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In this paper, the design problem of Gain‐Scheduled Output‐Feedback (GSOF) controllers using inexact scheduling parameters for morphing aircraft during the wing transition process is addressed. Both the stability of the closed‐loop system and the L2 gain performance can be guaranteed under the controller based on measured (not actual) scheduling parameters. Firstly, the linear parameter‐varying (LPV) model of morphing aircraft is established by Jacobian linearization and the additive uncertainty is introduced into the scheduling parameters. By employing non‐linear transformations, the problem is formulated as the solution to a set of parameter‐dependent linear matrix inequalities (LMI) with a single‐line search parameter. Finally, the robustness of the flight control system to the wing transition process is verified under the condition of both the uncertainty of aerodynamic parameters and of scheduling parameters.

The time-varying and rigid-flexible coupling dynamic behaviors of ball screw feed drives (BSFD) are the main reasons that affect their tracking and positioning accuracy. The traditional PID control strategy cannot overcome the impacts resulted from these factors. A linear parameter varying (LPV) model based gain scheduling (GS) control method is proposed. Considering the time-varying and rigid-flexible coupling dynamic characteristics of a BSFD, its LPV model is established through identification experiments of the rigid-body transfer function, Stribeck friction, and elastic-body transfer function. Based on the LPV model, an output feedback GS control strategy is proposed, and a tuning method of the controller parameters is summarized. The comparison experiments between the GS and PID control strategies prove that the GS control strategy can ensure the consistency of tracking and positioning accuracy on the entire feed stroke of the BSFD. This work is of great significance for improving the machining accuracy reliability and accuracy retention of CNC machine tools.

The use of quadrotor helicopters is highly demanded in both military and commercial fields. Depending on the application area, special requirements may be needed for the maneuverability of these unmanned aerial vehicles. Traditional controller structures cannot meet these demands, leading developers to seek innovative solutions. In this study, a gain-scheduling controller is proposed to maintain the performance requirements for the attitude control of quadrotor helicopters. In this context, different operating points are selected based on a proposed rule in the working region of the quadrotor helicopter, and a controller design is carried out after a necessary transformation of the linear models. Furthermore, the robustness of quadrotors against time-varying disturbances is ensured through the implementation of a supervisor neural network (NN) controller. Specifically, a radial basis function NN (RBFNN) is employed, trained using gradient descent-based supervised learning. The response of the proposed controller is compared numerically with the traditional proportional-derivative controller’s response, where the proposed controller, which is not so different from conventional controllers in terms of processor power, provides the desired performance criteria in a wide operating region. Finally, the gain-scheduling controller improved with the feedforward NN controller is tested under time-varying disturbances, resulting in a significant reduction in errors.

Gain scheduling control of hypersonic vehicles (HVs) in full envelope is studied utilizing switching polytopic linear parameter-varying (LPV) method. Envelope division and a new convex decomposition strategy with optimal gap metric are used to establish the switching polytopic LPV system of HVs. Sufficient conditions for stability assessment and controller synthesis for the switching polytopic LPV system are presented by average dwell time (ADT) and multiple parameter-dependent Lyapunov functions (MPDLF). To reduce computation burden and simplify the realization of controller, limited number of linear matrix inequalities (LMIs) are derived to dealing with switching polytopic LPV controllers by constructing the intermediate controller variables are depend affinely on the scheduling parameter. Furthermore, to make the proposed method have better engineering value, the control matrix of LPV system studied in this paper may not have to be a constant matrix. Simulation results show the effectiveness of the switching polytopic LPV control method for HVs.

In this paper, a general type-2 fuzzy gain scheduling PID (GT2FGS-PID) controller is presented to achieve self-balance adjustment of the power-line inspection (PLI) robot system. As the PLI robot system is an under-actuated nonlinear system, obtaining the full information of the four-state variables is necessary to balance the PLI robot. However, as the number of input variables increases, the number of control rules increases exponentially, making the design of the fuzzy controller extremely complex. Therefore, the proposed controller prevents the problem of rule explosion using information fusion and then simplifies the control design. Moreover, the particle swarm optimization algorithm is used to select improved controller parameters and make the controller achievable. In this paper, the control performance and anti-interference ability of the traditional PID control, type-1 fuzzy control, interval type-2 fuzzy control, and general type-2 fuzzy control methods are compared. By means of numerical simulation, we can conclude that the GT2FGS-PID controller exhibits superior stability and robustness over other controllers for the PLI robot system.

