Performance Analysis Of Controller Research Articles

Performance Analysis of Chemotaxis-Inspired Stochastic Controllers for Multi-Agent Coverage

In this study, we analyze the performance of stochastic coverage controllers inspired by the chemotaxis of bacteria. The control algorithm of bacteria to generate the chemotaxis switches between forward movement and random rotation based on the difference between the current and previous concentration of a chemical. The considered coverage controllers mimic this algorithm, where bacteria and the chemical concentration are regarded as agents and the achieved degree of coverage, respectively. Because the coverage controllers operate similar to the control algorithm of bacteria, they are potentially suitable for molecular robots. Molecular robots, which consist of biomolecules, are recognized as a key component in the development of future medical systems based on micro-robots working inside the human body. However, the performance of the controllers has not yet been analyzed, and no theoretical guarantee of coverage completion has been provided. We address this problem by determining whether a performance index that quantifies the achieved degree of coverage increases over time for the feedback system. We first show that the performance index is characterized by the distance between agents under certain conditions. Using this result, we prove that the performance index increases with probability 1 under some conditions although the controllers are stochastic. This provides partial evidence for coverage completion, which makes the controllers more reliable. The analysis result is validated by numerical experiments.

Control Strategy and Performance Analysis of Electrochemical Energy Storage Station Participating in Power System Frequency Regulation: A Case Study of the Jiangsu Power Grid

Electrochemical energy storage stations (EESSs) have been demonstrated as a promising solution to mitigate power imbalances by participating in peak shaving, load frequency control (LFC), etc. This paper mainly analyzes the effectiveness and advantages of control strategies for eight EESSs with a total capacity of 101 MW/202 MWh in the automatic generation control (AGC) in the power system of the Jiangsu power grid. Firstly, an adaptive tracking strategy for electricity quantity that considers the state of charge (SOC) of EESSs is proposed to calculate the baseline power of the EESS participating in AGC. This strategy can simultaneously coordinate different time scale application requirements, such as peak shaving and LFC. Then, an adaptive strategy for regulation requirement allocation among AGC control groups with EESSs that considers different area regulation requirements (ARRs) is proposed to calculate the regulation power of EESS participating in AGC. This strategy can realize the balance transfer of fast and slow regulation capacity, ensure the complementary advantages of various frequency regulation resources and improve the dynamic regulation performance of the control area. Finally, the proposed strategy is validated via a test system to confirm its effectiveness and advantages, as well as via a quantitative analysis on the improvement of the control performance standard (CPS) of the Jiangsu power grid with the participation of EESSs in AGC.

Performance Analysis and Improvement of PI-Type Current Controller in Digital Average Current Mode Controlled Three-Phase Six-Switch Boost PFC Rectifier

In this article, the performance of the proportional–integral-type (PI-type) current controller in the digital average current mode (ACM) controlled three-phase six-switch (3ph-6s) boost PFC rectifier is analyzed with the consideration of the effect of the dead time, the time delays, and the dc offsets of the sampled input voltages/currents. Current control model is established to analyze the effect of the time delays and the dead time on the inductor currents. Analysis results show that both the time delays and the dead time lead to the phase shift of the inductor currents. The design principle of the current controller to suppress the negative effects of the time delays and the dead time on the phase of the inductor currents is given, and the PI-type current controller is found to considerably restrain the negative effects of the time delays and the dead time. However, in the traditional ACM control scheme with the PI-type current controller, the dc offsets of the sampled input voltages/currents lead to serious inductor current distortion. The current distortion is discussed, and the average line current control scheme is proposed to eliminate it. The analysis results are verified by simulation and experimental results of a 4-kW prototype.

