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Automation of the robust control system synthesis for uncertain systems is of great practical interest. In this paper, the loop shaping step for synthesizing quantitative feedback theory (QFT) based controller for a two-phase permanent magnet stepper motor (PMSM) has been automated using teaching learning-based optimization (TLBO) algorithm. The QFT controller design problem has been posed as an optimization problem and TLBO algorithm has been used to minimize the proposed cost function. This facilitates designing low-order fixed-structure controller, eliminates the need of manual loop shaping step on the Nichols charts, and prevents the overdesign of the controller. A performance comparison of the designed controller has been made with the classical PID tuning method of Ziegler-Nichols and QFT controller tuned using other optimization algorithms. The simulation results show that the designed QFT controller using TLBO offers robust stability, disturbance rejection, and proper reference tracking over a range of PMSM’s parametric uncertainties as compared to the classical design techniques. [ABSTRACT FROM AUTHOR]

This paper presents theoritical and experimental design of a robust control based on quantitative feedback theory (QFT) approach to control deepness variations on cutting process for a spindle of lathe machine. The dynamics of a spindle is uncertain and varying due to deepness variation on cutting process. Practical design steps are explained in which QFT based conditions are assembled to obtain a compensator and pre-filter gain to control a spindle. The robust controller show an advantage control the system under various cutting conditions. The performances of the proposed controller are evaluated in terms of input tracking capability of the spindle responses and speed responses of a spindle incorporating deepness on cutting process. Experimental results show that QFT based robust control provides the improvement of robustness and performances. [ABSTRACT FROM AUTHOR]

Loop shaping is the prime step for synthesising Quantitative Feedback Theory (QFT) based robust controllers. The synthesised QFT controller assures performance robustness in presence of parametric plant uncertainties'. In this paper for automating the controller synthesis, loop-shaping problem has been posed as multi-objective optimization problem, which is solved using particle swarm optimization algorithm. The presented approach, explores a template and bounds free method for the automatic synthesis of fixed structure QFT controller for a highly uncertain pneumatic servo actuator system. The paper also explores the use of level diagrams for choosing the ideal solution from the Pareto optimal set. From the results obtained, the designed controller offers performance robustness over a range of plant's parametric uncertainty. [ABSTRACT FROM AUTHOR]

This brief presents design and experimental evaluation of a fixed-gain position controller for the class of electrohydrostatic actuator that is tolerant to actuator internal leakage fault and robust to various environmental stiffnesses and system parametric uncertainties. Built upon quantitative feedback theory, the proposed controller is designed according to stability and tracking specifications, considering actuator internal leakage as one of the uncertain phenomena. The controller is also augmented with a friction compensator to alleviate the parasitic effect of dry friction in the hydraulic cylinder and further improve the tracking performance. The ability of the augmented controller in maintaining the actuator position within acceptable response envelopes is demonstrated in both simulations and experiments. More specifically, the experimental results show that the steady-state error of various step input responses remains within 0.1 mm despite an internal leakage flow rate as high as 8.5 L/min. [ABSTRACT FROM AUTHOR]

Landing is a challenging flight phase for automatic control of fixed-wing aircraft. For unmanned air vehicles in particular, it is imperative that model uncertainty be considered in the control synthesis. These vehicles tend to have limited sensors and instrumentation yet must achieve sufficient performance in the presence of modeling uncertainties and exogenous inputs such as turbulence. Quantitative feedback theory has been reported in the literature for design of automatic landing control laws, but none of these controllers has been flight-tested. In this paper, quantitative feedback theory is employed to synthesize robust discrete-time controllers for automatic landing of an unmanned air vehicle. A low-cost flight vehicle with standard aileron, rudder, elevator, and throttle controls is used. Dynamic simulation is conducted using uncertain aircraft models and sensor noise profiles derived from flight hardware. Controllers are initially synthesized in deterministic simulations. Control validation is performed using a Monte Carlo analysis of stochastic simulations. Sources of uncertainty considered are sensor noise, model uncertainty, and static winds. Landing-phase simulations presented in this paper indicate a routinely high probability of a successful landing in relatively calm wind conditions. The flight-testing process is discussed, and time histories from two automatic landings are presented. Dynamic responses in flight test are found to be similar to the simulation, but a significant amount of control redesign is still required to achieve adequate experimental performance. The methodology is judged to be a promising candidate for an automatic landing controller for unmanned air vehicles. [ABSTRACT FROM AUTHOR]

