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This paper aims to provide a mathematical modeling and design of H-infinity controller for an autonomous vertical take-off and landing (VTOL) Quad Tiltrotor hybrid unmanned aerial vehicles (UAVs). The variation in the aerodynamics and model dynamics of these aerial vehicles due to its tilting rotors are the key issues and challenges, which attracts the attention of many researchers. They carry parametric uncertainties (such as non-linear friction force, backlash, etc.), which drives the designed controller based on the nominal model to instability or performance degradation. The controller needs to take these factors into consideration and still give good stability and performance. Hence, a robust H-infinity controller is proposed that can handle these uncertainties.

A unique VTOL Quad Tiltrotor hybrid UAV, which operates in three flight modes, is mathematically modeled using Newton–Euler equations of motion. The contribution of the model is its ability to combine high-speed level flight, VTOL and transition between these two phases. The transition involves the tilting of the proprotors from 90° to 0° and vice-versa in 15° intervals. A robust H-infinity control strategy is proposed, evaluated and analyzed through simulation to control the flight dynamics for different modes of operation.

The main contribution of this research is the mathematical modeling of three flight modes (vertical takeoff–forward, transition–cruise-back, transition-vertical landing) of operation by controlling the revolutions per minute and tilt angles, which are independent of each other. An autonomous flight control system using a robust H-infinity controller to stabilize the mode of transition is designed for the Quad Tiltrotor UAV in the presence of uncertainties, noise and disturbances using MATLAB/SIMULINK. This paper focused on improving the disturbance rejection properties of the proposed UAV by designing a robust H-infinity controller for position and orientation trajectory regulation in the presence of uncertainty. The simulation results show that the Tiltrotor achieves transition successfully with disturbances, noise and uncertainties being present.

A novel VTOL Quad Tiltrotor UAV mathematical model is developed with a special tilting rotor mechanism, which combines both aircraft and helicopter flight modes with the transition taking place in between phases using robust H-infinity controller for attitude, altitude and trajectory regulation in the presence of uncertainty.

In the high-altitude, high-voltage electromagnetic interference operation environment, due to the parameters perturbation for robot control model caused by uncertainties and disturbances, and with the poor effective of the conventional proportional–integral–derivative (PID) control to parameters perturbation system, the mathematical model of power cable live operation robot joint PID closed-loop control system is established.

The corresponding joint motion robust PID control method is also proposed based on Kharitonov theory, the system robust stability conditions including the sufficient and necessary conditions are deduced and obtained and the solving process of robust PID control parameters stability region is provided.

Finally, the simulation research on robot joint motion PID control system is also launched in MATLAB environment based on Kharitonov theory. The results show that the conventional PID control obtains better control effect only to nominal model but is ineffective to parameter perturbation system, while robust PID obtains sound control effect to parameter perturbation system. Compared with H8 robust PID, the Kharitonov robust PID has better control effect which meet the system design requirements of joint motor quickly response, high tracking accuracy and sound stability. Finally, the validity and engineering practicability are verified by 220-kV living replacing damper operation experiment.

This paper has described the development of a damper replacement power cable live maintenance robot experimental prototype, which greatly improves operation efficiency and deals with the safety problem of operation in a high-voltage environment. A general manipulator motion control model of the power cable robot is established; the Kharitonov theory-based parameter perturbation robust motion control method of damper replacement robot is also obtained. Through the simulation comparison, it is verified that the Kharitonov control has more superiority for dealing with the parameter perturbation systems under the premise of ensuring the stability motion. The field experiment has further confirmed the engineering practicability.

Uncertainties in the design variables of non‐linear engineering optimization problems are often neglected. That could result in considerable deterioration of the target function value of an implemented design compared with the computed optimal solution. This effect can be reduced with robust optimization, where it is tried to achieve robust designs by actively embedding the uncertainties and robustness measures in the optimization process. A methodology for robust optimization of non‐linear problems is presented, including practical methods for the solution of such programs. The benefits of the approach are discussed in a numerical field calculation example.

The purpose of this paper is to propose a robust optimization approach for the short‐term scheduling of batch plants under demand uncertainty where the uncertain parameters can be described by a normal distribution function.

The robust optimization formulation introduces a small number of auxiliary variables and additional constraints into the original mixed integer linear programming problem, generating a deterministic robust counterpart problem which provides the optimal solution given the magnitude of the uncertain data, a feasibility tolerance, and a reliability level.

