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In our industry, active disturbance rejection control already has been used to enhance the performance of the electro-hydraulic servo systems, despite the fact that electro-hydraulic servo systems are usually reduced to first-order and second-order systems. The aim of this paper is to extend the application of active disturbance rejection control to high-order electro-hydraulic servo systems by introducing a new tuning method. Active disturbance rejection control is transformed into two separate parts in the frequency domain: a pre-filter H (s) and a controller T (s) . The parameters of the pre-filter and controller can be tuned to satisfy the performance requirements of high-order electro-hydraulic servo systems using quantitative feedback theory. To assess the efficacy of the proposed tuning approach, simulations and an application of a third-order electro-hydraulic servo system have been carried out and the stability of the application with an improved active disturbance rejection controller is analyzed. The results of simulations and experiments reveal that the new tuning method for high-order electro-hydraulic servo systems can obtain a better performance than the bandwidth tuning method and other methods. [ABSTRACT FROM AUTHOR]

In our industry, active disturbance rejection control already has been used to enhance the performance of the electro-hydraulic servo systems, despite the fact that electro-hydraulic servo systems are usually reduced to first-order and second-order systems. The aim of this paper is to extend the application of active disturbance rejection control to high-order electro-hydraulic servo systems by introducing a new tuning method. Active disturbance rejection control is transformed into two separate parts in the frequency domain: a pre-filter H(s) and a controller T(s). The parameters of the pre-filter and controller can be tuned to satisfy the performance requirements of high-order electro-hydraulic servo systems using quantitative feedback theory. To assess the efficacy of the proposed tuning approach, simulations and an application of a third-order electro-hydraulic servo system have been carried out and the stability of the application with an improved active disturbance rejection controller is analyzed. The results of simulations and experiments reveal that the new tuning method for high-order electro-hydraulic servo systems can obtain a better performance than the bandwidth tuning method and other methods.

This paper addresses the regulation of water quality influencers such as Organic Nitrogen, Ammonia Nitrogen, Nitrate Nitrogen, Dissolved Organic Carbon and Dissolved Oxygen for a sub-surface flow horizontal wetland in a controlled environment. The plant uncertainty is quantified by using measurement data. The robust control of the process is achieved using a decentralized quantitative feedback theory based control strategy. The control structure also employs a feed-forward mechanism to minimize loop interactions and feedback control to ensure stability, tracking and disturbance rejection. The numerical simulations and hardware-in-loop implementation show that the performance specifications are robustly met. • The control of water quality deciding variables by using a constructed wetland • The parametric uncertainty is quantified using measurement data collected • A decentralized quantitative feedback theory based robust controller is adopted • Each loop is equipped with feed-forward controllers to minimize coupling effects • Performance is verified by numerical simulation and hardware-in-Loop validation [ABSTRACT FROM AUTHOR]

This paper proposes a new parameter tuning approach for active disturbance rejection control (ADRC) of multi-input multi-output (MIMO) uncertain systems. Firstly, decentralized ADRC (DADRC), dynamic decoupling ADRC (DD-ADRC), and inverted decoupling ADRC (ID-ADRC) are introduced. Three control schemes are uniformly transformed into a two-degree-of-freedom (2DOF) equivalent structure for analysis. Then, a parameter tuning approach based on multivariable quantitative feedback theory (QFT) is proposed to achieve the desired performance. Considering the coupling effects, the QFT performance specifications are reformulated to reduce the conservatism in design, and the closed-loop stability conditions are studied to establish the robust stability performance specification. Finally, the control schemes and the proposed tuning approach are applied to a heat integrated distillation column (HIDiC) process. The effectiveness of the parameter tuning approach is verified, and the respective advantages of the ADRC control schemes are analyzed in parameter tuning and simulations. • A parameter tuning approach based on quantitative feedback theory is proposed. • Performance specifications are reformulated to reduce conservatism in design. • Closed-loop stability conditions are studied to establish robust stability performance specifications. • The stability and disturbance rejection performance are analyzed and compared. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of controlling turbidity, dissolved oxygen, ammonium‐ion concentration, and water‐temperature to maintain the desired water quality in an intensive aquaculture plant. The research is carried out to fit into the present scenario of intensive aquaculture in India. The plant model along with uncertain parameters are derived using physical laws and the data acquired from an aquaculture pond in Assam, India. A pre‐compensated multi‐variable quantitative feedback theory (QFT)‐based fully populated robust matrix controller is proposed to mitigate the control challenge. A novel method is used to design the pre‐compensator to enhance the diagonal dominance of plant transfer function matrix. The desired robust stability, reference tracking, and sensitivity specifications are fulfilled by the proposed QFT‐based robust controller despite the parametric uncertainty. The effectiveness of the proposed method is validated through numerical simulation. A comparative study against a H∞$$ {H}_{\infty } $$ controller shows that the proposed controller strategy gives a satisfactory performance compared to it. [ABSTRACT FROM AUTHOR]

