Robust Gain-scheduled Controller Research Articles

Robust gain-scheduled control for unmanned aerial vehicles

The flight dynamics of a modern aircraft are highly nonlinear and vary over the wide flightenvelope of the aircraft. This fact makes it difficult for a single controller to achieve the desired closedloopspecifications. This paper considers gain-scheduling successive loop control design for linear parameter-varying system in terms of linear matrix inequalities. The obtained controller guarantees an efficientunmanned aerial vehicle’s control under external disturbances within the flight envelope. The designprocedure is illustrated by a case study of unmanned aerial vehicle lateral channel control

Robust Gain-Scheduling Control with Guaranteed Performance

Abstract: Robust Gain-Scheduling (RGS) control synthesis conditions are developed in this paper. Differently from most existing literature in gain-scheduling control, the derived conditions assume scheduling parameters are inexactly measured. This is a realistic assumption for practical control applications. Sufficient conditions in terms of Parametrized Bilinear Matrix Inequalities (PBMIs) for synthesizing dynamic output-feedback controllers with guaranteed H ∞ performance are given. The resulting controller not only guarantees robust stability and H ∞ performance but also ensures robustness against scheduling parameter uncertainties. An numerical example is presented to demonstrate the effectiveness of the developed approach and compare with existing approaches from literature.

Guaranteed Performance State-Feedback Gain-Scheduling Control With Uncertain Scheduling Parameters

State-feedback gain-scheduling controller synthesis with guaranteed performance is considered in this brief. Practical assumption has been considered in the sense that scheduling parameters are assumed to be uncertain. The contribution of this paper is the characterization of the control synthesis that parameterized linear matrix inequalities (PLMIs) to synthesize robust gain-scheduling controllers. Additive uncertainty model has been used to model measurement noise of the scheduling parameters. The resulting controllers not only ensure robustness against scheduling parameters uncertainties but also guarantee closed-loop performance in terms of H2 and H∞ performances as well. Numerical examples and simulations are presented to illustrate the effectiveness of the synthesized controller. Compared to other control design methods from literature, the synthesized controllers achieve less conservative results as measurement noise increases.

Design of robust gain scheduled hold control system

Запропоновано методику налаштування робастної системи керування на прикладі режиму стабілізації кута тангажу для невеликих безпілотних літальних апаратів за допомогою табличних ПІД-регуляторів. Моделювання замкнутої системи з урахуванням змін умов польоту та дії стохастичних збурень демонструє ефективність запропонованої процедури. Метод корисний для отримання системи з високим рівнем показників якості та робастності

Robust Controller Design for T1DM Individualized Model:Gain-Scheduling Approach

This paper deals with the robust gain-scheduled controller design for individualized type 1 diabetes mellitus (T1DM) subject model. The controller is designed using LPV model created from T1DM minimal model with two additional subsystems - absorption of digested carbohydrates and subcutaneous insulin absorption. Data collected from continuous glucose monitoring with the help of pharmacodynamics and pharmacokinetics characteristics were used for model identification. The closed-loop stability and cost for all scheduled parameters is guaranteed by the controller design approach. The benefits of the presented approach are shown in the simulation results.

Robust gain scheduled control of spacecraft rendezvous system subject to input saturation

The problem of robust control of spacecraft circular orbit rendezvous system subject to input saturation is studied in this paper. The relative model with parameter uncertainties caused by linearization error and saturation nonlinearity is established based on C–W equation. By combining the parametric Riccati equation and the existing gain scheduling technique, a new robust gain scheduling controller is proposed to solve the robust control problem. By scheduling the design parameters online, the convergence rate of the state can be improved. With the designed controller, the spacecraft orbit rendezvous is accomplished successfully. Numerical simulations show the effectiveness of the proposed approach.

Design of robust gain-scheduled PI controllers

A novel approach to robust gain-scheduled controller design is presented. The proposed design procedure is based on the robust stability condition developed for an uncertain LPV system model introduced in this paper. The feasible design procedures are obtained in the form of BMI or LMI. The obtained design results and their properties are illustrated in simulation examples.

Robust Gain-Scheduled Controller Design for T1DM Individualised Model

Novel original robust gain-scheduled controller design for individualized type 1 diabetes mellitus (T1DM) subject model is presented in this paper. For controller design an LPV model is created from insulin-glucose subsystem based on Bergman’s minimal model with subcutaneous insulin absorption and absorption of digested carbohydrates. Identification was performed on pharmacokinetics and pharmacodynamics characteristics of administered insulin and data collected from continuous glucose monitoring (CGM) system. The controller design approach guarantees the closed-loop stability and cost for all scheduled parameter changes. Simulation results show the benefits of the proposed approach.

