Gain Scheduling Research Articles

Research on a Passenger Aircraft Flight Control System Gain Scheduler Design

This paper employs the mathematical model of a passenger aircraft for the purpose of designing longitudinal flight control law to satisfy handling qualities assessment. Aircraft Rate Command Attitude Hold (RCAH) controllers are designed at the specific equilibrium points in the flight envelope by means of a state space pole placement design procedure. The handling qualities assessment of the aircraft is presented, based on which the gain scheduler is designed. The existing criteria are employed to assess the handling qualities of the aircraft augmented by the gain scheduler, including the Control Anticipation Parameter (CAP) and Neal and Smith. The augmented aircraft performs satisfactorily and meets the requirement of handling qualities.

Research on the Neal&Smith Criterion Application on Aircraft Flight Control System Handling Qualities Assessment

This paper utilized Neal&Smith criterion to quantify handling qualities of some aircraft augmented with Control and Stability Augmentation System (CSAS) over the flight envelop. Some aircraft mathematical model which augmented by longitudinal pitch Rate Command-Attitude Hold(RCAH) controller are employed. The aircraft handling qualities are described in terms of transfer functions of the pilot mathematical model, which includes a pilot’s neuromuscular delay, phase and gain compensation terms. If desirable closed loop dynamic performance can be obtained by the pilot mathematical model described by transfer function characteristics, then the satisfactory closed loop dynamic performance will also be achievable for the human pilot with decent workload. Consequently, the assessment results can be used to identify CSAS controller’s satisfactory effect domain, and furthermore, in aid of CSAS gain scheduling strategy design.

Speed Control and Torque Ripple Reduction of SRM Using Fuzzy Gain Scheduling PI Controller

Speed Control and Torque Ripple Reduction of SRM Using Fuzzy Gain Scheduling PI Controller

Event‐triggered and self‐triggered gain scheduling control of input constrained systems with applications to the spacecraft rendezvous

AbstractThis article studies event‐triggered and self‐triggered gain scheduling control design for semi‐global stabilization of input constrained linear systems. Using the parametric Lyapunov equation (PLE), a event‐triggered gain scheduling control, which can increase the convergence rate of the closed‐loop systems by designing a gain scheduling scheme and save the communication resources by building an event generator, is designed. In order to avoid continuously monitoring the system states, the self‐triggered gain scheduling control algorithms are also designed. The non‐occurrence of the Zeno phenomenon and the boundedness of the parameter in the PLE are proved. The impact of the parameter on the minimal inter‐event time is analyzed, which allows us to find easily a trade‐off between the inter‐event times and the control performance. Another advantage of the designed methods is that the controller is linear. Finally, the proposed control algorithms are applied to stabilize the spacecraft rendezvous control system and the numerical simulation result shows the efficacy of the control algorithms.

Adaptive Pitch Controller of a Large-Scale Wind Turbine Using Multi-Objective Optimization

This paper deals with the control problems of a wind turbine working in its nominal zone. In this region, the wind turbine speed is controlled by means of the pitch angle, which keeps the nominal power constant against wind fluctuations. The non-uniform profile of the wind causes tower displacements that must be reduced to improve the wind turbine lifetime. In this work, an adaptive control structure operating on the pitch angle variable is proposed for a nonlinear model of a wind turbine provided by FAST software. The proposed control structure is composed of a gain scheduling proportional–integral (PI) controller, an adaptive feedforward compensation for the wind speed, and an adaptive gain compensation for the tower damping. The tuning of the controller parameters is formulated as a Pareto optimization problem that minimizes the tower fore-aft displacements and the deviation of the generator speed using multi-objective genetic algorithms. Three multi-criteria decision making (MCDM) methods are compared, and a satisfactory solution is selected. The optimal solutions for power generation and for tower fore-aft displacement reduction are also obtained. The performance of these three proposed solutions is evaluated for a set of wind pattern conditions and compared with that achieved by a classical baseline PI controller.

