Autonomous Rotorcraft Flight Control with Multi-Level Pilot Interaction in Hover and Forward Flight

PurposeThe paper aims to provide further study on the development and analysis of flight control system for two‐dimensional (2D) differential geometric (DG) guidance and control system based on the application of a set‐point weighting proportional‐integral‐derivative (PID) controller.Design/methodology/approachThe commanded angle‐of‐attack is developed in the time domain using the classical differential geometry theory. Then, a set‐point weighting PID controller is introduced to develop a flight control system so as to form the 2D DG guidance and control system, and the gains of the PID controller are determined by the Ziegler‐Nichols method as well as the Routh‐Hurwitz stability criterion. Finally, the classical frequency method is utilized to study the relative stability and robustness of the designed flight control system.FindingsThe results demonstrate that the designed controller yields a fast responding and stable system which is robust to the high frequency parameters variation. Moreover, the DG guidance law is viable and effective in a realistic missile defense engagement.Originality/valueThis paper provides a novel approach on the development of DG guidance and control system associated with its stability analysis.

In this paper, an optimal controller is investigate d based on the Linear Quadratic Control method. The controller simulation is execut ed based on a small-scale autonomous model helicopter, Yamaha R-50. Genetic algorithms are employed to generate weighting matrices by optimizing the performance index of the control system. As a result, this method produces optimal weighting matrices which further improve the Linear Quadratic Controller. A full state feedback approach is used in the control design process. A Kalman observer is integrated into the controller to predi ct full state variables, since only a limited number of state variables are measured. Finally, th e performance of the controller is evaluated in the time domain with and without disturbances when the model helicopter is in hovering flight and forward flight. I. Introduction utonomous helicopters offer special advantages for major operations in both civilian and military sect ors, particularly in cases that are considered either in accessible or dangerous for human beings, due to th eir vertical take-off and landing (VTOL) capabilities. The contr ol system of autonomous helicopters plays a key rol e in its ability to carry out the assigned task effectively. This has lead to a growing interest in the design and analysis of the control system of autonomous helicopters. In 1990s, classic control theory was widely used for autonom ous helicopter control systems, which is mainly a succe ssive loop closure approach. The control gains are selected separately using tools such as Root locus, Bode and Nyquist plots. The controller parameters are usual ly tuned based on the controller performance measured either in ti me domain or in frequency domain. This design procedure becomes increasingly difficult as more and more loo ps are added, specifically, when the dynamics invol ve multiple inputs, multiple outputs, or multiple feedback loop s with complex performance criteria. To control an autonomous helicopter modeled as a complex Multiple Input Multiple Output (MIMO) system, the performance criteria can not be easily met by the approach based on classis cont rol theory. Several researchers have developed a number of diff erent ways for the control system design of autonom ous helicopters in the literature. Shim et al 1 presented three different control methods using li near robust, fuzzy logic, and nonlinear tracking controls, for an autonomous helicopter in hover and low speed flight. Johnson a nd Kannan 2

Integrating self-health awareness in autonomous systems

The control algorithm includes: attitude control, position control, flight velocity control and flight trajectory control. The basic flight control algorithm is composed of two parts: orientation controller based on the model for rotation dynamics and a robust position controller based on the model for a double integrator. Then, the mathematical model of a small size helicopter is described at first. After that we present simple but effective MTC (Model and Trajectory based Controller, named by the author for convenience.) control algorithm. It is used to achieve translation position and velocity control and no stopping multi-way-point flight trajectory control. Simulation results and results achieved in real flight experiments demonstrated that the presented controller is effective and practical.

The increasing usage of Unmanned Aerial Vehicles (UAVs) in diverse applications necessitates the development of effective flight control systems. A major difficulty, nevertheless, is maintaining robust flight control under complex and dynamic environmental conditions, such as obstacle and non-flying zones, wind disturbances, and sensor noise. Traditional control techniques fail to achieve required flight control in these environments. To address this point, an adaptive control strategy is proposed based on a Deep Reinforcement Learning (DRL) model to enhance the flight performance of quadcopters. The learning and adaptation of the DRL-based control strategy are implemented in real-time through continuous interaction with the environment. This is to improve flight control and achieve consistent UAV performance under varying conditions. Proximal policy optimization with a reward function is used to minimize positional errors, ensure collision-free flight paths, and reduce energy consumption. The developed DRL model for quadcopters is trained in a simulated environment and then tested in three complex environmental scenarios, including urban, forest and mountain terrains. Experimental results demonstrate remarkable improvements in UAV flight performance. In the training phase, the reported training reward increased from 10 to 110 and the train loss is dropped from 0.85 to 0.05, which indicated successful model learning. Also, during system verification, rewards increased from 12 to 115 and UAV flight path deviations were decreased from 0.5 to 0.08m. The proposed controller outperforms conventional approaches in urban environments by lowering average trajectory deviations to 0.2m from 0.35m for MPC and 0.6m for PID. Also, the developed DRL-based controller outperformed the PID and MPC controllers, with path deviations of 0.18m in mountains and 0.12m in forests. In addition, fewer collision rates with obstacles are achieved with the model, 3% in forest, 1.8% in urban areas, and 4.5% in mountains. Furthermore, the consumed energy is reduced to 950J as compared to 1200J for PID and 1050J for MPC. The results show the strength of deploying the proposed controller in following the intended UAV flight path with high precision, effectively avoiding detected conflicts and minimizing consumed energy by the UAV.