Robust Gain-Scheduling Controller for Airbreathing Hypersonic Flight Vehicle

This paper addresses issues related to robust control for an airbreathing hypersonic flight vehicle. Owing to aero-propulsion couplings caused by the unique structure shape, the model of the vehicle is greatly nonlinear and complex, which presents an enormous technical challenge for control. The nonlinear model is transformed into a linear fractional transformation (LFT) model, and a robust gain-scheduling controller based on linear parameter-varying control (LPV) with full block multipliers is obtained. Simulations illustrate great improvements of the dynamic performance in closed-loop system.

A synthesis framework for robust gain-scheduling controllers

We present a general framework for the systematic synthesis of robust gain-scheduling controllers by convex optimization techniques and for uncertain dynamical systems described by standard linear fractional representations. We distinguish between linear time-varying parameters, which are assumed to be available online as scheduling parameters for the controller, and genuine uncertainties, not necessarily time-varying, parametric or linear, that are not available online. Under the rough hypothesis that the control channel is not affected by the unmeasurable uncertainties and that the properties of the uncertainties and scheduling variables are captured by suitable families of integral quadratic constraints, this paper reveals how controller synthesis can be turned into a genuine semi-definite program. The design framework is shown to encompass a rich class of concrete scenarios.

Robust Gain Scheduling Control Design in Frequency Domain

Gain scheduling control has proven to be a successful nonlinear plant control in many engineering applications. However, if the plant model belongs to an uncertain class and there is absence of a robust gain scheduled controller design procedure, these designs come with no guarantees of robust stability and performance. This paper presents a new robust gain scheduled controller design for uncertain stable MIMO and SISO systems in the frequency domain. The proposed method is based on the Small Gain Theory and known M-delta structure of a closed loop system in the frequency domain. An example illustrates the effectiveness of the proposed gain-scheduled controller.

Robust Global Stabilization of Spacecraft Rendezvous System via Gain Scheduling

The problem of robust global stabilization of a spacecraft circular orbit rendezvous system with input saturation and input-additive uncertainties is studied in this paper. The relative models with saturation nonlinearity are established based on Clohessey-Wiltshire equation. Considering the advantages of the recently developed parametric Lyapunov equation-based low gain feedback design method and an existing high gain scheduling technique, a new robust gain scheduling controller is proposed to solve the robust global stabilization problem. To apply the proposed gain scheduling approaches, only a scalar nonlinear equation is required to be solved. Different from the controller design, simulations have been carried out directly on the nonlinear model of the spacecraft rendezvous operation instead of a linearized one. The effectiveness of the proposed approach is shown.

Robust gain-scheduled controller design for uncertain LPV systems: Affine quadratic stability approach

Our paper deals with robust gain-scheduled controller design for uncertain LPV systems which ensures closed-loop stability and guaranteed cost for all scheduled parameter changes. The novel procedure is based on LPV paradigm, Lyapunov theory of stability and guaranteed cost from LQ theory. The feasible design procedures are obtained in the form of BMI or LMI. The class of control structure includes centralized or decentralized fixed order output feedbacks like PI controller. Numerical examples illustrate the effectiveness of the proposed approach.

LPV Based Robust Gain – Scheduling Control for Transient Mode of Morphing UAV

Robust Gain-Scheduling control based on Linear Parameter-Varying (LPV) system is researched in theory and applied to transient mode control of a morphing wing UAV (MUAV). H∞ output feedback control method is extended to the LPV system via parameterized LMIs. In application, LPV model of MUAV is established using the Jacobian linearization method, based on which an LPV controller is designed using the proposed method to control the attitudes of transient mode in morphing process, the problem of high frequency dynamics is found and solved by a robust pole constraint method. Monte-Carlo simulation is performed for 30 times, by which satisfactory performance and robustness of the LPV controller is revealed.