A novel optimal firefly algorithm based gain scheduling proportional integral derivative controller for rotor spinning machine speed control

In advanced yarn production, the rotor spinning machine plays a significant role due to its low power consumption and high speed of yarn delivery. Nevertheless, if the speed of the machine exceeds from its desired level, the yarn output will go worsen. Therefore, in this paper, a novel optimal firefly algorithm based gain scheduling proportional-integral-derivative controller is proposed to regulate the speed of linear parameter varying based rotor spinning machine at the desired level. Here, the OFA is added to the GSPID controller for tuning the controller parameters. Consequently, Spline piecewise interpolation is newly developed to regulate the gain tuning parameters in high desired rate. The stability of the projected controller is synthesized by the combination of linear matrix variations with $$H_{\infty }$$ control. Moreover, the error percentage and the accuracy of the proposed system are optimized using OFA. The implementation of this projected work was done in the MATLAB R2018b platform. Furthermore, the simulation result of the developed control strategy is compared with other traditional control approaches and its efficiency measure has proved by gaining less computational time as 10 s, error rate as 0.0982%, and high accuracy as 92%.

Universal Control of Permanent Magnet Synchronous Motors with Uncertain Dynamics

This paper focuses on the universal control design of permanent magnet synchronous motors (PMSMs) with uncertain system dynamics. In vector control, classical proportional-integral (PI) controllers are used to control d-q axis currents and speed of the PMSM. This paper uses two control methods: conventional field-oriented vector control and simplified control. First, all the control gains are determined for numerous PMSMs with various power ratings using an empirical study and generalized mathematical expressions are derived for each of the gains. Then, these expressions are used for automatic gain calculation for various PMSMs with a wide power-rating range. In vector control, the control gains are determined using only the motor power ratings. In the simplified control, generalized control gain expressions are obtained using the number of pole pairs and the flux linkage. Compared to the vector control, the simplified control method provides much simpler generalized mathematical expressions. Validation is carried out in MATLAB/Simulink environment using various PMSMs from 0.2 HP to 10 HP, and results show accurate tracking of reference speed and d-q axis reference currents. Thus, the proposed gain scheduling approach is effective and can be used for self-commissioning motor drives.

Magnetic tweezers with magnetic flux density feedback control.

In this work, we present a single-pole magnetic tweezers (MT) device designed for integration with substrate deformation tracking microscopy and/or traction force microscopy experiments intended to explore extracellular matrix rheology and human epidermal keratinocyte mechanobiology. Assembled from commercially available off-the-shelf electronics hardware and software, the MT device is amenable to replication in the basic biology laboratory. In contrast to conventional solenoid current-controlled MT devices, operation of this instrument is based on real-time feedback control of the magnetic flux density emanating from the blunt end of the needle core using a cascade control scheme and a digital proportional-integral-derivative (PID) controller. Algorithms that compensate for a spatially non-uniform remnant magnetization of the needle core that develops during actuation are implemented into the feedback control scheme. Through optimization of PID gain scheduling, the MT device exhibits magnetization and demagnetization response times of less than 100ms without overshoot over a wide range of magnetic flux density setpoints. Compared to current-based control, magnetic flux density-based control allows for more accurate and precise magnetic actuation forces by compensating for temperature increases within the needle core due to heat generated by the applied solenoid currents. Near field calibrations validate the ability of the MT device to actuate 4.5 μm-diameter superparamagnetic beads with forces up to 25 nN with maximum relative uncertainties of ±30% for beads positioned between 2.5 and 40 µm from the needle tip.

Robust Controller And Industrıal Internet For The Industrıal Nonlınear Level Process

Automatic gain scheduling of PID controller gives monstrous yield reaction for controlling tank level away industrial application. This proposed strong controller furnishes tasteful yield reaction with least pinnacle overshoot, brisk settling time. The Industrial Internet of Things (IIoT) is generally used to interconnect accessible enterprises assets and give dependable, powerful and brilliant checking and control includes in process businesses. The proposed work outlines the use of IoT in a straight tank framework, checking and change set point and controller parameters from remote spots utilizing cloud administrations. In this paper, a basic straight tank exploratory setup is created and level in the direct tank framework is controlled utilizing PID controller. Utilizing IoT and electronic administration blynk, the information can be checked and dissected from any piece of the world at whenever. Set point and PID controller parameter of the straight tank framework can likewise be adjusted.