Systematic design methodology for development and flight testing of a variable pitch quadrotor biplane VTOL UAV for payload delivery

This paper discusses the design and application method of flight control actuation system models based Modelica. According to the physical topology layout of aircraft flight control system, the model development of flight control system is decomposed from top to bottom, and all component parts of flight control system are developed by using development tool based on Modelica language, and the tree structure model library of flight control system is set up. Based on the established model library resources, the flying control system of specific aircraft can be integrated and encapsulated in accordance with the requirements. The model verification work is made through several levels of model verification to ensure that the function of the model has reached the development requirement. The confirmed flight control system models, which can be used to analyze the influence of flight control system on different user cases of aircraft ‘flight scenes, the models also can be used in real-time simulation of human in the loop with visual virtual scene. In the upgrading plan of an engineering simulator, the flight control system models are transformed into FMU models of FMI interface standard and loading into the engineering simulator to run successfully.

In this work, optimization methodologies of the kinematics of flapping wings in forward and hover flights are considered. Particularly, local and global optimization algorithms are combined with the unsteady vortex lattice method (UVLM) to determine the most efficient kinematics. In the first problem, the kinematic optimization of a three-dimensional flapping wing in forward flight with active shape morphing is aimed at maximizing the propulsive efficiency under lift and thrust constraints. Results show that due to the quasi-concavity of the objective function associated with the flapping kinematics employed in forward flight, local gradient-based optimizers perform very well in terms of accuracy and computational cost. In the second problem, the objective is to identify the optimized kinematics of a twodimensional hovering wing that minimize the aerodynamic power under lift constraint. The results show that using a hybrid optimization algorithm (combination of local and global schemes) accelerates the convergence to optimal points and avoids being trapped at local minimum points. While the efficiency of using a local optimizer, a global optimizer, or a hybrid of the two depends on the nature of the problem and associated design space, it is determined that hybrid optimization is best suited for determining local minima.

The design of new helicopter rotor blades is a challenging task. The individual blade sections undergo very different flow conditions during the various flight regimes of the helicopter. In forward flight, the advancing side operates in a transonic regime where potentially shock waves can occur, while on the retreating side little flow velocities at high angle of attacks are seen up to reverse flow. In hover, the oncoming tip vortex of the previous blade drastically influences the inflow on the rotor. This paper joins the classical blade shape design with numerical optimization techniques. Opposing to the direct solution process of directly modifying the blade shape, the rotor blade is conventionally considered as a set of airfoils, a planform and a twist distribution. First, rotor airfoils are found through numerical optimization and then placed on the reference rotor. The planform and twist of this rotor are then also numerical optimized. The obtained trade-off blade for hover and forward flight drastically improved the performance over the reference HART-II blade (11% in forward flight, 5% in hover flight). In order to arrive at industrial relevant blades, further work including more disciplines becomes necessary.

The paper describes a methodology to extract linearized state-space dynamic inflow model from a generic and high fidelity aerodynamic analysis for single and coaxial helicopter rotor systems. Both hover and forward flight are studied including maneuvering and the results are demonstrated by a free-wake analysis. The proposed methodology which is founded on a Single Frequency Analysis is computationally efficient and provide the entire frequency-domain behavior of the wake inflow states. Besides being able to incorporate any advanced computational tool, the present methodology takes advantage of exact wake states and thus adequately encompasses high frequency responses. The paper also extends the methodology to the case where states of higher harmonics are required and to the case of heaving, rolling and pitching rotor disc. For a single rotor system the results resemble the well known classical dynamic inflow model. For coaxial rotor system in hover, the high mutual couplings between the rotors are clearly demonstrated and affect the resulting system matrices. An important feature of the present methodology lays in the fact that the entire formulation is non-dimensional and the in-flow analysis is completely separated from the loads analysis, which enables a consistent generalization of the results.

Design and experimental study of a new flapping wing rotor micro aerial vehicle

The task of increasing the accuracy and stabilization of the flight of unmanned aerial vehicles (UAV) in the alpine environment is a complex problem. It is related to the evaluation of UAV flight parameters and control conditions for the operator’s place. The purpose of the UAV’s autonomous flight control is to ensure stable control of the UAV’s flight parameters. Flight control systems are affected by various disturbances caused by both internal and external conditions. In general, the number of autonomous control systems corresponds to the number of degrees of freedom, which determines the flight of an autonomous vehicle. An important factor in assessing the quality of such a UAV is its readiness for an autonomous flight together with the level of its safe guidance on the route. The presented article focuses on the analysis of UAV flight control and the quality of prediction and elimination of errors that exist during maneuvers toward the place of a successful UAV landing. The aim of the article is to point out the solvability of the complexities of such a flight procedure with the evaluation of the readiness for the descent phase of the autonomous UAV. The given problem is caused by the social demand for the creation of a way of providing health care in the mountain area of the High Tatras in Slovakia. The existing database of data obtained from the flying vehicles used in Slovakia was compared with the data obtained from the simulated flights, with their subsequent evaluation in the MATLAB software (Version R2021b) environment.

