision in the system response, like less overshoot, reduced settling time, less steady state error, etc. It gives better control over the operating region with the help of fractional terms. Initially, the range of system stability is determined based on a novel graphical method, stability boundary locus. This method is used for tuning the fractional order controller parameters, K p , K i and K d for the specified gain and phase margins. Stability of the system with controller is checked based on bode plot. This novel graphical method, stability boundary locus, in frequency domain uses less mathematical calculations and gives an idea about the system stability regions. Using this method, the gain and phase margin specification can be attained very easily without complex numerical analysis.