Gain-scheduled Control System Research Articles

Stability and Robustness Analysis and Optimization for Gain-Scheduled Control of Aero-Engines

Abstract Gainscheduled control is widely applied in the aerospace domain, yet the selection of design points for gainscheduling controllers to ensure stability and robustness throughout the range of scheduling variables remains theoretically unguided. Therefore, this paper introduces an analysis and optimization method for the stability and robustness of gain-scheduled control, aimed at providing a theoretical framework for design points selection. Initially, the method characterizes the gainscheduled control system as a polytopic Linear Parameter Varying (LPV) system, wherein the design points of the gainscheduled control system correspond to the vertices of the polytopic LPV system. Subsequently, the method utilizes Linear Matrix Inequality techniques to demonstrate the stability of a polytopic LPV system with a corresponding number of vertices, and by assessing the approximation degree between the polytopic LPV system and the gainscheduled control system with an identical number of design points, it evaluates and ensures the stability of the latter, thereby establishing the minimal requirements for the number of design points. After ensuring stability, the method further refines the number of design points within the gainscheduled control system to meet additional robustness and performance considerations. A case study on turbofan engine controls validates the proposed method. New design points, selected via stability and robustness analysis, enhance the system's steadystate phase margin and robustness against model uncertainties. Moreover, compared to a vgap metric-based method, the two methods exhibit similar performance in terms of stability, robustness, and tracking control. However, the proposed method requires fewer design points, resulting in less conservatism.

Research on fuzzy weighted gain scheduling water level control system of U-tube steam generator

U-tube steam generator (UTSG) is one of the key components of the pressurized water reactor (PWR) in nuclear power plant (NPP). The Traditional UTSG water level control system (WLCS) copes with a wide range of load variations by changing the gain of the water level controller. The water level controller is designed based on a specific power level. At other power levels simply changing the gain of the controller will not perform well. Therefore, it is necessary to study a full power range UTSG WLCS. In this paper, based on the transfer function, the traditional controller is designed, including water level controllers and flow rate controllers under five power levels. However, the traditional controller is designed based on fixed working points, and the performance is poor when applied to other power levels. In order to solve this problem, the fuzzy weighted (FW) controller is designed by using the triangle fuzzy membership function and trapezoidal fuzzy membership function respectively. The simulation results show that the FW controller using the triangle fuzzy membership function is recommended.

Enhancing performance and stability of gain-scheduling control system using evolutionary algorithms: A case study on transport aircraft

An enhanced gain-scheduling control strategy was presented to establish a smooth adaptation mechanism for the longitudinal motion of B747 between different flight envelopes. The focal objective is to accomplish a smooth and non-conservative gain-scheduling control system that has high performance and stability characteristics for different flight conditions and transitions between them. The proposed approach ensured a successful gain scheduling control system by allocating a specific error performance index that should be minimized for all flight conditions. Then all required performance indices were cohered according to the flight envelope in the form of a multi-objective optimization problem that could be solved using evolutionary algorithms. The performance and stability of the transition points between different flight conditions were preserved through the sets of feasible solutions obtained by an evolutionary algorithm which are known as a set of Pareto optimal solutions. The proposed gain-scheduling system was built based on 2DoF-PID (Two-degree-of-freedom Proportional Integral Derivative) controller. An auto-decision-maker was developed to adjust the parameters of the 2DoF-PID gain-scheduling control system with the current flight condition. The effectiveness of the proposed gain-scheduling control structure was studied for two different multiobjective evolutionary-based optimizers known as fast sorting and elite multi-objective genetic algorithm.II (NSGA.II), and sub-population genetic algorithm.II (SPGA.II). The proposed methodology was evaluated by simulation results according to the quality of the pareto-front and transient response characteristics of the proposed gain-scheduling controller for the chosen flight conditions in normal flight conditions and 50% loss of actuator effectiveness.

Enhancing Performance and Stability of Gain-Scheduling Control System Using Evolutionary Algorithms: A Case Study on the Transport Aircraft

Enhancing Performance and Stability of Gain-Scheduling Control System Using Evolutionary Algorithms: A Case Study on the Transport Aircraft

Simple Gain-Scheduled Control System for Dissolved Oxygen Control in Bioreactors

An adaptive control system for the set-point control and disturbance rejection of biotechnological-process parameters is presented. The gain scheduling of PID (PI) controller parameters is based on only controller input/output signals and does not require additional measurement of process variables for controller-parameter adaptation. Realization of the proposed system does not depend on the instrumentation-level of the bioreactor and is, therefore, attractive for practical application. A simple gain-scheduling algorithm is developed, using tendency models of the controlled process. Dissolved oxygen concentration was controlled using the developed control system. The biotechnological process was simulated in fed-batch operating mode, under extreme operating conditions (the oxygen uptake-rate’s rapidly and widely varying, feeding and aeration rate disturbances). In the simulation experiments, the gain-scheduled controller demonstrated robust behavior and outperformed the compared conventional PI controller with fixed parameters.

