Quantitative Feedback Theory Design Research Articles

Comparison of Quantitative Feedback Theory Dependent Controller with Conventional PID and Sliding Mode Controllers on DC-DC Boost Converter for Microgrid Applications

This paper is discussed towards the issue of variations happening in the voltage control method of DC-DC boost converter. Quantitative feedback theory (QFT) is adjusted to efficiently plan a robust PID regulator, which is acknowledged utilizing only output voltage of the plant sensed by voltage sensor. The benefits of the explained PID configuration by utilizing the QFT design (Tarakanath Kobaku et al. 25) is proved with the fact that it disposes the problem of extra work and ad-hoc tuning of PID gain utilizing the regular PID methods, current measurement isn’t needed, it provides the design for case of non-minimum phase of boost converter even if there is restrictions on the bandwidth and disturbance factors are already included in the design of QFT based controller with the help of QFT bounds and thus disturbance effect is considered in the output of system. Various simulation results are taken in each case i.e. conventional PID controller and sliding mode controller. Here results are compared with the QFT based controller to verify the importance of this controller over other two controllers in terms of output response, reference tracking, line regulation and most importantly on the basis of cost effectiveness.

Automated QFT-Based PI Tuning for Speed Control of SynRM Drive with Analytical Selection of QFT Control Specifications

The gains of PI controllers, used in the cascaded speed control of synchronous reluctance motors (SynRMs), are synthesized using quantitative feedback theory (QFT). A systematic design approach is employed to quantitatively determine the PI controller gains in terms of speed and current loops, using a mathematical model of the SynRM. Further, to make the QFT design a more transparent method, an analytical procedure using the frequency domain is attempted to design the QFT bounds as well as the initial search space of the optimization algorithm used in automatic loop shaping. The effectiveness of the proposed PI tuning method is verified with the extensive MATLAB/Simulink simulation environment. The results illustrate the supremacy of the proposed PI tuning method, in terms of control performance, over the conventional PI tuning method, using the analytical procedure.

Quantitative Feedback Theory Control to Improve Stability in DC Catenary Feeding Traction and Auxiliary Drives

The progressive electrification of railways involves an increasing number of power electronic converters connected to the railway catenary, which may compromise its stability. Both the converter for traction and the converter for auxiliary power systems (APS) behave as constant power loads (CPL) and interact negatively with the catenary impedance producing voltage instability. This article applies quantitative feedback theory (QFT) to design an ac voltage controller for the APS converter that shapes the dc input admittance of the converter by performing only ac side-control without a dc-side feedback loop. The QFT enables to design a low order controller that satisfies multiple performance specifications in systems with high uncertainty as is the case of the train system. The proposed control guarantees catenary stability while ensuring ac output voltage reference tracking and providing robustness to unmodeled uncertainties. As an additional contribution, the article presents an algorithm for including input admittance specifications in the QFT design process. The proposed control has been evaluated on an experimental platform that recreates the train system. Experimental results show that the controlled system meets railway standards and correctly shapes the specified dc input impedance.

Robust semiactive control of a half‐car vehicle suspension system with magnetorheological dampers: Quantitative feedback theory approach with dynamic decoupler

AbstractThis article presents the quantitative feedback theory (QFT) based multivariable controller for the vertical and the pitch angle motion of a half‐car suspension system. A coupled half‐car system with significant uncertainty, due to sprung masses variation, poses a challenging control problem. Multi‐input multi‐output (MIMO) QFT method is used for this purpose which involves converting the actual MIMO system into an equivalent single‐input single‐output (SISO) system so that the design problem is carried out using the SISO QFT principles. The proposed idea is centered on by converting the coupled MIMO system into a decoupled one using the dynamic decoupler where in controllers are designed independently based on the equivalent SISO system. The designed QFT‐based controllers with the decoupler use the semiactive suspension strategy (realized using the magnetorheological (MR) damper) to reduce the vibration of the half‐car suspension system (in vertical/pitch angular motion) and hence to increase the ride comfort and the vehicle road holding. The feedback cost is less in the proposed design than the sequential QFT design. In this study, the MR damper dynamics is captured by the first‐order model which is realistic, efficient, and simple form. Extensive comparative simulation studies are carried out to illustrate the effectiveness of the proposed design over the existing methods such as passive and skyhook control under different road excitation.