Floating offshore wind turbines (FOWTs) face inherent control limitations in above‐rated operating conditions due to right‐half‐plane zeros in the blade‐pitch‐to‐rotor‐speed dynamics, which restrict achievable control bandwidth and may lead to closed‐loop instability. Conventional mitigation strategies based on controller detuning preserve stability at the expense of performance, while auxiliary feedback loops improve regulation but introduce additional dynamic coupling that complicates tuning and gain scheduling. This work proposes a novel gain‐scheduling methodology based on an output‐feedback linear quadratic regulator (LQR) formulation for pitch control of FOWT. The approach leverages a reduced‐order linear model capturing the dominant coupled dynamics of the drivetrain and platform pitch motion and synthesizes optimal gains scheduled as functions of operating conditions. The resulting gains are directly mapped onto the standard Reference Open‐Source Controller (ROSCO) pitch control parameters, without modifying the controller structure or introducing additional feedback loops. Nonlinear aero‐servo‐hydro‐elastic simulations performed with OpenFAST on the IEA 15‐MW reference turbine demonstrate that the proposed approach significantly improves rotor speed regulation and power quality while enhancing closed‐loop stability compared with conventional detuning strategies. These improvements are accompanied by reduced fatigue loads on the tower and blades across a wide range of wind, turbulence, and sea‐state conditions, highlighting the effectiveness and practical applicability of the proposed methodology.

Position-Based Visual Servoing (PBVS) and Image-Based Visual Servoing (IBVS) struggle to balance end effector pose accuracy and robustness in apple picking. They are also prone to target loss and control singularities. A progressive Hybrid Automatic Switching Visual Servoing (HAVS) method is proposed and applied to an apple-picking robotic system. HAVS integrates PBVS and IBVS to coordinate control of the manipulator end effector pose. A depth-based switching function is designed. When target depth is below an optimal threshold, the controller switches to PBVS for precise final positioning. This reduces target loss and control singularities. An adaptive proportional-derivative (PD) controller with fuzzy gain scheduling updates the control gains online to enhance responsiveness and stability. The hardware consists of a six-axis manipulator, a depth camera, and a mobile base. You Only Look Once version 5 (YOLOv5) performs apple detection and generates control commands. Indoors, success rate was 96%, which was 4 and 10 percentage points higher than PBVS only and IBVS only. Average picking time was 12.5 s, 0.3 s, and 1.1 s shorter. Outdoors, success rate was 87.5%, average time was 13.2 s, and damage rate was 4.2%. This method provides a reference implementation for visual servo control in agricultural picking robots.

This article is devoted to the design of a real-time gain scheduling (adaptive) proportional–integral (PI) controller for the displacement volume regulation of a swash plate-type axial piston pump. The pump is intended for open circuit hydraulic drive applications without “secondary control”. In this type of pump, the displacement volume depends on the swash plate swivel angle. The swash plate is actuated by a hydraulic-driven mechanism. The classical control device is a hydro-mechanical type, which can realize different control laws (by pressure, flow rate, or power). In the present development, it is replaced by an electro-hydraulic proportional spool valve, which controls the swash plate-actuating mechanism. The designed digital gain scheduling controller evaluates control signal values applied to the proportional valve. The digital controller is based on the new linear parameter-varying mathematical model. This model is estimated and validated from experimental data for various loading modes by an identification procedure. The controller is implemented by a rapid prototyping system, and various real-time loading experiments are performed. The obtained results with the gain scheduling PI controller are compared with those obtained by other classical PI controllers. The developed control system achieves appropriate control performance for a wide working mode of the axial piston pump. The comparison analyses of the experimental results showed the advantages of the adaptive PI controller and confirmed the possibility for its implementation in a real-time control system of different types of variable displacement pumps.

Modern multi-megawatt wind turbines are currently designed as pitch-regulated machines, i.e., machines that use the rotation of the blades (pitching) in order to adjust the aerodynamic torque, such that the power is maintained constantly throughout a wide range of wind speeds when they exceed the design value (rated wind speed). Thus, pitch control is essential for optimal performance. However, the pitching activity is not for free. It introduces vibrations to the tower and blades and generates fatigue loads. Hence, pitch control requires a compromise between wind turbine performance and safety. In the past two decades, many approaches have been proposed to achieve different objectives and to overcome the problems of a wind energy converter using pitch control. The present work summarizes control strategies for problem of wind turbines, which are solved by using different approaches of pitch control. The emphasis is placed on the bibliographic information, but the merits and demerits of the approaches are also included in the presentation of the topics. Finally, very large wind turbines have to simultaneously satisfy several control objectives. Thus, approaches like collective and individual pitch control, tower and blade damping control, and pitch actuator control must coexist in an integrated control system.

This paper establishes a dynamic pressure-based PID parameter adjustment method, which uses the function of the ratio of the maximum dynamic pressure of the rocket to the actual dynamic pressure of the current flight to correct the rocket control parameters. Compared with the traditional time-based PID parameter gain scheduling method, the number of PID parameters to be adjusted is significantly reduced from nearly 50 to 10, and the adjustment complexity is significantly reduced. Based on the method in this paper, the PID parameter debugging of the attitude control of a model-guided rocket is completed. The six-degree-of-freedom ballistic simulation results show that the control law obtained by the method in this paper meets the requirements of the attitude control of the model-guided rocket, and is superior to the traditional time-based PID parameter gain adjustment method in terms of response rate.