Contact performance analysis of pressure controller's sealing interface in deep in-situ pressure-preserved coring system

The sealing performance of contact interfaces plays the most important role in the design and operation of the in-situ pressure-preserved coring system. To meet the demand of ultra-high pressure-retained coring for oil and gas exploration in deep reservoirs, a quantitative analysis of the contact mechanical behavior of the pressure controller was performed. Based on the micro-contact theory of rough surfaces, a three-dimensional numerical model of the rough contact interface between the valve cover and the valve seat was constructed, and the micro-contact behavior of the metal contact surfaces was comprehensively studied. The results show that the actual contact area of the valve interface increases with the increase of surface roughness before the critical contact point, but decreases after that. Compared with the real contact model with double rough surfaces, although the simplified hard-contact model with a single rough surface can reflect the micro-contact behavior of the rough surface to a certain extent, it cannot truly reveal the microchannel morphology between the sealing interfaces under pressure. Therefore, the realistic double-rough-surface model should be recommended to evaluate the sealing performance of coring tools, particularly for high pressure conditions. The material properties of valves have a significant effect on the contact characteristics of rough surfaces, which suggested that the actual contact area decreases with the increase of the elastic modulus of the contact material under the same loading conditions. The knowledge of this work could help to enhance the seal design of pressure controllers for in-situ pressure-preserved coring.

Leader–follower Stackelberg game oriented adaptive robust constraint-following control design for fuzzy exoskeleton robot systems

To comprehensively enhance the robust tracking performance, a leader–follower Stackelberg game oriented adaptive robust constraint-following control scheme has been proposed for a class of uncertain mechanical systems. In the proposed scheme, a fuzzy set-theoretic description represents the uncertainties (possibly fast time-varying), and an adaptive robust constraint-following control ensures the robust stability. With the fuzzy uncertainty description and control performance analysis, a leader–follower game theory is employed to obtain multiple optimal gains for the proposed control scheme. Further, the existence of these optimal parameters can be verified. The proposed approach is successfully applied to a lower limb exoskeleton (LLE) robot system for rehabilitation training.

Control Performance Analysis of Mining Ship Heave Compensation System Based on Fuzzy Logic Algorithm

With the depletion of land resources, demands for marine resources mining is increasing, the mining vessels which is known as one of the most important offshore equipment are widely concerned. The motions of wave surges in the marine environment will affect the operation of mining vessels, especially for the heave motion which will cause serious disturbances to the mining vessels during operation, and even the damage of the hull structure and related mining facilities. Hence, it is very necessary to compensate for the heave motion of the mining vessel, and a hydraulic cylinder-based active-passive integrated composite heave compensation system is designed in this paper. Firstly, the structural composition and working principle of the heave compensation system are introduced, and its mathematical model is also established. Secondly, the frequency domain and time domain analysis are carried out using AQWA software to obtain the heave displacement response of the ship under regular and irregular waves of six sea states as the desired compensation displacement. Finally, the controller of the active-passive heave compensation system is designed, and a fuzzy logic control strategy based on Mamdani type is proposed, and the control performance is analyzed. The results show that the accuracy of the fuzzy logic control algorithm is better than the traditional PID control algorithm, and the laws and methods of PID adjustment are obtained, which proves that the fuzzy logic control algorithm has obvious advantages for engineering applications.

Performance analysis of multistage PID controller for frequency regulation of multi microgrid system using atom search optimisation

Due to the presence of unpredictable renewable energy sources, the frequency control problem is a complex task in multi microgrid (MMG) systems. This research work recommends an atom search optimisation (ASO)-based multistage proportional–integral–derivative (M-PID) controller for frequency control of the MMG system under random and stochastic environments. The studied MMG system is a combination of photovoltaic, wind turbine and diesel engine generators along with diverse energy storage devices such as battery energy storage system and flywheel energy storage system. A comparative study with genetic algorithm and particle swarm optimisation is done to validate the effectiveness of the proposed technique. This prospective analysis is validated in OPAL-RT to check the practicability of this research.

