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The aim of this paper is to describe in detail the μ -synthesis of a miniature helicopter integral attitude controller of high order and to present results from the hardware-in-the-loop simulation of this controller implementing Digital Signal Processor. The μ -controller designed allows to suppress efficiently wind disturbances in the presence of 25 % input multiplicative uncertainty. A simple position controller is added to ensure tracking of the desired trajectory in 3D space. The results from hardware-in-the-loop simulation are close to the results from double-precision simulation of helicopter control system in Simulink ® . The software platform developed allows to implement easily different sensors, servoactuators and control laws and to investigate the closed-loop system behavior in presence of different disturbances and parameter variations.

This paper presents a high-order sliding mode approach to design variable structure controllers for nonlinear multivariable cross-coupling systems whereby a change in either control input affects the control loops of all the subsystems dynamics. A hybrid-sliding mode control (hybrid-SMC) scheme is constructed combining a new equivalent control algorithm with a high-order discontinuous control algorithm to benefit from the advantages of both control strategies. The hybrid-SMC scheme uses weighting coefficients to weight and combine controllers. The equivalent control algorithm uses a relative degree concept through dynamic constraints imposed on the sliding variables to overcome the limitations of the conventional approaches and to provide an optimum tracking performance. A scale-laboratory helicopter model is used to sum up the main features and demonstrate the effectiveness of the developed control scheme. The proposed hybrid-SMC strategy is compared to existing sliding mode-based control approaches in terms of tracking performance, stability and control efforts. The obtained results demonstrate the validity and efficiency of the proposed hybrid-SMC scheme.

In this paper, an incremental nonlinear dynamic inversion (INDI) control scheme is proposed for the attitude tracking of a helicopter with model uncertainties, and actuator delay and saturation constraints. A finite integral compensation based on model reduction is used to compensate the actuator delay, and the proposed scheme can guarantee the semi-globally uniformly ultimately bounded tracking. The overall attitude controller is separated into a rate, an attitude, and a collective pitch controller. The rate and collective pitch controllers combine the proposed method and INDI to enhance the robustness to actuator delay and model uncertainties. Considering the dynamic of physical actuators, pseudo-control hedging (PCH) is introduced both in the rate and attitude controller to improve tracking performance. By using the proposed controller, the helicopter shows good dynamics under the multiple restrictions of the actuators.

In the field of the widely used helicopter, this paper studies whether the helicopters with three-degree freedom (3DOF helicopters) have a new control method of stable attitude. Therefore, two research methods are adopted. One is to use intermittent control, so as to achieve control stability in a short time without its inputting. The other is to find and update the time needed to meet the next control through the event-triggered mechanism. A theorem is given to prove the feasibility of these methods, and Lyapunov’s second law is also applied in this paper to analyze the stability of the model designed for robust attitude control. Besides, we use the linear matrix inequality solver to solve the feedback gain of the controller in the theorem. Finally, through MATLAB simulation, the system error state of helicopters tends to zero under intermittent control, which highlights the advantages of short communication time and few times of simulation, thus achieving the simulation goal.

The modern helicopter is a sophisticated device which merges a surprising number of technologies together.This wide range of disciplines is one of the fascinations of the helicopter, but it is also makes a complete understanding difficult.Those searching for an understanding of the helicopter will find The Art of the Helicopter invaluable.