In this paper, 2 practical techniques for control of dynamic systems are integrated. An input shaper is placed outside of a closed-loop system to reduce vibrations induced by the reference input. A quantitative feedback controller handles the vibrations induced by disturbances and noise while ensuring good tracking and stability. They are practical because designing an input shaper only requires knowledge of natural frequencies and damping ratios of the system whereas a quantitative feedback controller lets the designer quantitatively evaluate tradeoffs among tracking, disturbances and noise rejections, and stability among others. Various frequency-domain specifications are combined for the controller to meet requirements for all plants in an uncertain plant set. The proposed control system is applied to a 2-staged pendulum to suppress residual vibration from point-to-point movement. [ABSTRACT FROM AUTHOR]

In this paper, a new method for robust decentralised control of multi-input multi-output (MIMO) systems using quantitative feedback theory (QFT) is suggested. The proposed method does not need inversion of the plant transfer function matrix in the design process. For a given system, an equivalent descriptor system representation is defined. By using this representation, sufficient conditions for closed-loop diagonal dominance over the uncertainty space are obtained. These conditions transform the original MIMO system into a set of isolated multi-input single-output (MISO) subsystems. Then, the local controllers are designed by using the typical MISO QFT technique for each isolated subsystem to satisfy the predefined desired specifications and the closed-loop diagonal dominance sufficient conditions. The proposed technique is less conservative in comparison to the approaches using the over-bounding concept in the design procedure. The effectiveness of the proposed technique is finally assessed on a MIMO Scara robot. [ABSTRACT FROM AUTHOR]

Input shaping technique has been applied to flexible-joint robot to suppress its residual vibration from fast point-to-point movement. Input shaping performance deteriorates when the knowledge of the mode parameters of the robot is not accurate. Several robust input shapers were proposed at the expense of longer move time. A novel input shaping system, consisting of a quantitative feedback controller, a feed-forward reference model, and a simple zero-vibration (ZV) input shaper, is proposed in this paper. Advantages over the existing robust input shapers include toleration of substantially larger amount of uncertainty in the mode parameters, shorter move time that does not increase with insensitivity, application to nonlinear and time-varying systems, and suppression of vibration induced by disturbance and noise. [ABSTRACT FROM AUTHOR]

Mathematical modeling and simulation of unmanned aerial vehicles, especially, quadrotor modeling are not a simple work because of their complex structure, nonlinear dynamics and under-actuated features. This paper presents the development of a general parametric model of a quadrotor with complete dynamic. First, a new robust PID control strategy based on QFT as a robust controller design method is introduced and designed for a multivariable nonlinear quadrotor. Then, the robustness of the control strategy is verified by simulations of the linear and nonlinear cases in the presence of uncertainties. The results demonstrate that the proposed PID robust controller can guarantee system stabilization, as well as roll, pitch and yaw tracking, while the disturbance rejection of quadrotor is achieved properly. [ABSTRACT FROM AUTHOR]

