Gain Scheduling Research Articles

Advanced embedded generalized predictive controller based on fuzzy gain scheduling for agricultural sprayers with dead zone nonlinearities

Variable rate application of pesticides in agriculture can improve pest control and also increase food production. Nevertheless, incorrect spraying poses risks to the environment and human health, as well as may increase the total cost of production. Nowadays, it is quite known the importance of innovation in techniques and technologies to improve the spraying process in a variable rate application for pest control. This work presents a generalized predictive control (GPC) strategy to cope with nonlinearities. An extension of the stability analysis for constrained GPC controller for infinite horizons is also developed, which guarantees the stability of a fuzzy GPC for a limited variation of its tuning parameters λ and δ. Results show the usefulness in adding a fuzzy logic system, to cope with nonlinearities, leading to a conception of an advanced fuzzy GPC for a limited variation of its tuning parameters.

Adaptive gain scheduling based event-triggering control design for robust performance of active magnetic bearing

This article proposes an efficient adaptive robust control for the eight-pole active magnetic bearing based on a heteropolar structure. Due to the uncertain behavior of active magnetic bearing, the mathematical model of active magnetic bearing is considered to be highly nonlinear and uncertain. As the rotor displacement and velocity are the measurable states, sliding mode control is designed to estimate state variables. Also, a matched disturbance term is used to deal with undesirable disturbances in the active magnetic bearing system. The controller is developed for an active magnetic bearing using the event-triggering-based sliding mode control technique. However, the stability of the proposed scheme has been achieved with the help of Lyapunov theory. Furthermore, the adaptive gain scheduling approach based on a neural network has been augmented to adjust the gain of the proposed controller for active magnetic bearing adaptively. The simulation studies have been performed in detail to demonstrate the use of proposed scheme for the robust control of active magnetic bearings. Finally, a comparative analysis of the proposed control design scheme with a conventional controller has been performed to achieve improved performance satisfying the plant constraints.

Multiobjetive H2/H control of a pitch regulated wind turbine for mechanical load reduction.

The paper deals with the design of acontrol system for a variable-speed pitch-regulatedwind turbine in the operating region correspond-ing to wind speeds above rated wind speed. Thecontrol objectives are mostly to regulate the plantoutput power and to reduce the mechanical fatigueof the plant components. The controller is designedfrom a non linear model of the system which takesinto account the blades, shaft and tower flexibil-ities. A Linear Matrix Inequalities (LMI) formu-lation of the control problem permits to obtaina Linear Parameter Varying (LPV) controller op-timizing, throughH2/H∞norm minimization, acriteria close to mechanical fatigue affecting theplant. The proposed controller performances arethen compared in simulation with those of a gainscheduling Linear Quadratic Gaussian (LQG) con-troller and with a gain scheduling PI controller, andis seen to be more efficient.

Polytopic LPV modeling and gain scheduling [formula omitted] control of ball screw with position- and load-dependent variable dynamics

Ball screw drive (BSD) is a precision transmission mechanism widely used in high-precision positioning or tracking systems. The dynamic behavior of BSD varies with position and load, which causes tracking errors and poor robustness. Therefore, this paper proposes a polytopic linear parameter varying (LPV) model to express the varying dynamic behavior of BSD. The parameters of the LPV model are identified by the closed-loop frequency domain method and Levenberg–Marquardt iterative algorithm. Based on the polytopic LPV model, an LPV gain scheduling (GS) H∞ controller is proposed for the BSD with varying dynamics. Specifically, the controller is designed through polytope-based GS representation and mixed sensitivity synthesis. The most significant part is the proposal of a GS H∞ control algorithm to implement controller parameters that change with changing dynamics. Moreover, the stability of the closed-loop system is achieved by quadratic stabilization with state feedback. Finally, identification experiments and trajectory-tracking comparative experiments are carried out. The experimental results demonstrate that the proposed polytopic LPV modeling and GS H∞ control synthesis are effective in achieving accurate trajectory tracking and excellent robustness.

A Study of a Gain-Scheduled Individual Pitch Controller for an NREL 5 MW Wind Turbine

In order to reduce the asymmetric load acting on the blades of MW-class wind turbines, it is necessary to apply an individual pitch controller that independently adjusts the pitch angles of the three blades. This paper takes a new look at the relationship between the individual pitch controller applied to MW-class wind turbines and the vibration mode of the blades. The purpose of this study is to propose a method in which the individual pitch controller further reduces the 1P component of the bending moment in the out-of-plane direction acting on the blade, without exciting the in-plane vibration mode of the blade within the entire wind speed range, from the rated wind speed to the cut-out wind speed. To this end, a problem related to the excitation of the blade’s vibration mode that may occur when applying the individual pitch controller to an NREL 5 MW wind turbine is examined, and a method that uses gain scheduling to overcome this problem is presented. It is confirmed that it is possible to solve the problem of exciting the first-order vibration mode in the in-plane direction of the blade that can occur in the high wind speed range by applying the proposed gain scheduling method to the individual pitch controller aimed at reducing the 1P component of the out-of-plane bending moment of the blade.