Quantitative Feedback Theory design of valve position control for co-ordinated superheater control of main steam temperatures of power plant boilers

Abstract This paper presents an application of a Single-Input Single-Output (SISO) controller and a Valve Position Controller (VPC) using robust Proportional-Integral (PI) controllers designed using Quantitative Feedback Theory (QFT) specifications to control superheater outlet steam temperatures of a 600MW once-through boiler. To illustrate the methodology, a dynamic model of a tower-type boiler was modelled using Flownex® to test the VPC design application with structured uncertainty under varying load and disturbance conditions. The results show that the valve position controller application is more efficient than the SISO technique, allowing the final attemperator more bandwidth to deal with unexpected temperature changes.

Robust Motion Control Using Combined Centralized Non-Integer Pre-Filter of Type FBLFD and Fractional Order Pdμ Controller

Designing and automation of a robust controller and pre-filter for multi-variable processes are a very challenging task. In this study, an automated and simple conception of multi- variable QFT (QFT: Quantitative Feedback Theory) is proposed using fractional order controllers design. Contrary to the traditional manual QFT design, our methodology consists of obtaining all required performances in QFT without going to the QFT loop shaping process.A non-integer order proportional derivative controller PDμ is conceived for a robust control of MIMO (Multi Input Multi Out- put) systems through multi-objective optimization based genetic algorithm . In the designed approach an implicit fractional order pre-filter FBLFD (FBLFD : Frequency Band Limited Fractional Differentiator) is adopted and its parameters are optimized. A diagonal version of this fractional order pre-filter and a non diagonal one are proposed. The problem of loop interactions is eliminated by the non diagonal designed pre-filter. Consequently, the procedure of fractional controller and pre-filter parameters optimization is illustrated. A comparative study and the efficiency of the developed methodologies are considered through SCARA robot.

Dynamic analysis and qft-based robust control design of a coaxial micro-helicopter

This paper presents the dynamic behavior of a coaxial micro-helicopter, under Quantitative Feedback Theory (QFT) control. The flight dynamics of autonomous air vehicles (AAVs) with rotating rings is non-linear and complex. Then, it becomes necessary to characterize these non-linearities for each flight configuration, in order to provide these autonomous air vehicles (AAVs) with autonomous flight and navigation capabilities. Then, the nonlinear model is linearized around the operating point using some assumptions. Finally, a robust QFT control law over the coaxial micro-helicopter is applied to meet some specifications. QFT (quantitative feedback theory) is a control law design method that uses frequency domain concepts to meet performance specifications while managing uncertainty. This method is based on the feedback control when the plant is uncertain or when uncertain disturbances are affecting the plant. The QFT design approach involves conventional frequency response loop shaping by manipulating the gain variable with the poles and zeros of the nominal transfer function. The design process is accomplished by using MATLAB environment software.

Quantitative Feedback Theory design of robust MPPT controller for Small Wind Energy Conversion Systems: Design, analysis and experimental study

This paper addresses the design of a robust Maximum Power Point Tracking (MPPT) controller for a small wind energy conversion system fed by a Permanent Magnet Synchronous Generator (PMSG). The proposed MPPT controls the generator rectified voltage instead of the rotational speed avoiding the need for a mechanical sensor. Traditionally, this control problem is performed using a Proportional Integrator (PI) controller optimised at a specific operating point. However, the PI controller does not guarantee the promising transient performance under changing operating conditions. In this work, the Quantitative Feedback Theory (QFT) has been applied to synthesis a robust DC-voltage controller to ensure a robust stability and tracking specifications for all operating points. The performance of the designed controller has been compared with the classical PI controller experimentally on laboratory benchmark. The experimental results prove that the proposed controller outperforms the conventional PI controller reducing the overshoot between 26.67% and 82.53% and the response time between 36.36% and 71.33%, reducing by the way the mechanical stress on the PMSG under a turbulent wind speed profile. In addition, the extracted electrical energy using the proposed controller over 90 s of a typical wind speed profile is 1.7015% higher.