Multi-objective model predictive control with gradient eigenvector algorithm

Multi-objective model predictive control (MMPC) is an effective method to solve the problem of nonlinear systems with multiple conflicting control objectives. However, the MMPC method usually suffers from the challenge of high computational cost for the determining the optimal objective weights with the process of transforming multiple objectives into a single objective. For low computational cost, an MMPC method with gradient eigenvector algorithm (MMPC-GEA) for nonlinear systems is proposed to comprehensively deal with multiple conflicting control objectives. The proposed MMPC-GEA in the framework of MMPC is composed of a fuzzy neural network (FNN) identifier and a receding optimization algorithm. For the proposed MMPC-GEA, FNN with an adaptive learning algorithm is devised to capture the nonlinear characteristic of systems. Moreover, a gradient eigenvector algorithm (GEA) is designed to gain the optimization solution of the control objectives for nonlinear systems. Specifically, GEA can reduce the computationally demanding by avoiding the determination of the objective weights. Furthermore, the stability and control performance analysis of the MMPC-GEA scheme is provided. Finally, the effectiveness of the proposed MMPC-GEA approach is demonstrated using a numerical simulation and wastewater treatment process.

A Novel Fractionalized PID controller Using The Sub-optimal Approximation of FOTF

In the last two decades, fractional calculus has been rediscovered by scientists and engineers and applied in an increasing number of fields, namely in the area of control theory. Recently, many research works have focused on fractional order control (FOC) and fractional systems. It has proven to be a good mean for improving the plant dynamics with respect to response time and disturbance rejection. In This work we use the Sub-optimal Approximation of fractional order transfer function to design the parameters of PID controller and we study the performance analysis of fractionalized PID controller over integer order PID controller.

Performance Analysis of Effective Controller for Active Power Filter using PUC5 Inverter for Improving Power Quality

Performance Analysis of Effective Controller for Active Power Filter using PUC5 Inverter for Improving Power Quality

Cascade adaptive optics: contrast performance analysis of a two-stage controller by numerical simulations

The contrast performance of current extreme adaptive optics (XAO) systems can be improved by adding a second AO correction stage featuring its own wavefront sensor (WFS), deformable mirror (DM), and real-time controller. We develop a dynamical model for such a cascade adaptive optics (CAO) system with two stages each controlled by a standard integrator and study its control properties. We study how such a configuration can improve an existing system without modifying the first stage. We analyze the CAO architecture in general and show how part of the disturbance is transferred from low to high temporal frequencies with a nefarious effect of the second stage integrator overshoot and suggest possible ways to mitigate this. We also carry out numerical simulations of the particular case of a first stage AO using a Shack–Hartmann WFS and a second stage AO with a smaller DM running at a higher framerate to reduce temporal error. In this case, we demonstrate that the second stage improves imaging contrast by one order of magnitude and shortens the decorrelation time of atmospheric turbulence speckles by even a greater factor. The results show that CAO presents a promising and relatively simple way to upgrade some existing XAO systems and achieve improved imaging contrasts fostering a large number of science case including the direct imaging of exoplanets.

Event-triggered adaptive fuzzy control for automated vehicle steer-by-wire system with prescribed performance: Theoretical design and experiment implementation