Gain Scheduled PI controller design using Multi-Objective Reinforcement Learning

Gain scheduling, a widely adopted control design approach, performs tasks by decomposing into sub-problems. It has found successful applications across diverse fields, including aerospace and industrial process control (Leith and Leithead (2000)). Reinforcement Learning (RL) has become increasingly significant in process control applications, thanks to the advancement of sophisticated algorithms and the rise in computational speeds. An attempt has been made to enhance the performance of a Proportional-Integral (PI) controller by integrating the benefits of both gain scheduling and RL. The manuscript focuses on designing a Gain Scheduled PI controller using Multi-Objective RL (GS-MORL). Proposing the training of multiple RL-based PI controllers with distinct objectives with customized reward functions to derive tuning parameters for each goal. The switching between these parameter sets is facilitated by a gain schedule variable. The controller parameters are adjusted based on the error between actual and desired responses. The aim is to enhance overall performance across various performance indices, including the integral of absolute error and time response specifications. The performance improvement from the proposed work has been demonstrated using two simulation case studies, one involving an underdamped second-order system and an integrating type steam turbine system. Comparative analysis against existing literature revealed superior performance across all indices.

A COMPARATIVE ANALYSIS OF LOWER LIMB EXOSKELETON GAIT CONTROL SYSTEMS

The complexities associated with lower limb exoskeleton control systems stem from the dynamic and non-linear nature of human movement. Gait control, in particular, re-quires intricate coordination of joints and muscles, demanding precise adjustments to ac-commodate variations in walking speed, terrain, and user preferences. Additionally, the diverse physical characteristics among users, such as weight, height, and muscle develop-ment, introduce parametric uncertainties that amplify the challenge of designing control systems that can adapt seamlessly to individual differences. Addressing these complexities involves an advanced and multi-level control approach. In the pursuit of effective control strategies, a non-linear mathematical model for a single-leg lower limb exoskeleton is de-rived, considering mechanical and electromechanical components. Тhe gait control sys-tems of a lower limb exoskeleton were investigated, emphasizing the development of vari-ous control strategies, including proportional derivative (PD), PD with gain scheduling, hy-brid adaptive, and adaptive controllers with gain scheduling. The article ends with a com-prehensive comparative analysis of the developed controllers, presenting the integral abso-lute errors (IAE) during exoskeleton walking in both load and no-load conditions to evalu-ate their productivity, efficiency, and adaptability. Extensive testing was conducted using a physical test model representing the exoskeleton of the lower limbs. During a series of ex-periments, the functionality and operability of each control system were evaluated in vari-ous scenarios. The results of these tests give valuable information about the strengths and weaknesses of various control strategies, contributing to the development of lower limb exoskeleton technology.

Practice-oriented controller design of a simple nonlinear system

The paper analyses and illustrates the design of a constrained gain scheduling for a simple non-linear hydraulic system based on automatic-reset controller. The main objective is to explain the basics of gain-scheduling control in a simple way so that it can be understood by computer programmers working in the field of automatic control. The study is based on small deviations from the selected operating points that allow the use of linear design methods. In contrast to linearization-based design methods, where the control action is calculated by integrating small control increments, the new control output is obtained by adding the calculated small increments to the operating point values. Another innovative aspect is the introduction of a gain-scheduled automatic-reset controller. This is the oldest and the simplest control solution including a disturbance observer based on ultra-local models and accurate even in steady-states.

On the implementation of gain scheduling in FOPID controllers

This paper deals with the implementation of a gain scheduling technique for fractional-order-proportional-integral-derivative (FOPID) controllers. The presence of fractional-order integer and derivative parts requires special considerations when the controller parameters are changed during the control task due to the initialization issue of the fractional operators when the fractional order changes. Simulation results show the effectiveness of the proposed technique.