One of the most critical problems in all practical systems is the presence of uncertainties, internal and external disturbances, as well as disturbing noise, which makes the control of the system a challenging task. Another challenge with the physical systems is the possibility of cyber-attacks that the system’s cyber security against them is a critical issue. The systems related to oil and gas industries may also be subjected to cyber-attacks. The subsets of these industries can be mentioned to the oil and gas transmission industry, where ships have a critical role. This paper uses the Quantitative Feedback Theory (QFT) method to design a robust controller for the ship course system, aiming towards desired trajectory tracking. The proposed controller is robust against all uncertainties, internal and external disturbances, noise, and various possible Deception, Stealth, and Denial-of-Service (DOS) attacks. The robust controller for the ship system is designed using the QFT method and the QFTCT toolbox in MATLAB software. Numerical simulations are performed in MATLAB/Simulink for two case studies with disturbances and attacks involving intermittent sinusoidal and random behavior to demonstrate the proposed controller.

This article presents the control of Soil moisture, Nitrogen, and Salt content in soil using a robust control technique to maintain a desired quality of soil in a drip irrigated field. The control of this multi-variable system is accomplished by adopting two possible control structures namely (i) a decentralized controller backed by a feed-forward controller (ii) a diagonal centralized de-coupler along with a diagonal controller. The controllers are designed using quantitative feedback theory. The efficacy of the proposed techniques is validated through numerical simulations. A comparative study among the two methods reveals that the former performs better than the later. Another comparative study shows that the proposed controller outperforms some of the reported works. • Control of Soil moisture, Nitrogen and Salt content in a drip irrigated field. • A 3 × 3 uncertain model is derived from physical laws and practical data. • De-centralized QFT along with feed-forward controllers is proposed. • Centralized decoupler with diagonal QFT based controllers is proposed. [ABSTRACT FROM AUTHOR]

Previous studies compare quantitative feedback ratings of student peers and instructors, but new presentation-feedback technologies enable qualitative-feedback comparison. This study extends previous research by comparing qualitative feedback and business professionals' feedback. Compared to the professionals, the instructors provided similar feedback types and sentiment; students, however, de-emphasized message delivery and made fewer suggestions for improvement. The results suggest that students may need additional practice in critiquing message delivery and in suggesting needed improvements in their peers' oral presentations. The study also provides a methodology using the new technologies for instructors to calibrate their own and their students' feedback with professionals' feedback. [ABSTRACT FROM AUTHOR]