Identification and control using LSDP approach applied to the PT326 blower

The present work focuses on the control of the nonlinear system, the PT326 blower, using the LSDP (Loop Shaping Design Procedure) approach in the discrete case and the gain scheduling technique. First, the system’s behavior is described by defining two operating points. In each of these latter the system is described using the linear ARX (Auto Regressive model with Xternal inputs) model which we propose to identify its parameters using the least squares method. Then, for each operating point the LSDP approach is exploited to synthesize a local robust controller. Later, the global robust controller resulting from switching between the local robust controllers by exploiting the gain scheduling technique is used to control the nonlinear PT326 blower.

Auto-Tuning Control of Proton Exchange Membrane Water Electrolyzer With Self-Assessment and Gain Scheduling

Abstract Proton exchange membrane (PEM) electrolyzer can produce gases at the pressure suitable for direct storage into metal hydride cylinders, bypassing compressors, and other auxiliary components. For direct storage into metal hydride containers, hydrogen gas's pressure and flowrate must be well controlled. However, the PEM electrolyzer's time-variant and nonlinear dynamics call for an adaptive control to maintain its output performance. Therefore, in this paper, a model-free relay-feedback autotuning approach is proposed to tune a proportional-integral (PI) controller online. The controller determines the voltage supply to the electrolyzer to track a certain current setpoint, which corresponds to a constant hydrogen production rate. A gain scheduling approach is developed to pick up the right controller gain at different setpoints, minimizing the tuning frequency. A self-assessment algorithm is developed to determine the situations where the autotuner should activate to update the PI parameters, thus allowing the control system to be tuned autonomously. The autotuning PI control is successfully tested with a PEM electrolyzer setup. Experiment results showed that autotuner with gain scheduling could tune the controller parameters producing a desired transient behavior and is adaptive to the variations in setpoint and operating conditions.

Design and Implementation of Adaptive PID and Adaptive Fuzzy Controllers for a Level Process Station

This proposed work proposes the design and real-time implementation of an adaptive fuzzy logic controller (FLC) and a proportional-integral-derivative (PID) controller for adaptive gain scheduling that can be configured for any complex industrial nonlinear application. Initially, the open-loop test of the single-input single-output (SISO) system, with nonlinearities and disturbances, is conducted to represent the mathematical model of the process around a set of equilibrium points. The adaptive controllers are then developed and deployed by using the national instruments reconfigurable input/output data acquisition device (NI RIO), NI myRIO-1900, and the control parameters are adapted in real-time corresponding to the changes in the process variable. The resulting servo and regulatory performance of the controllers are compared in MATLAB® software. The adaptive fuzzy controller is deduced to be the better controller as it can generate the desired output with quicker settling times, fewer oscillations, and negligible overshoot.

Fuzzy PID Gain Scheduling Controller for Networked Control System

The use of a communication network in the closed loop control systems has many advantages such as remotely controlling equipment, low cost, easy to maintenance, efficient information transmission, etc. However, the Networked Control System (NCS) has many drawbacks, such as network-induce end-to-end time delay and packet loss, which lead to significant degradation in controller performance and may result in instability. Aiming at solving performance degradation in NCS, this paper propose to take the advantages and strength of the conventional Proportional-Integral-Derivative (PID), Fuzzy Logic (FL), and Gain Scheduling (GS) fundamentals to design a Fuzzy-PID like-Gain Scheduling (F-PID-GS) control technique, which has been proved to be effective in obtaining better performance. The True Time toolbox is used to establish the simulation model of the NCS. Ethernet as a communication network is simulated for different load conditions and random packet loss. The design approach is tested on a second order stepper motor. The results obtained show the effectiveness of the proposed approach in improving the overall system performance.