A New Scheduling Quantitative Feedback Theory‐Based Controller Integrated with Fault Detection for Effective Vibration Control

In this work, a new integrated fault detection and control (IFDC) method is presented for single‐input/single‐output systems (SISOs). The idea is centered on comparing the closed‐loop output between the faulty system and fault‐free one to schedule/switch the feedback control once the fault occurs. The problem addressed in this work is the output disturbance rejection. The set of feedback controllers are designed using quantitative feedback theory (QFT) for fault‐free and faulty systems. In the context of QFT‐based IFDC, the proposed active approach is novel, simple, and easy to implement from an engineering point of view. The efficiency of the proposed method is assessed on a flexible smart structure system featuring a piezoelectric actuator. The actuator and sensor faults considered are the multiplicative type with both fixed and time‐varying magnitudes. In the fixed magnitude fault case, the actuator/sensor output delivering capability is reduced by 50% (multiplying a factor of 0.5 to its actual output), while in the time‐varying magnitude case, it becomes 60% to 50% for a particular time interval. In both cases, the proposed control method identifies the fault and activates the required controller to satisfy the specification with less control effort as opposed to the passive QFT design featured by faulty system design alone.

A novel semi-active control strategy based on the quantitative feedback theory for a vehicle suspension system with magneto-rheological damper saturation

This paper presents a robust controller for a semi-active suspension system with actuator saturation. It addresses the vehicle vibration attenuation problem under two cases: (i) without actuator fault (magneto-rheological (MR) damper) and (ii) with base oil leakage in MR damper. The solution is obtained using the quantitative feedback theory (QFT) design. The actuator (MR damper) dynamics is well approximated by a first order model with an uncertain time constant. The superior performance of the proposed QFT controller, for fault free case, is compared with the sky-hook, H∞ control and passive suspension in time as well as in frequency domains. To address the system with faulty MR damper, a multiple model approach based QFT design is then proposed. The multiplicative type fault is considered as an MR damper fault and the faulty damper output delivering capability is then reduced by 80% to 75% due to the oil leakage in the damper. The proposed idea is centered on dividing the large uncertain system into a set of small uncertain linear system and then design the QFT controller corresponding to each of the generated linear models. The global controller is formulated by aggregating the local controller with the gap metric based weights. This new approach produces the similar performance as that of the passive fault tolerant control (FTC)-QFT design with less control effort. Extensive comparative simulations are provided to show the efficacy of the proposed method over passive FTC-QFT, passive FTC-H∞ design and sky-hook control.

Non-diagonal multivariable fractional prefilter in motion control

A novel approach for robust Commande Robuste d'Ordre Non Entier (CRONE) control of multi input multi output (MIMO) systems using quantitative feedback theory (QFT) design is discussed through fractional prefilters with off-diagonal elements. More design flexibility is guaranteed when using the non-diagonal prefilter. For a given system, the CRONE control approach is combined with QFT design to get the controller matrix. After that, the classic diagonal fractional prefilter expression is extended to a fully populated prefilter matrix. The Davidson-Cole fractional prefilter optimisation is used to determine the diagonal terms of prefilter. The role of the off-diagonal elements of prefilter is to eliminate loop interactions in the case of reference tracking. So a sequential design procedure is proposed in order to get the fully populated prefilter matrix elements. The performance of the novel methodology is finally verified by adopting the designed prefilter and controller to govern the MIMO SCARA robot model.