In the renewable energy consumption scheduling, due to the large fluctuation of wind power output, the renewable energy consumption rate is low, and the energy consumption scheduling effect is poor. Therefore, a new renewable energy consumption scheduling model based on quantitative feedback theory is designed. For the first time, calculate the output response of wind power generation, obtain the output change rate of the wind farm at the time scale, and determine the response curve of wind power generation according to the power generation process is divided into three stages: the initial stage, the peak stage and the end stage, and the response output during the peak period, so as to obtain the transfer rate of output during the peak period. Build a mathematical model of renewable energy power generation, calculate the output state of wind power generation, and analyze the output characteristics of renewable energy storage system; Secondly, the objective weight coefficient of renewable energy consumption is determined by using quantitative feedback theory, the objective function of renewable energy consumption is constructed, the power injected by parameter nodes is determined, the quantitative feedback controller is designed by using loop shaping technology, the control structure of two degrees of freedom is determined, the objective function of renewable energy consumption is constructed, and the constraint range of renewable energy consumption capacity is determined according to static constraints such as current constraints and voltage constraints; Then, the quantitative feedback theoretical controller is designed, the input and output transfer functions of the consumption system are determined, and the renewable energy consumption scheduling model is constructed. The renewable energy consumption scheduling model is solved by particle swarm optimization through a variety of index parameters in the renewable energy consumption determined by the QFT controller. The experimental results show that the proposed model can effectively improve the renewable energy consumption rate and optimize the consumption scheduling effect. [ABSTRACT FROM AUTHOR]

This brief reports a novel method of synthesizing a robust PID controller for regulating boost DC-DC converter that exhibits non-minimum phase (NMP) dynamics and complex-conjugate poles in its linear model. The NMP dynamics restrict the achievable closed-loop bandwidth and make tuning of PID parameters a difficult task. To solve this problem, the proposed design method uses the Quantitative Feedback Theory (QFT) in conjunction with particle swarm optimization (PSO) to carry out automatic loop-shaping. Due to the global optimization capability of PSO, the proposed multi-objective function approach with PID simplifies the loop-shaping to compensate the converter having complex-conjugate zeros. An attractive feature of this design method is that it accounts for the worst-case scenario due to parametric variations in the converter model. The real-time simulation results and the experiments reveal the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the design of a robust controller for a quadrotor unmanned aerial vehicle (UAV) system subject to parameter uncertainties and external disturbances. A new double closed-loop active disturbance rejection generalized predictive control (ADRC-GPC) is proposed for the trajectory tracking problem of the UAV. Considering the measurement noise, the ADRC-GPC control strategy can provide better dynamic performance and robustness against uncertainties and external disturbances than active disturbance rejection control (ADRC). Furthermore, a controller parameter tuning method for ADRC-GPC is proposed. In the framework of the classical two-degree-of-freedom equivalent model, the bandwidth of ESO is determined according to the parameter selection criterion. The criterion is a trade-off between the estimation accuracy and the immunity of measurement noise. In addition, the parameters of the ADRC-GPC controller are tuned by quantitative feedback theory to achieve the expected performance specifications. Finally, the proposed method is compared with several traditional control methods in the simulation experiments. The simulation results show that the proposed method has better set-point tracking performance, disturbance rejection performance, and robustness.

One of the most critical problems in all practical systems is the presence of uncertainties, internal and external disturbances, as well as disturbing noise, which makes the control of the system a challenging task. Another challenge with the physical systems is the possibility of cyber-attacks that the system's cyber security against them is a critical issue. The systems related to oil and gas industries may also be subjected to cyber-attacks. The subsets of these industries can be mentioned to the oil and gas transmission industry, where ships have a critical role. This paper uses the Quantitative Feedback Theory (QFT) method to design a robust controller for the ship course system, aiming towards desired trajectory tracking. The proposed controller is robust against all uncertainties, internal and external disturbances, noise, and various possible Deception, Stealth, and Denial-of-Service (DOS) attacks. The robust controller for the ship system is designed using the QFT method and the QFTCT toolbox in MATLAB software. Numerical simulations are performed in MATLAB/Simulink for two case studies with disturbances and attacks involving intermittent sinusoidal and random behavior to demonstrate the proposed controller. [ABSTRACT FROM AUTHOR]