A Data-Driven Method for Online Gain Scheduling of Distributed Secondary Controller in Time-Delayed Microgrids

A Data-Driven Method for Online Gain Scheduling of Distributed Secondary Controller in Time-Delayed Microgrids

Modified Active Disturbance Rejection Control Design Based on Gain Scheduling for Selective Catalytic Reduction Denitrification Processes

Modified Active Disturbance Rejection Control Design Based on Gain Scheduling for Selective Catalytic Reduction Denitrification Processes

Marine Wind Turbine PID-PID Torque Control with Vibration Reduction

Marine turbines are an alternative for the production of clean energy in countries where the use of land turbines is limited. However, these systems, especially floating turbines, present a series of control challenges due to their non-linear dynamics and strong wind and wave loads. In this work, a dual control architecture is proposed consisting of two conventional Proportional-Integral-Derivate (PID) controllers that have been tuned with genetic algorithms. One of them is responsible for achieving maximum power in the operating region where torque control is applied, and the other tries to reduce the oscillations of the turbine that cause its efficiency to decrease and produce structural fatigue. Furthermore, the benefits of including the gain scheduling based on wind speed in this dual structure have been studied. This dual control structure has been shown in simulation to be useful for both objectives.

An Adaptive PID Control System for the Attitude and Altitude Control of a Quadcopter

Abstract In adaptive model-based control systems, determining the appropriate controller gain is a complex and time-consuming task due to noise and external disturbances. Changes in the controller parameters were assumed to be dependent on the quadcopter mass, which was the process variable. A nonlinear model of the plant was used to identify the mass, employing the weighted recursive least squares (WRLS) method for online identification. The identification and control processes involved filtration using differential filters, which provided appropriate derivatives of signals. Proportional integral derivative (PID) controller tuning was performed using the Gauss–Newton optimisation procedure on the plant. Differential filters played a crucial role in all the developed control systems by significantly reducing measurement noise. The results showed that the performance of classical PID controllers can be improved by using differential filters and gain scheduling. The control and identification algorithms were implemented in an National Instruments (NI) myRIO-1900 controller. The nonlinear model of the plant was built based on Newton’s equations.

Tau Theory-Based Flare Control in Autonomous Helicopter Autorotation

A novel trajectory generation and control architecture for fully autonomous autorotative flare that combines rapid path generation with model-based control is proposed. The trajectory generation component uses optical Tau theory to compute flare trajectories for both longitudinal and vertical speed. These flare trajectories are tracked using a nonlinear dynamic inversion (NDI) control law. One convenient feature of NDI is that it inverts the plant model in its feedback linearization loop, which eliminates the need for gain scheduling. However, the plant model used for feedback linearization still needs to be scheduled with the flight condition. This key aspect is leveraged to derive a control law that is scheduled with linearized models of the rotorcraft flight dynamics obtained in steady-state autorotation, while relying on a single set of gains. Computer simulations are used to demonstrate that the NDI control law is able to successfully execute autorotative flare in the UH-60 aircraft. Autonomous flare trajectories are compared to piloted simulation data to assess similarities and discrepancies between piloted and automatic control approaches. Trade studies examine which combinations of downrange distances and altitudes at flare initiation result in successful autorotative landings.

Gain scheduled task space control of multi DOF machine tools with non-linear parallel kinematics

Machine tools with multiple degrees of freedom and parallel kinematics offer tremendous opportunities for new kind of processes but at the same time also a lot of control challenges. They are subject to uncertainties in the form of kinematic errors, elasticities and thermal deflections. Their kinematic non-linearity requires the application of model-based control concepts whose full effectiveness can only be unlocked through controls in the task space. In particular, kinematic singularities occur in forming machines such as presses, which make closed-loop control at corresponding operating points considerably more difficult. In this paper, we use the example of a servo-driven press with three ram degrees of freedom to show how parallel kinematic machine tools can be controlled via inverse differential kinematics models in task space and to what extent the controls can benefit from scheduled gain factors. The results are validated both simulatively and experimentally. In the experimental tests, three-dimensional tool paths are traced that can be used to carry out orbital forging processes. Furthermore, the example of a punch hole rolling process demonstrates that the ram pose is controlled more accurately, which also has positive effects on the resulting workpiece geometry. The performance of the developed gain scheduling task space control is compared with that of a robust and non-robust control with static gains.

MRAC with SMC Applied to Lateral Control of a Fixed-Wing MAV

Abstract: This paper presents a PD control law with adaptive gains with the MIT (Massachusetts Institute Technology) rule with different sliding modes; that is, the MIT rule has been designed with is known in the literature with first order sliding mode, second order sliding mode and high order sliding mode (HOSM) to obtain a better gain scheduling taking advantage the sliding modes techniques-the PD control law with adaptive gains that is designed for the lateral dynamics of a fixed-wing MAV. To apply the methodology of the model reference adaptive control (MRAC), sometimes called model reference adaptive system (MRAS), to the adaptive gains of the PD control, a sliding manifold is proposed considering the output of the lateral dynamics and with the output of the reference model.