Non-diagonal multivariable fractional prefilter in motion control

A novel approach for robust Commande Robuste d'Ordre Non Entier (CRONE) control of multi input multi output (MIMO) systems using quantitative feedback theory (QFT) design is discussed through fractional prefilters with off-diagonal elements. More design flexibility is guaranteed when using the non-diagonal prefilter. For a given system, the CRONE control approach is combined with QFT design to get the controller matrix. After that, the classic diagonal fractional prefilter expression is extended to a fully populated prefilter matrix. The Davidson-Cole fractional prefilter optimisation is used to determine the diagonal terms of prefilter. The role of the off-diagonal elements of prefilter is to eliminate loop interactions in the case of reference tracking. So a sequential design procedure is proposed in order to get the fully populated prefilter matrix elements. The performance of the novel methodology is finally verified by adopting the designed prefilter and controller to govern the MIMO SCARA robot model.

An interval-consistency-based hybrid optimization algorithm for automatic loop shaping in quantitative feedback theory design

A computationally efficient method for automatic synthesis of quantitative feedback theory (QFT)-based robust controllers is proposed. The synthesis problem consists of obtaining a fixed structure QFT controller that ensures stability and achieves the performance specifications in the presence of disturbances and parametric uncertainty. The proposed method uses an interval consistency technique (hull consistency HC4) and hybrid optimization. The HC4 method is used to remove inconsistent values, which are not part of the solution in the controller parameter regions. The hybrid part incorporates interval global optimization and nonlinear local optimization methods. The proposed algorithm is illustrated by means of two examples. The first one concerns the longitudinal motion control of an aircraft system (flexible), while the second one describes the experimental study of the position control of the industrial plant emulator setup. The robustness of the designed control system for emulator setup is validated by adding extra weights on the load disk in the presence of disturbances. The experimental results show that the designed controller satisfies the robust performance specifications.

Design of robust fractional-order controllers and prefilters for multivariable system using interval constraint satisfaction technique

Design of robust controller for multivariable systems is very challenging and their automation is a key concern in control system design. In this paper, a new, simple, and reliable automated fractional-order multivariable Quantitative Feedback Theory (QFT) controllers design methodology is proposed. A fixed structure fractional-order multivariable QFT controller has been synthesized by solving QFT quadratic inequalities of robust stability and tracking specifications. The quadratic inequalities (constraints) are posed as Interval Constraint Satisfaction Problem (ICSP). The constraints are solved by constraint solver-RealPaver. The synthesis problem consists of obtaining a controller that ensures stability and meets a given set of performance specifications, in spite of disturbance and model uncertainties. In addition to perform the above tasks, a MIMO controller also has to perform the difficult task of minimizing interaction between the various control loops. Unlike existing manual or convex optimization based QFT design approaches, the proposed method gives a controller which meets all performance requirements in QFT, without going through the conservative and sequential design stages for each of the multivariable sub-systems. In the design method, we pose the prefilter design problem as an ICSP and solve it using the well-established constraint solver. The designed controllers and prefilters are tested for a quadruple tank process and their efficacy is demonstrated.

Robust Air-to-Fuel Ratio and Boost Pressure Controller Design for the EGR and VGT Systems Using Quantitative Feedback Theory

This paper describes robust multi-input, multi-output controller for the exhaust gas recirculation (EGR) and variable geometry turbocharger (VGT) systems of passenger car diesel engines. The air-to-fuel ratio of the exhaust gas and boost pressure of the intake manifold were selected as performance indicators in this paper. To enable the online calibration of the controller, proportional-integral-derivative (PID) was used as a feedback controller. Using quantitative feedback theory (QFT), two control loops for air-to-fuel ratio and boost pressure were independently designed with linearized models and parameter uncertainties. The prefilters and PID gains of two control loops were designed for satisfying required robust stability and tracking performance using the QFT design framework. Furthermore, the problems originated from the cross-coupled dynamics between the EGR and VGT systems were mitigated by a static decoupler. Using the proposed design steps, PID and decoupler gains of the representative 15 engine operating points which are mainly used in New European Driving Cycle were obtained. The proposed controller was validated through various test conditions of engine experiments. From the step responses and transient experiments, it was demonstrated that the required robustness and tracking performance were successfully achieved.