This article proposes a novel method, inspired from eigen decomposition technique, to design a quantitative feedback theory (QFT) based robust controller for a multiple input multiple output (MIMO) uncertain plant. The proposed method is a direct and sufficiently generalized one. Unlike existing practice, it does not require to transform a "n×n" MIMO‐QFT based design problem into "n" sequential multiple input single output QFT based design problems. Apart from the frequency dependency, the frequency response of a MIMO system also has the spatial dependency. This makes the frequency domain analysis and design for a MIMO system, more challenging than its SISO counterpart. Three new concepts namely directional transfer ratio (DTR), output directionality (OD), and principle of control along characteristic vectors (PCCV) are introduced to take care of the complexities of the frequency response of a MIMO feedback system. The DTR, OD, PCCV and existing techniques of QFT are combined together to develop the proposed design method. A case study is presented considering a "2×2" ill‐conditioned plant to illustrate the method. The proposed method is expected to open up new avenues in the area of MIMO‐QFT based design. [ABSTRACT FROM AUTHOR]

Once an infectious disease has become an epidemic and can no longer be contained, non‐pharmaceutical public health interventions may be used to reduce infection rates so as to control demand on health care resources including staff and hospital facilities. Feedback control is shown to have limited possibilities due to (often unmodeled) non‐minimum phase lag; uncertainty in model parameters and measurements; and the discrete time nature of practical controller implementation for the interventions. Classical susceptible‐exposed‐infected models do not capture real time delays in disease progression, or phase lag effects of discrete time feedback control. Non‐minimum phase lag constraints are more severe if the number of hospitalized individuals rather than the number of infected individuals is used as the measurement variable. [ABSTRACT FROM AUTHOR]

This paper examines methods to incorporate feedforward loops of known external inputs (output reference) into a multi-input feedback control structure to achieve certain robust performance of its output. Undoubtedly, feedforward can reduce the need for feedback and therefore the amplification of sensor noise at actuators, as occurs in single-input control. Beyond that, since there are several available inputs, a convenient distribution of feedforward and feedback can minimise the control action at each input and offer benefits at all frequencies. The procedure is as follows: because there are rough plant models of the behaviour from each input to the output, it is possible to approximate the individual control demand that will satisfy the performance. Based on this, individual feedforward filters allocate the control bandwidth among the inputs in order to build an equivalent plant that has an equal or greater magnitude than any individual plant at each frequency. Next, the uncertainty of this equivalent plant is addressed by feedback that reduces the closed loop deviation of magnitude frequency responses. The reduction is sufficient to enable a master feedforward to place them, at a second step, around the desired tracking performance model without violating any deviation tolerances. Individual feedback controllers distribute the total feedback among the inputs in order to have the least possible feedback at each frequency. A first example illustrates the method and the relevance of a feedforward orientation to reduce the individual control action, instead of the individual feedback action. Another example proves the superiority of adding feedforward loops to feedback-only schemes and highlights the benefits of robust design methods such as Quantitative Feedback Theory (QFT). This paper also provides the algorithms to employ in response to new robust control specifications in the framework of QFT.

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.

A dual‐rate control system is a hybrid system composed of continuous‐time and discrete‐time elements with two sampling frequencies. In this work, a new frequency domain analysis and design approach, based on the quantitative feedback theory is developed, to cope with robust stability and robust tracking specifications. Tracking specifications are considered not only in the discrete‐time but also in continuous‐time, that allow a precise description of the intersample behavior (ripples), and characterization of frequencies below and beyond the Nyquist frequencies. Several illustrative examples and a case study has been developed. [ABSTRACT FROM AUTHOR]