Gain Scheduled Attitude Control of Fixed-Wing UAV With Automatic Controller Tuning

Fixed-wing unmanned aerial vehicles (UAVs) have become increasingly important in military, civil, and scientific sectors. Because of the existing nonlinearities, effective control this type of UAV remains a challenge. This paper proposes a gain scheduled proportional-integral derivative (PID) control system for fixed-wing UAVs where a family of PID cascade control systems is designed for several operating conditions of airspeed. This is done using an automatic tuning algorithm, where the controllers are automatically selected by deploying an airspeed sensor positioned ahead of the aircraft. Furthermore, the actual gain scheduling is carried out by forming an interpolation between the family members of the linear closed-loop system, which ensures a smooth transition from one operating point to another. Experimental results are conducted in a wind tunnel to show the successful design and implementation of the gain scheduled control system for the fixed-wing UAV and the significant performance improvement over a linear control system without controller adaptation.

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

Automated generation and comparison of Takagi–Sugeno and polytopic quasi-LPV models

In the last decades, gain-scheduling control techniques have consolidated as an efficient answer to analysis and synthesis problems for non-linear systems. Among the approaches proposed in the literature, the linear parameter varying (LPV) and Takagi–Sugeno (TS) paradigms have proved to be successful in dealing with the different trials that the analyzer, or the designer, of a gain-scheduled control system has to face. Despite the strong similarities between the two paradigms, research on LPV and TS systems has been performed in an independent way and some results that could be useful for both paradigms were obtained only for one of them. However, in recent works, some clues that there is a very close connection between LPV and TS worlds have been presented. The present paper openly addresses the presence of strong analogies between LPV and TS models, in an attempt to establish a bridge between these two worlds, so far considered different. In particular, this paper addresses the modeling problem, presenting two methods for the automated generation of LPV and TS systems, and introducing some measures in order to compare the obtained models. A mathematical example is used to illustrate the proposed methods.

GENETIC FUZZY APPROACH TO ADAPTIVE CRANE CONTROL SYSTEM

In automated manufacturing processes the safety, precise and fast transfer of goods realized by automated material handling devices is required to raise efficiency and productivity of manufacturing process. Hence, in those industrial branches where cranes are extensively used the problem of an anti-sway crane control is especially important to speed-up the time of transportation operations and ensures the safe and effective transportation operations. The precise positioning of a cargo requires controlling the speed of crane motion mechanisms to reduce the sway of a payload. Moreover, the anti-sway crane control scheme involves applying the adaptive techniques owing to the nonlinearities of a system that comes especially from stochastic variation of rope length on which a payload is suspended and mass of this payload. The paper provides the design method of an adaptive control system for a planar model of crane. The control system is based on the gain scheduling control scheme created using fuzzy logic controller with Takagi-Sugeno-Kang-type fuzzy implications. The design process of a gain scheduling control system consists in selecting such a suitable set of operating points at which the linear controllers are determined that interpolation control scheme ensures the expected control quality within the known range of nonlinear system parameters changes, when those parameters vary in relation to the exogenous variables: rope length and mass of a payload. The method that is proposed in this paper to solve the problem of designing the fuzzy gain scheduling crane control system for minimum set of operating points is based on the pole placement method and genetic algorithm.

Gain scheduled continuous-time model predictive controller with experimental validation on AC machine

Linear controllers with gain scheduling have been successfully used in the control of nonlinear systems for the past several decades. This paper proposes the design of gain scheduled continuous-time model predictive controller with constraints. Using induction machine as an illustrative example, the paper will show the four steps involved in the design of a gain scheduled predictive controller: (i) linearisation of a nonlinear plant according to operating conditions; (ii) the design of linear predictive controllers for the family of linear models; (iii) gain scheduled predictive control law that will optimise a multiple model objective function with constraints, which will also ensure smooth transitions (i.e. bumpless transfer) between the predictive controllers; (iv) experimental validation of the gain scheduled predictive control system with constraints.

Heliostat-field gain-scheduling control applied to a two-step solar hydrogen production plant

This article describes a temperature control structure designed for the interior of a solar hydrogen reactor based on a two-step ferrite-redox technology. Until now, this temperature has been controlled by manual selection of the heliostats to be focused on the receiver targets. However, the strong system dependency on operating conditions suggests that the procedure be automated in order to ensure the desired setpoint change response. The aims are to maintain the desired temperatures and to make the setpoint switch as fast as possible, keeping plant conditions within the margins of safety. The scheme proposed includes a procedure for selecting the heliostats to be focused on the reactor by using a simple model of the solar field and a gain scheduling control system which changes the control tuning parameters to deal with the varying dynamics observed during the process. Real experiments show the promising results of this work.

Turbofan aero-engine full flight envelope control using H<SUB align=right>∞ loop-shaping control technique

A full flight envelope turbofan aero-engine control is developed by H ∞ loop-shaping control concept in this paper. First, H∞ loop-shaping control concept which is carried out in frequency domain is introduced and used to aero-engine control design. In order to meet the maximum robustness, multi-objective genetic algorithm is proposed creatively to obtain the global optimum loop-shaping weights. Second, considering the finite robustness of H ∞ loop-shaping controller while implementing the task of flight envelope turbofan engine control, the full flight envelope is divided to eight sub-regions and gain-scheduled control system where the sub-region controller could be switched with the change of the engine Mach number and altitude is constructed as the original work. The simulation results show the ability of the proposed control system in tracking the flight command, it is also verified that switching process has only slight effects on the engine condition under the control of the designed flight envelope controller.