Steer-by-wire (SbW) systems substitute the typical mechanical linkage between the steering wheel and the front wheel with electromechanical actuators, resulting in that the steering performance of SbW systems depends on the control of electromechanical actuators. To guarantee the transient and steady-state performance of SbW systems, this paper proposes an event-triggered adaptive fuzzy control for the SbW system subject to the unavailable steering angular velocity, the time-varying disturbance, and the limited communication resources. First, to solve the problem of uncertainty modeling and external interference, an interval type-2 fuzzy logic system (IT2 FLS) and a disturbance observer are used to approximate the unknown SbW system dynamics and disturbance, respectively. Second, considering the angular velocity of the front wheels is difficult to measure, an adaptive observer is developed to estimate the steering angular velocity. The observation error is proved by the Lyapunov theory to converge in finite time. Third, to guarantee the transient and steady-state performance of the SbW system, this paper develops an output feedback controller for the automated vehicles based on event-triggered control (ETC) and prescribed performance control (PPC). Theoretical analysis proves that the tracking error can converge to a preset range within the set time, and the communication data between the controller and the actuator is reduced. Finally, simulation and experiment verify the effectiveness and superiority of the proposed method. From the analysis of the estimation performance, the designed observer has strong adaptability, which can ensure better observation accuracy even if the system has uncertainty. From the analysis of control performance, the proposed controller can guarantee the output trajectory tracking performance attributes (maximum overshoot, convergence time, maximum steady-state error). More specifically, in the experiment, the tracking error can converge to within 0.075 rad in 5 s. Additionally, the RMSE of the experimental results of the designed method is 44.7% higher than that of the output-feedback adaptive neural controller. From the perspective of communication data, the control signal transmitted to the motor driver is effectively saved by 19.3 %.

Performance analysis and enhancement of brain emotion-based intelligent controller and its impact on PMBLDC motor drive for electric vehicle applications

ABSTRACT Growing awareness of electric vehicles insists on the necessity of Permanent Magnet Brushless Direct Current Motor (PMBLDCM) worldwide. This paper involves building a simulation model of the complete PMBLDCM drive system using Matlab/Simulink to control the speed and Torque. Using the Simulink model, speed parameters with various controllers of the drive system are studied and analyzed. The conventional PI controller is capable of controlling the speed of the PMBLDC motor. H1owever, it cannot give assurance of the stability of the motor throughout the load variation. In a speed loop, Improved Brain Emotional Learning Based Intelligent Controller (IBELBIC) is proposed in this paper. The proposed IBELBIC-based PMBLDC motor drive system with a rating of 3 phase, 30 V, 400 W, 3000 RPM is implemented using Spartan 3 Field Programmable Gate Array (FPGA) from Xilinx. This paper presents an IBELBIC design for enhancing the speed performance of the drive system at various set speeds and different load conditions of 1.2 Nm load, 0.6 Nm load, and no load. The proposed PMBLDCM drive system is realized with the help of a Very high speed integrated circuit Hardware Description Language (VHDL) programming algorithm of digital Pulse Width Modulation (PWM) generator topology. Various test cases are evaluated under different operating conditions to demonstrate the learning capability and the applicability of the proposed controller. In this paper, simulation validation is done using hardware setup, and experimental results are monitored on a computer using a customized program developed using LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench). Instead of a Data Acquisition (DAQ) card, the Virtual Instrument Software Architecture (VISA) tool of LabVIEW software is used in this work and results in cost minimization of the experimental setup.

Robust sample-based model predictive control of a greenhouse system with parametric uncertainty

Achieving optimal resource use efficiency is a key challenge in modern greenhouse production systems. Optimal performance in terms of crop yield and resource efficiency can in theory be achieved via optimal control. Standard optimal controllers are not designed to deal with uncertainty, whereas considerable model prediction errors occur due to the mismatch between the model and the real system. This paper explores the relation between parametric uncertainty, and performance with respect to crop yield, CO2 demand, ventilation demand, and heating energy. This is done using the following steps 1) extension of an existing controller model with parametric uncertainty, 2) design of a sample-based robust model predictive controller and 3) analysis of control performance under increasing parametric uncertainty. The results predict that control performance is significantly sensitive to parametric uncertainty. A relative parameter uncertainty of 20%, reduced crop yield with 11% compared to the case without uncertainty. Furthermore, a 20% uncertainty decreased CO2 demand with 80%, whereas it increased ventilation demand with 96%, and increased heating energy demand with 90%.