Like other multi-input multi-output (MIMO) systems, adverse effects of interactions among control loops on the system performance is one of the most challenging issues in the control of microgrids (MGs). In this paper, a robust MIMO controller is proposed for the MGs to solve the problem of power sharing among its distributed generators systematically. To this end, the relative gain array (RGA) matrix is used to address the problem of input-output pairing, and adverse effects of interactions among the control loops are decreased by designing proper pre-compensators. The sequential loop closing technique is employed, and the quantitative feedback theory (QFT) is used to achieve robust stability, the robust tracking performance, and the desired level of disturbance attenuation for all the control loops. The simulation and experimental results reveal the desirable and acceptable performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This proposed work deals with the real-time implementation of a PI level controller for a nonlinear interacting multi-input multi-output (MIMO) system using YOKOGAWA CENTUM CS 3000 DCS. Some intricate algorithms were chosen to tune the PI controller, presuming the effect of disturbances in a nonlinear interacting MIMO system. Three algorithms; a classical evolution algorithm, genetic algorithm (GA); a metaheuristic optimization algorithm, particle swarm optimization algorithm (PSO); and a robust algorithm, quantitative feedback theory (QFT) were chosen to tune the controller offline optimally. These controllers were then implemented in the process using distributed control systems (DCS), and the simulation results resulting from the three algorithms were compared with the experimental results. The impact of the tuning algorithms in the controller performance was studied in real-time.

Increasing penetration of renewable energy sources based on power electronic interfaces in traditional power systems reduces the inertia constant and damping coefficient. It also increases uncertainty and the sensitivity of the system to disturbances. The concept of the virtual synchronous generator (VSG) is used to emulate the inertia constant and damping property like a synchronous generator. It can be shown that all given VSG structures have the same dynamics as the proportional-integral-derivative (PID) controller. In this paper, the quantitative feedback theory (QFT) is used to tune the VSG parameters such that robust system stability and performance are guaranteed. Moreover, the desired disturbance attenuation is also taken into account. Through frequency response analysis and time-domain simulations, it is shown that the proposed strategy can be successfully used to solve the load-frequency control problem in islanded microgrids (MGs). In addition, the proposed QFT-based VSG is compared with another robust VSG designed by the well-known $H_\infty$ technique to illustrate its better performance against disturbances. [ABSTRACT FROM AUTHOR]

The quest for an efficient quantitative feedback theory (QFT) Automatic Loop Shaping algorithm is an open research problem. Different approaches have been adopted in the literature to efficiently solve this optimization problem, which is computationally hard due to its nonlinear and nonconvex nature. The first algorithms focused on different forms of simplification of the original problem, leading to faster but not accurate results. Stochastic algorithms have been another popular way of dealing with the complexity of this problem. These algorithms are faster than an exhaustive search, but do not guarantee, in general, the globally optimal solution. A third, more recent, approach, consists of using interval analysis global search algorithms, which are able to accurately solve the original problem, and are very suitable for execution speed optimization. In this work, one of these algorithms is taken as a basis to propose and develop an improved algorithm which is more efficient in terms of the execution time needed to solve a given problem. This improved efficiency is achieved by using two new information sources: Phase information and feasible boxes information. The main contribution of this work is to propose the use of these two new information sources to reduce execution time and to integrate this idea in the original algorithm. Their individual and joint associated speedups are measured by solving two classical QFT example problems: Matlab® QFT Toolbox example 2 and ACC '90 benchmark problem. The results show that the new algorithm's performance is significantly better. [ABSTRACT FROM AUTHOR]

In this paper, a control scheme based on feedback linearization technique and quantitative feedback theory (QFT) is used to regulate the inner diurnal temperature in a greenhouse located in the south of Spain. In a first step, a non-linear model for the greenhouse is used to design a feedback linearization controller, which provides the vents opening percentage from a virtual control signal provided by a robust proportional integral (PI) controller. The relation between the system output (inside temperature of the greenhouse) and the virtual control signal is given by a first order plus dead time (FOPDT) system. The values for the three parameters of this linear model are identified in the experimental greenhouse by applying several step changes in the virtual control signal and analyzing the process response. Different values for gain, the time constant, and time delay are identified. So, this uncertain linear description for the system is used to design a quantitative feedback theory (QFT) controller with a PI structure. Finally, experimental results are analyzed showing satisfactory performance of the proposed control approach.