Gain Scheduled PID Controller Design by Data-Driven Loop-Shaping Method

In this paper, a gain scheduled PID control system is constructed for a nonlinear plant whose steady state changes by the setpoint change. Our data-driven loop shaping method is applied to the direct design of PID gains using the plant input output response measured at several setpoints. The reference input is used for the scheduling parameter. Usefulness of our method is shown by simulation for a Hammerstein model.

Gain Scheduling Control System Synthesis of an Acrobot Based on SOS

Gain Scheduling Control System Synthesis of an Acrobot Based on SOS

Optimal gain-scheduled flight control system design using a new fuzzy clustering algorithm

This article presents an analytical framework for the design of autopilots using fuzzy systems. A new fuzzy clustering method is presented in this article, which is used to model a non-linear flight vehicle using a set of linear models. It is shown that the proposed fuzzy clustering technique produces lower estimation errors compared with other fuzzy clustering techniques; it means that the modelling error using the technique introduced is lower than other clustering methods. The membership functions and rule sets, which are obtained by fuzzy clustering, are then applied to a set of linear time-invariant optimal state-feedback controllers, obtained for each rule, towards extraction of the global non-linear controller matching closely with the dynamic properties and changes in the plant. The stability of the fuzzy model and the fuzzy system is established by the Lyapunov-based linear matrix inequality analysis. Simulation studies are reported to demonstrate the merits of the fuzzy set-based modelling and control approach in handling the demanding non-linear modelling and control task.

New Results on Linear Time Invariant and Parameter Varying Static Output Feedback

The increasing complexity of models related to future generation aircraft systems has encouraged the usage of linear parameter varying methodology with gain-scheduling control system configurations. This work presents new results on the design of static output feedback controllers by extending the H ∞ loop-shaping procedure to linear parameter varying models. In addition, an improved robustness measure is computed for both linear time invariant and linear parameter varying models. Extra constraints that guarantee closed-loop pole placement and a restricted structure for the static controller can also be imposed. Very promising results are illustrated by controller designs for both the lateral-directional and longitudinal dynamics of the F-16 aircraft.

Active control of shock by gain scheduling

In this paper, we deal with the active control of shock caused by the collision between two objects so as to make the deformation of the shock-receiving object large and the deformation of the shock-giving object small. Since the shock-receiving object deforms from the elastic range to the plastic range, we formulate a linear parameter-varying system to cover all the ranges and apply gain-scheduled (GS) control. Also, we utilize a frequency weighting function with varying gain in order to improve the performance of shock control. The GS control system exerts a continuous input when the deformation of the shock-receiving object changes from the elastic range to the plastic range. It is verified experimentally that the designed GS controller is effective for the active control of shock and that the plastic deformation ratio between the two objects is increased.

635 特性変動を有する外乱を受けるスマート構造の振動制御法

This paper proposes a multidisciplinary optimization approach of smart structures with disturbance characteristic variation. The control system and actuator locations are optimized by genetic algorithm according to H_2 specification with a reduced-order modal model derived from FEM and modal analysis. A gain-scheduled control system is applied to cope with the disturbance characteristic variation. This system estimates the disturbance characteristics continuously and then uses the appropriate scheduling gains against the estimated disturbance characteristics. The scheduling gains are optimized by genetic algorithm to enhance the vibration control performance under a constraint on the control cost, beforehand. A time-domain simulation and experiment have been carried out to verify the performance of the presented control system.

An Integrated Design of Structural and Gain Scheduled Control Systems

We deal with an integrated design problem of structural and gain scheduled control systems for LPV systems. The integrated design problem is formulated as an optimization problem of structural design parameters and a gain scheduled controller minimizing L2 gain of the closed-loop system. Even in the simplest case the integrated design problem is represented as a BMI problem which cannot be solved exactly and efficiently. In the present paper we propose an iterative LMI-based method to solve the formulated optimization problem approximately. We can guarantee the local convergence of the closed-loop L2 gain with the proposed design algorithm even if the coefficient matrices of the state-space form of the control object are nonlinear functions on the structural design parameters. We show the effectiveness of the proposed design method through a design example.

Postoperative blood pressure control using gain-scheduling controller

Postoperative hypertension is commonly found in cardiac patients, and untreated hypertension patients may develop severe complications. This paper presents a gain-scheduling control system for postoperative blood pressure management. The system is based on a controller bank designed a priori using multiple-model control. A tuning method, which can effectively select a suitable control output, is then adopted. Each controller in the controller bank is a non-linear Proportional-Integral (PI) controller. The proportional and integral gains of the controller are updated using the error and the change of the plant, so that a wide range of parameter changes and non-linearities of the plant can also be handled. In simulation study, a non-linear pulsatile-flow model is used. This model can accurately describe the patient's plant. The simulation results show that the proposed gain-scheduling control system can effectively handle the changes in the patient's dynamics and provide satisfactory control performance.