Robust PID controller design using particle swarm optimization-enabled automated quantitative feedback theory approach for a first-order lag system with minimal dead time

This paper presents the design of a robust proportional integral and derivative (PID) controller for a first-order lag with pure delay (FOLPD) model using particle swarm optimization (PSO)-enabled automated quantitative feedback theory (QFT). The plant model considered here can be approximated as a first-order system with a non-minimum phase (NMP) zero. Synthesis of controller for the FOLPD model via manual graphical technique involved in the QFT method is always a challenging and cumbersome task, because an NMP system stabilizes by a small gain. In this paper, a proposal is being presented to automate the loop-shaping phase in the QFT design method to synthesize a robust controller that can undertake the exact amount of plant uncertainty even in the presence of larger uncertainties than those assumed initially and can ensure a proper trade-off between robust stability and tracking performance specifications over the entire range of design frequencies. In this paper,s the PSO technique has been employed to tune the controller automatically,which can significantly reduce the computational effort compared with manual graphical techniques. It has also been demonstrated that this methodology not only automates loop shaping but also improves design quality and, most usefully, improves performance with optimally tuned PID controller in quantitative manner.

Quantitative Feedback Theory Design of Line Current Commutated HVDC Control Systems

Line Current Commutated (LCC) HVDC systems consists of uncertain plants. These uncertainties are result of changes/disturbances in the ac networks or in the LCC HVDC system itself. Further uncertainties can be introduced due to simplified system modelling

Robust Water Level Control of the U-Tube Steam Generator

In this paper, a new practical robust water level control system for the U-tube steam generator (UTSG) using the quantitative feedback theory (QFT) is proposed. The steam generator is a nonlinear uncertain plant. However, the steam generator behaves as a linear uncertain and nonminimum phase plant at its different operating points, which makes its control a challenging problem. The control problem is to design controllers such that the closed-loop plant satisfies the robust stability, disturbance rejection, and robust tracking specifications that are derived from a desired steam generator performance. In the QFT design methodology, these specifications are satisfied by generating the plant templates, the composite bounds, and a nominal plant loop shaping procedure to satisfy these bounds. Simulation results reveal that the designed QFT water level controllers will ensure all the designers’ closed-loop specifications. Also, comparison results are provided that show the effectiveness of the robust QFT controllers with respect to the previously employed internal model-based controller.

Design Procedure of Robust QFT-Based Controller for Continuous-Flow Grain Dryer Plant

Quantitative Feedback Theory (QFT) is a well known robust controller that deals with plant uncertainty. QFT has been applied to many industrial applications, however it never been applied to any types of grain dryer plant. Grain dryer plant prone to parameter uncertainty and needs a robust controller in order to maintain a good quality of product output. The objective of this paper is to explain step-by-step design procedure of QFT design for a continuous-flow grain dryer plant. The designed QFT-based controller is also tested and compared with PID controller via simulation. The test results showed that the QFT-based controller works better than PID controller in terms of shorter settling time and smaller percentage of overshoot for the grain dryer plant under study and at the same time insensitive to parameter changes i.e. input and output disturbances.

A robust anti-windup design procedure for SISO systems

A model-based anti-windup (AW) controller design approach for constrained uncertain linear single-input–single-output (SISO) systems is proposed based on quantitative feedback theory (QFT) loopshaping. The design approach explicitly incorporates uncertainty, is suitable for the solution of both the magnitude and rate saturation problems, and provides for the design of low-order AW controllers satisfying robust stability and robust performance objectives. Robust stability is enforced using absolute stability theory and generic multipliers (i.e. circle, Popov, Zames–Falb), and robust performance is enforced using linear lower-bounds on the input–output maps capturing the effects of saturation as a metric. Two detailed design examples are presented. These show that even for simple systems, certain popular AW techniques lead to compensators that may fail to ensure robust stability and performance when saturation is encountered, but that the proposed QFT design approach is able to handle both saturation and uncertainty effectively.