For the low control precision problem of gun servo system induced by parameter perturbation and nonlinear disturbance factors, a robust control strategy for gun servo system based on quantitative feedback theory (QFT) is proposed. On the basis of gun servo system model with uncertain parameters, a certain gun servo system is taken as an example to show the method process, and the robust controller based on QFT is designed by using loop shaping method. System stability, tracking performance and robustness are analyzed and validated, and the system time domain response with parameter perturbation and output disturbance is studied. The research results show that the designed QFT robust controller can satisfy the performance index of gun servo system, and it has strong robustness and high tracking performance, which proves the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Since the fuel injection pressure in diesel engines is one of the main parameters which determine the emissions and the fuel efficiency, a precise control algorithm for the common-rail pressure is a required priority for improving the engine performances. This paper proposes a coordinated common-rail pressure control strategy for passenger car diesel engines using a metering unit and a pressure control valve. The metering unit, which is located at the high-pressure pump, adjusts the inlet fuel flow for the common rail using a first-order polynomial equation that describes the relation between the inlet fuel flow and the outlet fuel flow for the common rail. The injected fuel flow is used as the input for the control algorithm to determine the driving current of the metering unit. The designed control strategy for the metering unit effectively reduces the rail pressure wave generated by the high-pressure pump. Furthermore, since the inlet fuel flow is adjusted according to the injected fuel flow, the proposed control algorithm shows a robust performance to the injection disturbance. The pressure control valve located on the common rail adjusts the outlet fuel flow of the common rail. The control algorithm for the pressure control valve is designed using quantitative feedback theory to assure robustness even when the variation in the plant characteristics (such as the static gain and the time constant) is caused by the metering unit operation. Engine experiments proved that the proposed control strategy can reduce the variation in the steady-state rail pressure to less than 10 bar; in addition, the proposed rail pressure controller has a good degree of consistency under various engine operating conditions. [ABSTRACT FROM PUBLISHER]

In this paper, a robust H/H control with regional Pole-Placement is considered for tool position control of a nonlinear uncertain flexible robot manipulator. The uncertain nonlinear system is first approximated by Takagi and Sugeno's (T-S) fuzzy model. To achieve a better tracking, an extra state (error of tracking) is then augmented to the T-S model. Based on each local linear subsystem with augmented state, a regional pole-placement state feedback H/H controller is properly designed via linear matrix inequality (LMI) approach. Parallel Distributed Compensation (PDC) is also used to establish the whole controller for the overall system and the total linear system is obtained by using the weighted sum of the local linear systems. A fuzzy weighted online computation (FWOC) component is employed to update fuzzy weights in real time for different operating points of the system. Simulation results are presented to validate the effectiveness of the proposed controller like robustness and good load disturbance attenuation and accurate tracking, even in the presence of parameter variations and also load disturbances on the motor and the tool. The superiority of the proposed control scheme is finally highlighted in comparison with the Quantitative feedback theory (QFT) controller, the QFT controller of order 13, a polynomial controller and the so-called linear sliding-mode controller methods. [ABSTRACT FROM AUTHOR]

Quadrotor type helicopters continue to grow in popularity for academic research and unmanned aerial vehicle applications. However, the model uncertainties caused by battery voltage drop, payload variation and flight condition change, have rarely been considered in control design. This work proposes a quantitative feedback theory based robust design approach to deal with these uncertainties. By analyzing the rigid body dynamics and aerodynamic forces/moments under different voltages, payloads and flight conditions, we model quadrotor dynamics as a set of linear models with parameter uncertainties, which represent a larger flight envelop than models linearized from hover condition. These model uncertainties, as well as the robust stability requirements and performance specifications of flight control system are then used for designing and tuning the controllers, to perform tradeoff between controller complexity, robust requirements, and performance specifications. We also implemented a prototype system, and conducted a serial of experiments in realtime outdoor flights to evaluate its performance. The results show good, robust, and reliable performances of the designed system in autonomous hovering, takeoff, waypoint navigation and landing flights. [ABSTRACT FROM AUTHOR]