Developed robust optimization approaches produce robust solutions for uncertainties in both the coefficients and right‐hand‐side parameters of the linear inequality constraints and can be applied to address the problem of production scheduling with uncertain parameters.

The choice of the magnitude of the uncertain data, a feasibility tolerance, and a reliability level are the main limitation of the model.

Very useful advice for short‐term scheduling of batch plants under demand uncertainty.

The paper proposes a robust optimization approach for short‐term scheduling of batch plants under demand uncertainty. Computational results are presented to demonstrate the effectiveness of the proposed approach.

This paper aims to develop a robust controller to control vibration of a thin plate attached with two piezoelectric patches in the presence of uncertainties in the mass of the plate. The main goal of this study is to tackle dynamic perturbation that could lead to modelling error in flexible structures. The controller is designed to suppress first and second modal vibrations.

Out of various robust control strategies, μ-synthesis controller design algorithm has been used for active vibration control of a simply supported thin place excited and actuated using two piezoelectric patches. Parametric uncertainty in the system is taken into account so that the robust system will be achieved by maximizing the complex stability radius of the closed-loop system. Effectiveness of the designed controller is validated through robust stability and performance analysis.

Results obtained from numerical simulation indicate that implementation of the designed controller can effectively suppress the vibration of the system at the first and second modal frequencies by 98.5 and 88.4 per cent, respectively, despite the presence of structural uncertainties. The designed controller has also shown satisfactory results in terms of robustness and performance.

Although vibration control in designing any structural system has been an active topic for decades, Ordinary fixed controllers designed based on nominal parameters do not take into account the uncertainties present in and around the system and hence lose their effectiveness when subjected to uncertainties. This paper fulfills an identified need to design a robust control system that accommodates uncertainties.

The purpose of this paper is to present a conceptual risk assessment technique to aid facility managers with developing robust asset management programs. It proposes to evaluate three discrete risk sensitivity levels relative to the recognition of stochastic costs on expected budgetary outcomes. The paper expands the domain of available risk assessment techniques toward estimating impacts from uncertainty on desired levels of service.

The paper explores the concept that facility managers can cost‐effectively manage robust asset management programs. This is accomplished by evaluating simple relationships between risk‐sensitive decision‐response alternatives and systems degradation characteristics. The resulting parameters are aggregated to estimate expected budgetary outcomes for robust asset management programs.

The paper reveals that if facility managers assume risk‐avoidance positions, they can positively affect expected budgetary outcomes for robust asset management programs. Facility managers can manage the magnitude of these adverse impacts by mitigating stochastic costs associated with the completion of unscheduled asset management activities.

The expected implications are enhancements to the abilities of facility managers to cost‐effectively manage stochastic costs relative to risk sensitivity and desired levels of service. However, because of the chosen research approach, the research results may lack general usability. Therefore, researchers are encouraged to test the proposed propositions further.

The practical implications allow facility managers to cost‐effectively manage adverse impacts on expected budgetary outcomes for robust asset management programs.

The expected contribution is a tool for facility managers to manage uncertainty when allocating limited financial resources among the competing corrective, maintenance, and rehabilitation activities within robust asset management programs.

The paper fulfills an identified need to study how facility managers can do more with less. This need to be cost‐effective requires facility managers to recognize stochastic costs on the expected budgetary outcomes for robust asset management programs.

The aim of this paper is to design a nonlinear disturbance observer-based control (DOBC) method obtained by patching a control method developed using a robust adaptive technique and a DO.

For designing a DOBC, initially a class of nonlinear system is considered with an external disturbance. First, a DO is designed to estimate the external disturbances. This estimate is combined with the controller to reject the disturbances and obtain the desired control objective. For designing a controller, the robust sliding mode control theory is used. Furthermore, instead of using a constant switching gain, an adaptive gain tuning criterion is designed using Lyapunov candidate function. To investigate the stability and effectiveness of the developed DOBC, stability analysis and simulation study are presented.

The major findings of this paper include the criteria of designing the robust adaptive control parameters and investigating the disturbance rejection when robust adaptive control based DOBC is developed.

In practice, the flight of quadrotor is affected by different kind of external disturbances, thus leading to the change in dynamics. Hence, it is necessary to design DOBCs based on robust adaptive controllers such that the quadrotor model adapts to the change in dynamics, as well as nullify the effect of disturbances.