Design of fuzzy neural network‐based robust gain scheduling controllers

AbstractThis paper proposes a method of robust gain scheduling control design by intelligent control that uses a fuzzy neural network without a model. We create a system that is robust and capable of automatic gain control against the conventional fixed PID control system, design a neural network which learns inverse dynamics as feedforward compensation, along with a two‐degree‐of‐freedom control to perform feedback compensation, produce a control system which adaptively adjusts the gain according to changes of the target errors, and verify the effectiveness of the proposed method. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 169(4): 21–28, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20820

Reduced Order Robust Gain-Scheduling Control Of The Diesel Apu For Series Hybrid Vehicles

This paper presents a reduced order robust gain-scheduling approach for the control of the diesel auxiliary power unit (APU) for series hybrid vehicles. The nonlinear plant dynamics are converted into a linear parameter-varying (LPV) form with parametric uncertainties, in which only partial information of the plant states is available. For this type of LPV system, a new reduced order robust gain-scheduling synthesis method is proposed based on partial state feedback. The parametric uncertainties are considered using multipliers to reduce the conservatism. The reduced order synthesis problem is solved offline by means of linear matrix inequalities (LMIs), and the synthesis result requires much simpler online computation than the explicit controller formulas do. The synthesis method is applied to the diesel APU controller design, and simulation results are given to demonstrate the controller performance.

Robust gain-scheduled control for vertical/short take-off and landing aircraft in hovering with time-varying mass and moment of inertia

This paper presents a robust gain-scheduled control approach for planar vertical take-off aircraft dynamics. The uncertain properties of the aircraft mass, moment of inertia, and the non-minimum phase parasitic coupling are all addressed by considering a reasonable range in the progress of controller design. The realized control law is not implemented as a function of the unmeasurable coupling parameter as has been done in previous works. After a system-variable scaling process for the dynamic normalization and a control input transformation to ensure the controllability of the dynamics in a linear parameter-varying representation, the composite control law is used to address all the inherent uncertainties of the mass, moment of inertia, and parasitic coupling parameter. The composite control law consists of a linear state-feedback gain-scheduled matrix, constructed from parameter-dependent linear matrix inequalities algorithms, and a non-linear control law for thrust manipulation to eliminate the effect of gravitational disturbance. The design is then demonstrated by a time response simulation.

The vibration control of speed-dependent flexible rotor/magnetic bearing systems using linear matrix inequality gain-scheduled H∞ design

The dynamics of rotor/magnetic bearing systems are speed dependent due to gyroscopic effects and other aerodynamic influences. This paper introduces a linear matrix inequality (LMI)-based design method that enables the speed dependence to be embedded within robust gain-scheduled controllers. By utilizing an augmented plant that closely resembles the physical system, it allows for the formulation of multiple design objectives in a unified framework. In particular, a control design for minimized rotor displacements or bearing transmitted forces is considered and the importance of achieving performance over the whole speed range is addressed. If speed dependence is ignored in the controller design, system instability may occur at particular rotational speeds. However, the LMI-based gain-scheduling approach is shown to maintain closed-loop stability over the full speed range. The results are demonstrated using a system model and through measurements taken from a flexible rotor/magnetic bearing facility.

Electromagnetic Actuator Control: A Linear Parameter-Varying (LPV) Approach

This paper deals with system identification and control of a nonlinear electromagnetic actuator, which can be used in many practical applications: electromagnetic valve actuators of combustion engines, artificial heart actuators, magnetic levitation, electromagnetic brakes, etc. The considered practical control problem requires accurate control of the moving armature between two extreme positions. The main objective is to assure small contact velocity, which is known as "soft landing" of the moving armature, and, in this way, low-noise low-component-wear operation. First, due to open-loop instability, system-identification experiments are performed around different equilibrium positions under closed-loop control, and a linear parameter-varying (LPV) model and a bound of plant uncertainty are derived. Next, an LPV controller is designed in a robust control framework (robust gain-scheduled controller). Since the system evolves along quasi-equilibrium positions, quadratic and biquadratic analyses are performed using linear matrix inequalities. Finally, the experimental results show that the controller design problem can be handled successfully, considering an LPV approach. This paper reflects a pragmatic viewpoint: The control structure is simple and easy to implement, and offers good performance and robustness; therefore, it is suitable for industrial applications

Robust and gain-scheduling control of LFT systems through duality and conjugate Lyapunov functions

In this paper, we study stability and performance properties of linear fractional transformation (LFT) parameter-dependent systems using duality theory and tools from convex analysis. A pair of conjugate functions, the convex hull and the maximum of a family of quadratic functions, are used for analysis and synthesis of LFT systems. Sufficient synthesis conditions for both robust state feedback and gain-scheduling output feedback control problems are formulated as a set of linear matrix inequalities (LMIs) with linear search over scalar variables. Finally, a numerical example is used to demonstrate the advantages of the proposed approaches.