Purpose – The purpose of this paper is to develop a multiobjective differential evolution (MODE)-based extended H-infinity controller for autonomous helicopter control. Design/methodology/approach – Development of a MATLAB-based MODE suitable for controller synthesis. Formulate the H-infinity control scheme as an extended H-infinity loop shaping design procedure (H ∞ -LSDP) with incorporation of v-gap metric for robustness to parametric variation. Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. Findings – The proposed optimized H-infinity control was able to yield set of Pareto-controller candidates with optimal compromise between conflicting stability and time-domain performances required in autonomous helicopter deployment. The result of performance evaluation shows robustness to parameter variation of up to 20 per cent variation in nominal values, and in addition provides satisfactory disturbance rejection to wind disturbance in all the three axes. Research limitations/implications – The formulated H-infinity controller is limited to hovering and low speed flight envelope. The optimization is focused on weighting function parameters for a given fixed weighting function structure. This thus requires a priori selection of weighting structures. Practical implications – The proposed MODE-infinity controller algorithm is expected to ease the design and deployment of the robust controller in autonomous helicopter application especially for practicing engineer with little experience in advance control parameters tuning. Also, it is expected to reduce the design cycle involved in autonomous helicopter development. In addition, the synthesized robust controller will provide effective hovering/low speed autonomous helicopter flight control required in many civilian unmanned aerial vehicle (UAV) applications. Social implications – The research will facilitate the deployment of low-cost, small-scale autonomous helicopter in various civilian applications. Originality/value – The research addresses the challenges involved in selection of weighting function parameters for H-infinity control synthesis to satisfy conflicting stability and time-domain objectives. The problem of population initialization and objectives function computation in the conventional MODE algorithm are addressed to ensure suitability of the optimization algorithm in the formulated H-infinity controller synthesis.

For the quantitative assessment of pilot workload during helicopter closed-loop tasks, wavelet transform technology is employed to investigate the evaluation methodology. A quantification function for pilot workload is established based on the power frequency and weights of control inputs, which comprehensively integrates the four helicopter control inputs. Based on the pirouette task flight tests conducted by two pilots, the correctness of the quantitative assessment method was validated by analyzing the correlations between the quantified results and the pilots’ handling qualities rating (HQR). The results demonstrate that the power frequency of single-axis control inputs does not always exhibit correlations with HQR. The weights of control inputs, derived from their aggressiveness and cut-off frequency, effectively reflect their contributions to pilot workload. The workload quantification function accurately characterizes pilot workload, showing a strong positive correlation between the quantified values and HQR. Furthermore, wavelet transform technology is validated as an effective method for conducting quantitative assessments of pilot workload.

Autonomous helicopter flight provides a challenging control problem. In order to evaluate control designs, an experimental platform must be developed in order to conduct flight tests. However, the literature describing existing platforms focuses on the hardware details, while little information is given regarding software design and control algorithm implementation. This paper presents the design, implementation, and validation of an experimental helicopter platform with a primary focus on a software framework optimized for controller development. In order to validate the operation of this platform and provide a basis for comparison with more sophisticated nonlinear designs, a PID controller with feedforward gravity compensation is derived using the generally accepted small helicopter model and tested experimentally.

This paper proposes a design of a direct optimal control for a class of multi-input–multi-output (MIMO) nonlinear systems. This work focuses on the design of optimal model-free backstepping controller for a MIMO quadrotor helicopter perturbed by unknown external disturbances. The proposed method consists of using a model-free-based backstepping controller optimized by a cuckoo search algorithm. First, the overall dynamic model is decoupled into six interconnected subsystems. Then, the ideal backstepping controller with a known dynamic function is designed for each subsystem. The model-free based on backstepping control uses a new estimator approach to approximate the unknown dynamic model functions. After that, the global asymptotical stability of the closed-loop control system is proved via the Lyapunov theory. Moreover, the parameters of the proposed controller are optimized by the cuckoo search algorithm according to a cost function. The results of numerical simulations applied to the quadrotor helicopter system demonstrate the robustness and the effectiveness of the proposed control strategy.

This study develops a neural network control for a non‐linear two‐degree‐of‐freedom unmanned helicopter system satisfying prescribed performance constraints is developed. By introducing a prescribed performance function to express the system constraints, a constrained tracking control problem is transformed into an equivalent unconstrained stability problem through error transformations. The neural network controller is designed to ensure that the tracking error converges to a small neighborhood of zero and that the prescribed performance constraints are satisfied. Furthermore, the stability and error convergence of the system are analysed through the Lyapunov direct approach. The effectiveness of the proposed control scheme is verified by simulation and experimental results.