Analysis, Design, and Implementation of Multi-Quasi-Proportional-Resonant Controller for Thyristor-ControlledLC-Coupling Hybrid Active Power Filter (TCLC-HAPF)

Compared with the conventional active power filter, the thyristor-controlled <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> -coupling hybrid active power filter (TC <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> -HAPF) has a distinct characteristics of low dc-link operating voltage, which can lower the system and operational costs in the medium-voltage-level system. It also has a wider operational range than the conventional hybrid active power filter. Besides that, the TC <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> -HAPF can provide reactive, harmonic, and unbalanced powers compensation simultaneously. In this article, the modeling of the TC <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> -HAPF is investigated based on the linear control aspect. Then, the analysis, design, and implementation of a multi-quasi-proportional-resonant (MQPR) controller with gain scheduling for the TC <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> -HAPF will be proposed, which can automatically change the resonant gain between the inductive and capacitive loads operation to improve its compensation performances. The proposed controller can significantly reduce the TC <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> -HAPF steady-state current tracking errors and output current ripple. Finally, the simulation and experimental results are also provided to verify the effectiveness and performance of the MQPR controller for the TC <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> -HAPF in comparison with the hysteresis current controller and quasi-proportional-resonant (QPR) controller, which shows superior compensating performances.

Engineering of An Innovative Oral Scientific Communication Device: Case of the Doctoral Training Context

The use of a communication network in the closed loop control systems has many advantages such as remotely controlling equipment, low cost, easy to maintenance, efficient information transmission, etc. However, the Networked Control System (NCS) has many drawbacks, such as network-induce end-to-end time delay and packet loss, which lead to significant degradation in controller performance and may result in instability. Aiming at solving performance degradation in NCS, this paper propose to take the advantages and strength of the conventional Proportional-Integral-Derivative (PID), Fuzzy Logic (FL), and Gain Scheduling (GS) fundamentals to design a Fuzzy-PID like-Gain Scheduling (F-PID-GS) control technique, which has been proved to be effective in obtaining better performance. The True Time toolbox is used to establish the simulation model of the NCS. Ethernet as a communication network is simulated for different load conditions and random packet loss. The design approach is tested on a second order stepper motor. The results obtained show the effectiveness of the proposed approach in improving the overall system performance.

Design, Analysis, and Comparison of Control Strategies for an Industrial Robotic Arm Driven by a Multi-Level Inverter

In this article, we present the design and implementation of different control strategies for the position of a 2-Degree-of-Freedom (DoF) robotic arm, namely gain scheduling per trenches, gain scheduling by interpolation, adaptive control, and fuzzy logic. The first link of this robot is driven by an Alternating Current Brushless Permanent Magnet Motor (ACBPMM) through a three-phase multi-level inverter with 27 levels of voltage per phase. Thanks to the topologies offered by ACBPMMs and to the multi-level inverter, high commutation frequencies are reduced, as observed in the computer simulations. Additionally, to determine which proposed control strategies are the most suitable for an ACBPMM connected to a multi-level inverter, a comparative study on the performance of the controllers implemented for this robot is conducted.

Observer-based gain scheduling path following control for autonomous electric vehicles subject to time delay

This paper presents a novel observer-based gain-scheduling path following control algorithm for autonomous electric vehicles subject to time delay. Firstly, the lateral dynamic model of the autonomous electric vehicle is constructed by a polytope with four vertices, in which the issues of the time-varying longitudinal velocity and nonlinear tyre dynamics are accurately described. Secondly, taking the time delay encountered in the process of signal transmission into consideration, the observer-based path following controller is proposed by using easily measured vehicle states. In the algorithm, the observer and controller gains are gain scheduled according to the actual longitudinal velocity. Thirdly, based on Lyapunov stability theory, an appropriate Lyapunov–Krasovskii functional is constructed to derive sufficient conditions of the controller, which is effective to ensure the asymptotical stability of the closed-loop path following error system with a guaranteed performance. Specially, for ease of computation, the sufficient conditions of controller design are developed in terms of a set of linear matrix inequalities. Finally, numerical simulations are implemented to illustrate the efficiency and superiority of the proposed method in comparison with the existing method.

