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During flight, a small-size autonomous helicopter will suffer external disturbance that is wind gust. Moreover, the small-size helicopter can carries limited payload or battery. Therefore control system of an autonomous helicopter should be able to eliminate external disturbance and optimize energy consumption. The purpose of this paper is to propose a hybrid controller structure to control a small-size autonomous helicopter capable to eliminate external disturbance and optimize energy consumption. The proposed control strategy comprise of two components, a linear component to stabilize the nominal linear system and a discontinuous component to guarantee the robustness. An integral control is included in the system to eliminate steady state error and tracking reference input.

This research started with derived mathematic model of the small-size helicopter that will be controlled. Based on the obtained mathematic model, then design of a hybrid controller to control the autonomous helicopter. The hybrid controller was designed based on optimal controller and sliding mode controller. The optimal controller as main controller is used to stabilize the nominal linear system and a discontinuous component based on sliding mode controller to guarantee the robustness.

Performance of the proposed controller was tested in simulation. The hybrid controller performance was compared with optimal controller performance. The hybrid controller has better performance compared with optimal controller. Results of the simulation shows that the proposed controller has good performance and robust against external disturbances. The proposed controller has better performance in rise time, settling time and overshoot compared with optimal controller response both for step input response and tracking capability.

Hybrid controller to control small-size helicopter has not reported yet. In this research new hybrid controller structure for a small size autonomous helicopter was proposed.

This paper aims to present a nonlinear finite element model (FEM) of the Brushless DC (BLDC) motor and the application of the optimal linear–quadratic control-based method to determine the excitation voltage and current waveform considering the minimization of the energy injected to the input circuit and energy lost. The control problem is designed and analyzed using the feedback gain strategy for the infinite time horizon problem.

The method exploits the distributed parameters, nonlinear FEM of the device. First, dynamic equations of the BLDC motor are transformed into a suitable form that makes an ARE (algebraic Riccati equation)-based control technique applicable. Moreover, in the controller design, a Bryson scaling method is used to obtain desirable properties of the closed-loop system. The numerical techniques for solving ARE with the gradient damping factor are proposed and described. Results for applied control strategy are obtained by simulations and compared with measurement.

The proposed control technique can ensure optimal dynamic response, small steady-state error and energy saving. The effectiveness of the proposed control strategy is verified via numerical simulation and experiment.

The authors introduced an innovative approach to the well-known control methodology and settled their research in the newest literature coverage for this issue.

The purpose of this paper is to investigate an optimal control solution with prescribed degree of stability for the position and tracking control problem of the twin rotor multiple input-multiple output (MIMO) system (TRMS). The twin rotor MIMO system is a benchmark aerodynamical laboratory model having strongly non-linear characteristics and unstable coupling dynamics which make the control of such system for either posture stabilization or trajectory tracking a challenging task.

This paper first describes the dynamical model of twin rotor MIMO system (TRMS) and then it adopts linear-quadratic regulator (LQR)-based optimal control technique with prescribed degree of stability to achieve the desired trajectory or posture stabilization of TRMS.

The simulation results show that the investigated controller has both static and dynamic performance; therefore, the stability and the quick control effect can be obtained simultaneously for the twin rotor MIMO system.

The articles on LQR optimal controllers for TRMS can also be found in many literatures, but the prescribed degree of stability concept was not discussed in any of the paper. In this work, new LQR with the prescribed degree of stability concept is applied to provide an optimal control solution for the position and tracking control problem of TRMS.

This paper aims to present a continuous-time workforce planning model in which workforce flow occurs in terms of internal and external recruitment considering human resource strategies (HRS). The proposed model is a linear optimal control model in which promotions occur by inside appointment and outside employment of the system considering a cost leadership or a differentiation strategy and whether organizations have an internal or an external recruitment orientation. In other words, in the model and its solution procedure, this paper could determine any arbitrary function for the demand of the workforce with each HRS.

The proposed model contains five main sections, namely, applicants, newcomers, workforce who are doing sensitive-simple jobs, expert workforce and supervisors (or managers) that have a different orientation in different HRS. Each of these sections has a target value that this paper tries to attain it by applying appropriate control variables, such as recruitment, layoff, degradation, promotion and retirement. To reach this purpose, this paper formulated an optimal control problem using a linear system transition equation with a quadratic cost function.

Based on the proposed model, it was found that the optimal control model can interpret the managerial aspects. This model could be useful for different firms with different types of workforce demands. This paper has tried to have a comprehensive view of different flows of the workforce in an organization that concern to workforce planning.

Despite the considerable amount of research published, and the importance of following a human resources strategy from organizational strategy, in the knowledge, there is no comprehensive study dedicated to human resources strategy and workforce planning by optimal control models for workforce planning.

In this paper, improvements in reducing transmitted accelerations in a full vehicle are obtained by optimizing the gain parameters of an active control in a roughness road profile.