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This 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. [ABSTRACT FROM AUTHOR]

In the refining and chemical industry, distillation is one of the prime processes and is a multivariable control problem, which involves interaction amongst several control loops and exhibit dead time in the dynamic behavior. The analysis and controller design of processes inheriting dead time is a challenging task, and the presence of plant uncertainties and disturbances makes it challenging to exert quality control over time. In this paper, a template and bounds free approach is explored for the simultaneous synthesis of quantitative feedback theory (QFT) based robust controller and pre-filter for Wood and Berry distillation column with multiple time delays. This presented method simplifies the QFT controller synthesis for MIMO systems and eliminates the need of ' Schauder fixed point theory ' to express the m × m MIMO system into analogous m 2 MISO plants before the QFT controller synthesis. Using the presented approach, an optimal MIMO QFT controller and pre-filter are synthesized in a single step, which else conventionally follows a long sequential design process. In the presented approach, the QFT controller design problem has been posed as an optimization problem and is solved using genetic algorithm. The work has been compared with the work already reported in literature. The designed multivariate QFT controller efficiently mitigate the effect of parametric uncertainties, satisfy the design requirements in a very tight envelope, minimize the interaction amongst the control loops and offers improved the disturbance rejection. • Work explores a template and bounds free approach for the simultaneous synthesis of QFT controllers. • Presented method eliminates the need of ' Schauder fixed point theory ' for conventional MIMO QFT controller synthesis. • Designed MIMO QFT controller efficiently mitigate the parametric uncertainties and time delays. • Comparison of the proposed technique with the reported methods is also presented. [ABSTRACT FROM AUTHOR]

The negative aspects of overusing fossil fuels for producing electricity attract the attention of engineers society to use renewable energies. Power electronic converters play an important role in the transmission and usage of renewable energy in the industry. Boost converters are a major part of devices in which convert renewable energies into usable energy for various industries or appliances. In this article, to control a boost converter with parametric uncertainty, a new robust‐optimal controller is designed. The proposed control method is designed based on merging two conventional control theory: the robust control theory and linear quadratic regulator technique. This method consists of two nested loops. The inner loop composed of a state feedback controller which works as active damping to improve the transient state. The outer loop consists of a PI controller to track the desired voltage and reject disturbance. The coefficients of both controllers are computed by a robust‐optimal control technique. To evaluate the proposed control method, a well‐tuned single‐loop PI controller and a quantitative feedback theory based PID controller are compared with the proposed method. As shown by simulations, the proposed method has a more reliable performance in dealing with parameters uncertainties such as load changes and input voltage drops. [ABSTRACT FROM AUTHOR]

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.

When in a digital control strategy there are samples lost due to limitations, different multirate (MR) control options can be used for solving the problem: Dual-rate inferential control (IC) and model-based dual-rate control (MBDR). The objective of this contribution is to analyze, compare, and to assess their behavior under different perspectives. Is a dual-rate inferential control better than a model-based dual-rate control? Both options lead to a periodically time-varying discrete-time system and for this reason a lifted modeling is considered. An efficient algorithm is used for computing a MR system's frequency response for these control structures. The robust performance and disturbance effects are studied in detail under sample losses and process uncertainty, and some considerations are reported. A new QFT (quantitative feedback theory) procedure for dual-rate systems analysis is also described. Analysis and simulation examples and experimental results for UGV path tracking are introduced in this work, revealing that MBDR outperforms IC when the model contains important uncertainties. • A frequency analysis is used to compare dual-rate strategies for slow measured systems. • New application of quantitative feedback theory techniques to dual-rate systems. • A discussion of robust stability and performance on practical problems is reported. • Under important model uncertainties, model-based dual-rate control is the best option. • Dual-rate control reveals energy saving in a low-cost mobile robot control application. [ABSTRACT FROM AUTHOR]

Hypersonic aircrafts are introduced as a platform for cost-efficient access to space. However, challenging problems of control hypersonic aircrafts exist due to aerodynamic parametric uncertainties, external disturbances and unstable internal dynamics. This paper explores how to design and tune a controller with quantitative feedback theory (QFT). Furthermore, robust controllers based on QFT for longitudinal model are designed to solve the non-minimum phase problem and the large aerodynamic parameters uncertainty problem due to complex flight environment. According to the summary of the plant dynamics and control method, different performance specifications are presented and transformed into a set of design criteria in transfer function form as constrains for the controller design. Simulation results obtained with the designed controller and prefilter demonstrate that the designed robust controller can guarantee the stability of hypersonic aircraft model and satisfy the given performance specifications. Simulation comparisons to LQR control approach are performed to demonstrate the advantages of the proposed QFT robust controller. [ABSTRACT FROM AUTHOR]