Extending Closed-Loop Control of Two-Dimensional Supersonic Boundary-Layer Instabilities Beyond a Single Operating Point

This paper investigates two control strategies to maintain low perturbation amplitudes of second Mack mode instabilities in a two-dimensional boundary layer with freestream velocity variations of ±5% around M∞=4.5: the multimodel synthesis and the gain scheduling method, both based on the structured mixed H2/H∞ synthesis to handle simultaneously, in an optimal way, the problems of nominal performance, stability, and performance robustness. The multimodel synthesis is based on a single linear-time invariant (LTI) controller optimized over multiple operating points, whereas the gain scheduling method results in a control law based on the interpolation of multiple LTI controllers designed at the various operating points. Both methods are compared with simple LTI controllers based solely on the nominal operating point in two sensor–actuator architectures: in feedforward (respectively, feedback) the estimation sensor is located upstream (respectively, downstream) of the actuator. In the feedforward case, significant performance loss is observed in off-design conditions, regardless of the method used. In the feedback case, multimodel synthesis enhances slightly performance robustness (but improvement is weak because of the wide range of freestream velocity variation), while the gain scheduling approach succeeds in strongly reducing the perturbation amplitude over the entire range of variation.

Design of a robust controller for the VEGA TVC using the L1-Adaptive Control

The purpose of this study is to Design of a robust controller for the VEGA TVC using the L1-Adaptive Control. The performance of the system with an L1 adaptive controller has been compared with that of a classical controller. The L1 adaptive controller optimization is an efficient as well as an effective approach for the design of a robust controller. The L1 adaptive controller ensures the robustness of the system against uncertainties, noise, and disturbances[10]. In a launch vehicle parameters like mass, thrust, and aerodynamic properties are time-varying. Due to the time-varying nature of these parameters gain scheduling is necessary with the classical control design methods otherwise the closed-loop system might become unstable for some values of these parameters. This procedure is costly and has no robustness. In addition to this, there are external disturbances also which can make the control system unstable. This is the reason why robust control is necessary. There is a trade-off between achievable performance and robustness. So, we need to compromise between required performance and robustness as per the requirement.

Implementing gain scheduling approach to control large-scale production of diethyl oxalate in a catalytic fixed bed multi-tubular reactor

In the large-scale production of Diethyl Oxalate (DEO), numerous control and optimization challenges are faced. These issues are targeted in this study by implementing a gain scheduling approach to control a catalytic fixed bed multi-tubular reactor designed for DEO production. A novel inferential modeling method, developed using Python and response surface methodology, was applied to simulate the dynamics of the reactor, and the inlet coolant temperature was identified as the most influential parameter. An inferential control system was implemented that utilized gain scheduling for Proportional Integral Derivative (PID) controllers. The results showed that the proposed PID controller gains offered fast and stable responses, even at high conversion setpoints. However, minimization of response overshoot at high amplitudes of step changes proved challenging, leading to a decrease in conversion estimator accuracy. The use of a quadratic model from response surface methodology for the regression of the inferential estimator was proposed, showing improved prediction accuracy over the linear model. These findings provide valuable insights and guide future optimization in the design and operation of reactors for large-scale DEO production.

Temperature-Controlled Laser Cutting of an Electrical Steel Sheet Using a Novel Fuzzy Logic Controller

A novel PID-type fuzzy logic controller (FLC) with an online fuzzy tuner was created to maintain stable in situ control of the cutting front temperature, aiming to enhance the laser process for thin non-oriented electrical steel sheets. In the developed controller, the output scaling factors and the universe of discourse were initially optimized using a hybrid of the particle swarm optimization and grey wolf optimization methods. The optimal parameters obtained were utilized in experiments involving the laser cutting of thin non-oriented electrical steel sheets, compared to an open-loop control system maintaining a constant cutting speed. The PID-type FLC with an online fuzzy tuner demonstrated a superior cutting quality, generating a smaller roundness and a reduced heat-affected zone (HAZ) through the in situ tuning of control parameters. Particularly, the HAZ width was significantly smaller than that reported in a previous study which used fuzzy gain scheduling for temperature control. Moreover, the cutting time was diminished by optimally adjusting the cutting speed using PID-type FLC with an online fuzzy tuner. Therefore, the accumulated heat in the steel sheet, particularly under high laser pulse frequencies, was effectively reduced, making it suitable for industrial applications.