For a classically designed linear quadratic regulator (LQR) control, the vibration attenuation performance will depend on weighting matrices Q and R. A methodology is proposed in this work to determine the optimal elements of these matrices by using a genetic algorithm method to get enhanced controller performance. The active control is implemented in an eight degrees of freedom (8-DOF) vehicle suspension model, subjected to a standard ISO road profile. The control performance is compared against a controlled system with few Q and R parameters, an active system without optimized gain matrices, and an optimized passive system.

The control with 12 optimized parameters for Q and R provided the best vibration attenuation, reducing significantly the Root Mean Square (RMS) accelerations at the driver’s seat and car body.

The research has positive implications in a wide class of active control systems, especially those based on a LQR, which was verified by the multibody dynamic systems tested in the paper.

Better active control gains can be devised to improve performance in vibration attenuation.

The main contribution proposed in this work is the improvement of the Q and R parameters simultaneously, in a full 8-DOF vehicle model, which minimizes the driver’s seat acceleration and, at the same time, guarantees vehicle safety.

In order to make sure of the safety of a long-span suspension bridge under earthquake action, this paper aims to study the traveling wave effect of the bridge under multi-support excitation and optimize the semi-active control schemes based on magneto-rheological (MR) dampers considering reference index as well as economical efficiency.

The finite element model of the long-span suspension bridge is established in MATLAB and ANSYS software, which includes different input currents and semi-active control conditions. Six apparent wave velocities are used to conduct non-linear time history analysis in order to consider the seismic response influence in primary members under traveling wave effect. The parameters α and β, which are key parameters of classical linear optimal control algorithm, are optimized and analyzed taking into account five different combinations to obtain the optimal control scheme.

When the apparent wave velocity is relatively small, the influence on the structural response is oscillatory. Along with the increase of the apparent wave velocity, the structural response is gradually approaching the response under uniform excitation. Semi-active control strategy based on MR dampers not only restrains the top displacement of main towers and relative displacement between towers and girders, but also affects the control effect of internal forces. For classical linear optimal control algorithm, the values of two parameters (α and β) are 100 and 8 × 10–6 considering the optimal control effect and economical efficiency.

The emphasis of this study is the traveling wave effect of the triple-tower suspension bridge under multi-support excitation. Meanwhile, the optimized parameters of semi-active control schemes using MR dampers have been obtained, providing relevant references in improving the seismic performance of three-tower suspension bridge.

Workforce planning must answer how many workforces, in which positions, and talents, and when each organization is needed. To find the requirements workforce, organizations need to know the organizational position and talents pools. Clarifying the number of workforces required in each pool requires attention to workforce flows, including hiring, promotion, degradation, horizontal movement, and exiting the organization. It is a dynamic issue and must be addressed over several periods over a specific duration, which adds to the complexity. According to the talent management presented in this research, all the above complex questions are answered by applying the optimal control (OC) model according to talent management presented in this research.

This research presents a dynamic model by using a linear-quadratic optimal control model, which was solved by Pontryagin's maximum principle, to achieve an optimal number of workforce requirements for each of the positions of nursing services manager, supervisor, head nurses and nurses in the health sector according to the required talents in each position.

The results have shown that the target value of workforce numbers has been achieved in the planning period, and the validation test and sensitivity analysis justified the model by reaching the workforce planning targets.

This study provides a dynamic model for achieving quantitative workforce planning targets; the model presented in this manuscript has included an important qualitative factor, namely workforce talents. According to the authors' review, there is no comprehensive research devoted to workforce planning through optimal control models by attention to workforces skills.

Damage due to delamination is an important issue during drilling in polymer-matrix composites (PMCs). It depends on thrust force and torque which are functions of feed rate. Transfer function of thrust force with feed rate and torque with feed rate is constructed through experiments. These transfer functions are then combined in state-space to formulate a sixth-order model. Then thrust force and torque are controlled by using optimal controller. The paper aims to discuss these issues.

A glass fiber reinforced plastic composite is drilled at constant feed rate during experimentation. The corresponding time response of thrust force and torque is recorded. Third-order transfer functions of thrust force with feed rate and torque with feed rate are identified using system identification toolbox of Matlab®. These transfer functions are then converted into sixth-order combined state-space model. Optimal controller is then designed to track given reference trajectories of thrust force/torque during drilling in composite laminate.

Optimal control is used to simultaneously control thrust force as well as torque during drilling. There is a critical thrust force during drilling below which no delamination occurs. Therefore, critical thrust force profile is used as reference for delamination free drilling. Present controller precisely tracks the critical thrust force profile. Using critical thrust force as reference, high-speed drilling can be done. The controller is capable of precisely tracking arbitrary thrust force and torque profile simultaneously. Findings suggest that the control mechanism is efficient and can be effective in minimizing drilling induced damage in composite laminates.

Simultaneous optimal control of thrust force and torque during drilling in composites is not available in literature. Feed rate corresponding to critical thrust force trajectory which can prevent delamination at fast speed also not available has been presented.