SUMMARY This paper introduces a novel solution for the multi-input multi-output (MIMO) quantitative feedback theory control design problem with tracking error specifications. Looking for a minimum controller overdesign, the technique finds new controller quantitative feedback theory bounds based on necessary and sufficient conditions for the existence of suitable associated prefilter matrix elements. It improves previous approaches to the subject and includes (i) the possibility of a free selection of the nominal plant, (ii) a less conservative application of the Schwartz inequality to decisively reduce the potential controller overdesign, (iii) a methodology to design independently the elements of the prefilter matrix, and (iv) a scope of application to both sequential and nonsequential MIMO controller design methods. The benefits of the new control design technique are illustrated by means of two examples. The first one, a standard 2 × 2 MIMO problem, is provided for comparison purposes with previous approaches. The second example, included as a major control challenge, deals with a well-known demanding distillation column benchmark problem. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, the modeling and control of a rotary missile that uses the proportional navigation law is proposed, applying the Quantitative Feedback Theory (QFT) technique. The dynamics of a missile are highly uncertain; thus, application of robust control methods for high precise control of missiles is inevitable. In the modeling section, a new coordinate system has been introduced, which simplifies analysis of rotary missile dynamics equations. In the controlling part, application of the QFT method leads to the design of a robust PID controller for the highly uncertain dynamics of a missile. Since missile dynamics have multivariable nonlinear transfer functions, in order to apply the QFT technique, these functions are converted to a family of linear time invariant processes with uncertainty. Next, in the loop shaping phase, an optimal robust PID controller for the linear process is designed. Lastly, analysis of the design procedure shows that the robust PID controller is superior to the commonly used PID scheme and multiple sliding surface schemes, in terms of both tracking accuracy and robustness. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Nowadays, ionic polymer metal composite actuators are widely used in many fields such as biometric, biomedical, and micro-manipulator devices. Although extensive research exists on control of the ionic polymer metal composite actuators, not much research has been done on robust control considering the nonlinear dynamics of the ionic polymer metal composite. In this study, for the first time, a closed-loop robust controller based on quantitative feedback theory is designed to overcome the actuation performance degradation of the ionic polymer metal composite actuators. First, an analytical electromechanical model is developed to fully describe dynamics of the flexible ionic polymer metal composite actuator. The model is based on the Euler–Bernoulli beam theory and includes structural damping to model viscoelastic behavior of the ionic polymer metal composite actuator. Considering the highly nonlinear and uncertain dynamics of the ionic polymer metal composite actuator, a feedback controller based on quantitative feedback theory is designed to suppress the arbitrary external disturbances and consistently track desired input. Results indicate that the robust quantitative feedback theory control techniques can significantly improve the ionic polymer metal composite performance against nonlinearity and parametric uncertainties. [ABSTRACT FROM PUBLISHER]

Robot force control is an essential issue in robotic intelligence. There is much high uncertainty when robot end-effector contacts with the environment. Because of the environment stiffness effects on the system of the robot end-effector contact with environment, the adaptive generalized predictive control algorithm based on quantitative feedback theory is designed for robot end-point contact force system. The controller of the internal loop is designed on the foundation of QFT to control the uncertainty of the system. An adaptive GPC algorithm is used to design external loop controller to improve the performance and the robustness of the system. Two closed loops used in the design approach realize the system׳s performance and improve the robustness. The simulation results show that the algorithm of the robot end-effector contacting force control system is effective. [ABSTRACT FROM AUTHOR]

This paper presents a new scheme for position tracking of pneumatic actuators. The controller is built upon the Brain Emotional Learning Based Intelligent Control (BELBIC) concept proposed by Caro Lucas [Lucas, C., Shahmirzadi, D., & Sheikholeslami, N. (2004). Introducing BELBIC: Brain emotional learning based intelligent controller.International Journal of Intelligent Automation and Soft Computing,10, 11–21]. First the structure of BELBIC is analyzed to further understand its features. Next, different types of emotional signals, required by BELBIC, are experimentally evaluated to meet the challenges in position tracking of pneumatic actuators. The best performing BELBIC structure is then experimentally compared with a previously developed robust proportional integral controller. It is also successfully applied to a force reflecting tele-operated application of pneumatic actuator. [ABSTRACT FROM AUTHOR]