To improve the control precision of the drive system of hydraulic tracked vehicles, we established a mathematical model of the drive system based on the analysis of structural characteristics of the high-clearance hydraulic tracked vehicles and the dual-pump dual-motor drive system and developed a control strategy based on the quantitative feedback theory. First, the mutual independence of the two motor channels was achieved through channel decoupling. Then, the loop-shaping controller and the pre-filter were designed for the two channels. The result of a simulation experiment indicates that the proposed control method is very effective in suppressing external uncertainties and smoothening the speed-switching process of the hydraulic motor. Finally, an hydraulic tracked vehicle steering experimental test was carried out. The results show that under two different steering modes, the maximum standard deviation of the output speeds of the inner and outer motors of the hydraulic tracked vehicle is only 0.42, which meets the performance requirement on the hydraulic motor speed. The average steering track radii of the geometric centers of the inner and outer tracks are 1.828 and 0.033 m, respectively, and the relative errors are 1.56% and 3.19%, respectively. This demonstrates that the proposed control method achieves satisfactory results in the robust control of the hydraulic tracked vehicle drive system. It provides some references for the future control research of the hydraulic servo drive system of the high-clearance hydraulic tracked vehicles. [ABSTRACT FROM AUTHOR]

This paper focuses on improving the performance of boiler-drum level control over a wide range of operation using the quantitative feedback theory (QFT) approach. A lab-scale boiler that is a scaled-down version of a power plant boiler is considered for the investigations. The lab boiler has the unique advantage of inducing dynamic variations or uncertainty in system behaviour, to mimic a wide range of real-world operation scenarios. The investigations on the lab boiler are conducted as follows. Firstly, the nonlinear dynamics and uncertainty of the lab boiler over the entire operation envelope are approximated in terms of linear models with parametric variations. Then, a robust two-element QFT control system for drum level control is proposed, designed, and validated over the set of linear models. Next, the proposed QFT controller is implemented on the lab-boiler, and lastly, the performance is compared experimentally with conventional fixed and scheduled two-element control schemes. Comparison of obtained experimental results show that the proposed QFT controller scheme outperforms conventional fixed and scheduled two-element control schemes, for boiler-drum level control over a wide range of operations. • A Quantitative Feedback Theory application for robust boiler drum level control. • Feasibility study on a laboratory scale natural re-circulation boiler. • Control performance metric comparison with classical and schedule approach. [ABSTRACT FROM AUTHOR]

The quantitative feedback theory is adopted as a robust control scheme for the distribution-static-compensator (DSTATCOM) in order to deactivate the effects of variations in its harmonic filter parameters on the fault ride through the capability of wind turbines (WTs). These variations may be due to factors like component aging and thermal drift. The DSTATCOM is applied in parallel with the wind generation (WG) together with a bridge-type-fault-current-limiter in series, to improve FRT capability of the WT. This proposed robust control strategy of the DSTATCOM is applied to a microgrid, including WG. The performance of this proposed scheme is simulated in PSCAD/EMTDC environment and the results indicate its efficiency.