Designing DOBCs based on robust control method is a common practice; however, the robust adaptive control method is rarely developed. This paper contributes in the domain of DOBC based on robust adaptive control methods such that the behavior of controller varies with the change in dynamics occurring due to external disturbances.

The purpose of this paper is to develop a robust optimization methodology for metamaterial (MM) unit designs to minimize the effect of manufacturing and operational uncertainties.

A new robustness quantification function, applicable to both convex and nonconvex relationships between the mean and the standard deviation, is introduced. A distance-based local radial basis function network surrogate model is proposed to substitute the global radial basis function network to reduce the heavy computational cost without any scarification on the solution accuracy.

The optimized results of a prototype MM unit demonstrate the feasibility and merit of the proposed methodology. The proposed methodology outperforms the existing ones in both performance and robust parameters in the design of a prototype MM unit.

It provides a robust optimization methodology for MM units when considering the imperfections in fabrications and fluctuations in operation and environment conditions in engineering applications.

This paper seeks to propose a univariate robust control chart for location and the necessary table of factors for computing the control limits and the central line as an alternative to the Shewhart X¯ control chart.

The proposed method is based on two robust estimators, namely, the sample median, MD, to estimate the process mean, μ, and the median absolute deviation from the sample median, MAD, to estimate the process standard deviation, σ. A numerical example was given and a simulation study was conducted in order to illustrate the performance of the proposed method and compare it with that of the traditional Shewhart X¯ control chart.

The proposed robust X¯_MDMAD control chart gives better performance than the traditional Shewhart X¯ control chart if the underlying distribution of chance causes is non‐normal. It has good properties for heavy‐tailed distribution functions and moderate sample sizes and it compares favorably with the traditional Shewhart X¯ control chart.

The most common statistical process control (SPC) tool is the traditional Shewhart X¯ control chart. The chart is used to monitor the process mean based on the assumption that the underlying distribution of the quality characteristic is normal and there is no major contamination due to outliers. The sample mean, X¯, and the sample standard deviation, S, are the most efficient location and scale estimators for the normal distribution often used to construct the X¯ control chart, but the sample mean, X¯, and the sample standard deviation, S, might not be the best choices when one or both assumptions are not met. Therefore, the need for alternatives to the X¯ control chart comes into play. The literature shows that the sample median, MD, and the median absolute deviation from the sample median, MAD, are indeed more resistant to departures from normality and the presence of outliers.

The power cable maintenance robot is an important equipment to ensure the reliable operation of high-voltage transmission (HVT) lines and is a useful exploration to achieve high-quality power transmission. In respond to a series of technical problems in the operation process, such as robot shaking, terminal positioning error, camera image blurred and visual servo control difficulty which caused by the influence of high altitude random wind load on the motion control of power maintenance robot. The purpose of this study is to minimizing the impact of wind loads on robot motion control on the high voltage transmission line, so as to obtain the sound motion performance.

This paper presents a robust stabilization control method for flexible wire power maintenance robot under wind load action, the coupling mathematical model between the flexible wire with the robot has been established, and the robot rolling model under wind load has also been established. According to the tilt sensor, the robot pendulum angle value can be obtained and fitted through sinusoidal function; the robot swing period and frequency under wind load action can be also obtained; the feedforward- and feedback-based robot closed-loop control system is also designed.

Through the online detection of wind load dection, so as to dynamic control the clamping force of the robot's dual-arm jaws, therefore, the robot robust stabilization control with different grades of wind load can be realized. Finally, the effectiveness and engineering practicability of the proposed algorithm are verified by simulation experiments and field operation experiments. Compared with the conventional proportional integral differential (PID) algorithm, this method can effectively suppress the influence of wind load on the robot robust stabilization motion control, and the robot posture detection operation control has been further optimized.

A robust stabilization control method for power robot under wind load is proposed. The coupling motion model of flexible HVT and robot is established. The mathematical relationship between the robot wind rolling angle and the wind force has been deduced, and the corresponding closed-loop control system with feedforward and feedback has also been designed. Through the design of robust stabilization control algorithm based on mixed sensitivity function, the effectiveness of the mixed sensitivity robust stabilization control algorithm is verified by simulation experiments in MATLAB environment. Compared with the traditional PID algorithm, this method can effectively suppress the influence of large-scale disturbance information represented by wind load on the robot motion control. The engineering practicability of the robot robust stabilization control algorithm is further verified by the robot live damper replacement operation under the field wind load, which further improves the robot operation efficiency and intelligence.