Adaptive Cruise Control With Gain Scheduling Technique Under Varying Vehicle Mass

Today, advanced driver-assistance systems (ADAS) come up with different abilities. One of them is the adaptive cruise control (ACC) system. The ACC system is a continuation of research on cruise control (CC) system, which integrates spacing control with the existing velocity control on the CC system. The vehicles with an ACC system guarantee traffic safety while at the same time ensure a well-driving sense. Many studies have demonstrated numerous control techniques applied as ACC controllers to accomplish uncertainty and perturbation issues. Nevertheless, most of the existing papers assumed the model vehicle dynamics as a linear time-invariant (LTI) system while designing the ACC controller. This paper proposed an ACC controller using the gain scheduling technique to deal with the model vehicle dynamics as a linear parameter varying (LPV) system. The passenger vehicle’s mass varies during ACC operation depending on how many passengers or loads on the vehicle’s trunks. Later, the vehicle’s mass is estimated by recursive least square (RLS) with a forgetting factor. Then, the disk margin is utilized to provide the high-level robustness at each operating or “frozen” point. The robustness performance will be analyzed using the worst-case gain metric while the uncertainty is modeled by integral quadratic constraints (IQC). The LPV system behavior, such as the rate vehicle’s mass, is also considered in the analysis. The effectiveness algorithm is validated through joint simulation between Matlab/Simulink and PreScan. The last, the comparison performance between gain scheduling and fixed gain ACC controller is evaluated.

Artificial Neural Network-Based Gain-Scheduled State Feedback Speed Controller for Synchronous Reluctance Motor

Abstract This paper focuses on designing a gain-scheduled (G-S) state feedback controller (SFC) for synchronous reluctance motor (SynRM) speed control with non-linear inductance characteristics. The augmented model of the drive with additional state variables is introduced to assure precise control of selected state variables (i.e. angular speed and d-axis current). Optimal, non-constant coefficients of the controller are calculated using a linear-quadratic optimisation method. Non-constant coefficients are approximated using an artificial neural network (ANN) to assure superior accuracy and relatively low usage of resources during implementation. To the best of our knowledge, this is the first time when ANN-based gain-scheduled state feedback controller (G-S SFC) is applied for speed control of SynRM. Based on numerous simulation tests, including a comparison with a signum-based SFC, it is shown that the proposed solution assures good dynamical behaviour of SynRM drive and robustness against q-axis inductance, the moment of inertia and viscous friction fluctuations.

Energy saving in batch distillation for separation of ternary zeotropic mixture integrated with vapor recompression scheme: dynamics and control

Abstract In this work, tight composition control and in parallel the operation is integrated with vapor recompression scheme (VRC) is proposed to achieve energy savings and maximum product at a specified high purity for the separation of ternary zeotropic mixture in batch distillation. Firstly, the model representing a ternary system of hexanol/octanol/decanol has been simulated to analyze the open-loop and close-loop dynamics of the process. Secondly, the open-loop and closed-loop operations are integrated with single stage VRC scheme to achieve energy savings. Single stage VRC is operated at very high compression ratio (CR) due to the large temperature difference of the top and bottom streams in batch distillation column. To further improve the thermodynamic efficiency of single stage VRC, double stage compression without intercoolers between the stages of VRC is proposed. Two control schemes have been implemented for constant composition, namely proportional integral (PI) controller and nonlinear gain scheduling proportional integral (GSPI) with and without VRC in closed-loop. The results shows that double stage VRC with GSPI algorithm provides better performance than conventional in terms of energy, product amount and Integral Square Error (ISE).