This paper proposes a robust controller for semi-active suspension system with actuator dynamics using the quantitative feedback theory. It solves the vehicle vibration attenuation problem using the novel cascade approach. The proposed cascade quantitative feedback theory control approach consists of the inner and outer loop. The damping force tracking of the magneto-rheological damper is chosen as the inner loop, while the outer loop is for the vibration attenuation. The inner loop is added to the control structure to enhance damping force tracking capabilities. The damping force of the magneto-rheological damper depends on the many factors, such as the complex and nonlinear (hysteresis) dynamics and operating temperature. The actuator (magneto-rheological damper) dynamics is well approximated by a first-order model with an uncertain time constant which captures the essential dynamics. The simulation case study is conducted on a realistic quarter car suspension system to show the effectiveness of the proposed cascade control method. The proposed method is found to deliver superior performances, in terms of ride comfort and road holding, over the skyhook, H ∞ control, and single-loop quantitative feedback theory control under the bump, sine, and random road disturbances. [ABSTRACT FROM AUTHOR]

In this paper, a robust fixed-gain linear output pressure controller is designed for a double-rod electrohydrostatic actuator using quantitative feedback theory (QFT). First, the family of frequency responses of the system is identified by applying an advanced form of fast Fourier transform on the open-loop input-output experimental data. This approach results in realistic frequency responses of the system, which prevents the generation of unnecessary large QFT templates, and consequently contributes to the design of a low-order QFT controller. The designed controller provides desired transient responses, desired tracking bandwidth, robust stability, and disturbance rejection for the closed-loop system. Experimental results confirm the desired performance met by the QFT controller. Then, the nonlinear stability of the closed-loop system is analyzed considering the friction and leakage, and in the presence of parametric uncertainties. For this analysis, Takagi-Sugeno (T-S) fuzzy modeling and its stability theory are employed. The T-S fuzzy model is derived for the closed-loop system and the stability conditions are presented as linear matrix inequalities (LMIs). LMIs are found feasible and thus the stability of the closed-loop system is proven for a wide range of parametric uncertainties and in the presence of friction and leakages. [ABSTRACT FROM AUTHOR]

Research Summary: This study draws on the performance feedback theory to advance a behavioral perspective on the dynamics of cooperation among competitors in venture capital (VC) syndicates. Analyzing VC syndicates over a 33‐year period, I find that firms' performance relative to historical and social aspirations acts as a switch in firms' behavior with respect to dual goals of cooperation and competition in syndicates with competitors. Competition among firms in a syndicate negatively affects the probability of an IPO, but syndicates composed of firms underperforming their aspirations have a better chance of an IPO than syndicates of firms outperforming their aspirations, ceteris paribus. This effect is stronger when firms' goals in a syndicate are symmetrical or when firms' motivations based on both historical and social aspirations are aligned. Managerial Summary: Competition among VC syndicate members negatively affects a syndicate's prospects of achieving an IPO because syndicate members hold back resources for fear of their appropriation by competing partners. However, firms underperforming their track record or peer firms shift their priorities toward syndicate success and allocate more resources to their syndicates, thereby reducing the negative effect of competition. These results suggest that start‐up companies seeking VC investors, VC firms seeking co‐investors, and limited partners providing funds to VC firms all need to look beyond the capabilities of VC firms in a syndicate or their complementarity and also consider firms' relative performance. VC syndicates comprised of firms striving to correct temporary underperformance are likely to show superior results due to those firms' added motivation. [ABSTRACT FROM AUTHOR]

Abstract This paper focuses on improving the performance of boiler drum level control over a wide range of operation envelopes for the smooth integration of renewable energy. The Quantitative Feedback Theory (QFT) approach is used to design robust control systems for improving the boiler drum level dynamics over a wide operating range. A case study is performed on a heat recovery steam generator (HRSG) type boiler from a combined cycle power plant (CCPP). The wide range of HRSG operation is enveloped between hot and cold start-up profiles of the CCCP. The nonlinear dynamics of boiler drum level over this operation envelop is modelled in terms of linear models with parametric variations. A robust three-element QFT control system is then proposed, designed, and validated on the nonlinear model via simulations. The proposed robust control system is compared for its performance with the existing conventional three-element control scheme. Comparative analysis of the control results show that the proposed robust control gives much superior performance over the existing conventional control – the proposed robust control reduces the control errors by as much as 77% with similar control effort. Thus, the proposed robust control seems to be highly promising in real-world boiler drum level control applications. [ABSTRACT FROM AUTHOR]