Design and Performance Analysis of Hybrid controller for Self Tuning Filter Based Solar Integrated UPQC

Design and Performance Analysis of Hybrid controller for Self Tuning Filter Based Solar Integrated UPQC

Performance Analysis of Sliding Mode Controller for the Matrix Converter Based Dynamic Voltage Restorer to Mitigate the Voltage Sag in Distribution System

Performance Analysis of Sliding Mode Controller for the Matrix Converter Based Dynamic Voltage Restorer to Mitigate the Voltage Sag in Distribution System

Comparative performance analysis of intelligent controllers for solar tracking system

Solar Energy is the cleanest, cheapest and the most abundant form of renewable energy source that could complement the conventional fossil fuels but the continuous change in the position of the sun relative to earth reduces the power produced by it. In order to overcome this problem, solar tracking system are used to increase the efficiency of the photo voltaic panel. The conventional PID controllers are used for controlling linear and negligible lag system. For controlling non linear system the conventional controllers does not work effectively, therefore for such system intelligent control techniques are needed. This paper elucidates the performance comparative analysis of three intelligent controllers based on Artificial Neural Network which are Model Predictive Controller, Nonlinear Auto Regressive Moving Average (NARMA-L2) Controller and Adaptive-Network-Based Fuzzy Inference System (ANFIS) Controller. The simulation of the above controllers are done using MATLAB/ SIMULINK.

Analysis of postural control and muscle function performance of older adults participating in a multicomponent exercise program in primary health care

Objectives: This cross-sectional study aimed to investigate (1) postural control performance in different postural tasks and (2) muscle strength and power of the hip, knee, and ankle of active vs inactive older adults. Methods: The sample consisted of 61 healthy community-dwelling older adults, classified into 2 groups: active, consisting of participants of a multicomponent exercise program offered through the Exercise Orientation Service; and inactive. Participants were considered physically active/inactive in the past 3 months. Postural control was assessed using a force plate in 8 postural tasks. Muscle function was evaluated using an isokinetic dynamometer. T-tests were used to compare clinical characteristics between the groups. ANCOVA and MANCOVA were used to compare differences in variables of postural control and muscle function. Results: Active participants had higher levels of physical activity, clinical balance, and quality of life than inactive participants. The active group had lower values for area (center of pressure) than the inactive group under the following conditions: bipedal stance on an unstable surface with eyes open and with eyes closed, and semi-tandem stance on an unstable surface with eyes open. The active group showed greater muscle power, with higher mean power values for hip abduction and adduction, knee extension, and knee flexion and shorter time to peak torque for hip adduction and ankle dorsiflexion than the inactive group. Conclusions: Multicomponent exercise programs delivered in primary health care settings contributed to improving postural control and muscle power in this sample of older adults, which can potentially help prevent falls and improve quality of life.

Dynamic Event-Triggered Scheduling and Platooning Control Co-Design for Automated Vehicles Over Vehicular Ad-Hoc Networks

This paper deals with the co-design problem of event-triggered communication scheduling and platooning control over vehicular ad-hoc networks (VANETs) subject to finite communication resource. First, a unified model is presented to describe the coordinated platoon behavior of leader-follower vehicles in the simultaneous presence of unknown external disturbances and an unknown leader control input. Under such a platoon model, the central aim is to achieve robust platoon formation tracking with desired inter-vehicle spacing and same velocities and accelerations guided by the leader, while attaining improved communication efficiency. Toward this aim, a novel bandwidth-aware dynamic event-triggered scheduling mechanism is developed. One salient feature of the scheduling mechanism is that the threshold parameter in the triggering law is dynamically adjusted over time based on both vehicular state variations and bandwidth status. Then, a sufficient condition for platoon control system stability and performance analysis as well as a co-design criterion of the admissible event-triggered platooning control law and the desired scheduling mechanism are derived. Finally, simulation results are provided to substantiate the effectiveness and merits of the proposed co-design approach for guaranteeing a trade-off between robust platooning control performance and communication efficiency.

Control Performance Analysis of Centralized Control System in the Seimei Telescope

Control Performance Analysis of Centralized Control System in the Seimei Telescope