Nowadays, the development of modern technologies in the transportation area has increased rapidly. The latest technology is focused on autonomous vehicles. The most important aspect in autonomous vehicle control systems is safety, smooth operation and comfort. It can be provided by the natural element which is from human behavior as a reference to the autonomous control system. This paper is briefly describing the human behavior during braking for autonomous electric vehicle (AEV) control system development. To obtain the human behaviour during accelerating and braking, two units of angle sensors were installed to the accelerator and brake pedal of an electric car to measure the angle of both pedals. Real-time speed is recorded by using a GPS unit. The experiment is focused on braking characteristic of the electric vehicle. It was carried out based on four different distances with fixed initial speed before braking action was recorded. A software interface was designed to display and control real-time speed and pedal angle value during operation.

In the present study, the parametric study was performed to analyze the effect of the tab on the aerodynamic performance and characteristics of rotor blades. Also, the tab shape was designed to improve the aerodynamic performance of rotor blades. A computational fluid dynamics solver based on three-dimensional Reynolds averaged Navier–Stokes equation using an unstructured mesh was used for the parametric study and the tab design. For airfoils, the effect of length and angle of a tab was studied on the aerodynamic characteristics of airfoils. In addition, including those parameters, the effect of a span of a tab was studied for rotor blades in hovering flight. The results of the parametric study were analyzed in terms of change of the aerodynamic performance and characteristics to understand the effect of a tab. Considering the analysis, the design of tab shape was conducted to improve the aerodynamic performance of rotor blades. The simply attached tab to trailing edge of the rotor blades increases the thrust of the rotor blades without significant changing of aerodynamic characteristics of the rotor blades in hovering and forward flight.

The synchronization of somatic motor outflow and sympathetic efferent activity during exercise has important functional consequences. For example, a certain degree of sympathetic vasoconstriction to active skeletal muscle vascular beds may be required to prevent an excessive decrease in vascular resistance during intense dynamic exercise involving a large skeletal muscle mass. Moreover, the redistribution of blood flow away from non-exercising vascular beds to contracting skeletal muscles is necessary to meet their increased metabolic demands. Historically, the nervous system has been separated arbitrarily into a volitional (somatic) and a reflex (autonomic) control system that does not necessitate volitional input (Koizumi & Brooks, 1972). However, during exercise this partition of the somatic and autonomic control systems is replaced by an overlapping control system that influences both somatic and sympathetic outflows in a parallel fashion. Previous work has suggested that the integration and co-ordination of the somatic and sympathetic motor responses during exercise were mediated by a supraspinal neural mechanism referred to as central command (Waldrop et al. 1996). However, there is an accumulating body of evidence, including papers on the role of the spinal cord in the regulation of sympathetic outflow (Weaver & Stein, 1989), suggesting that rhythmic neural activity destined for somatomotor and sympathetic outflows may be under the control of intrinsic neuronal circuitry in the spinal cord. In this issue of The Journal of Physiology, the paper by Chizh et al. (1998) demonstrates for the first time that some components of somatic motor and sympathetic neural outflows are synchronized by a spinal mechanism. The authors studied the relationship between sympathetic and somatic motor outflows from the thoraco-sacral spinal cord using an isolated trunk-hindquarters preparation of the adult mouse. They found that some of the activity in both somatic and sympathetic outflows was coupled. However, since there was also sympathetic neural activity that showed burst discharges in the absence of somatic motor activity, the spinal mechanism responsible for generating sympathetic burst activity was not the same mechanism that was responsible for somato-sympathetic coupling. Therefore, there remained spinal mechanisms that were capable of generating bursting activity independently of somatic and sympathetic activities. When NMDA was added to the perfusate to induce rhythmic somatic motor activity, a dose-dependent bursting pattern in sympathetic efferent and somatic motor nerves was evoked that was coupled at similar frequencies. Correlational analyses found a strong coherence between somatic motor outflow and sympathetic efferent discharge when triggered from peaks in somatic motor activity. However, this synchronization was not found when triggered from the peaks of sympathetic discharge. This finding led Chizh et al. (1998) to hypothesize that the generating mechanism responsible for somatic locomotor activity was the same mechanism responsible for coupling somatic outflow to sympathetic activity. These findings support the notion that the spinal cord possesses the necessary neuronal ‘machinery’ for generating and coupling sympathetic discharge with somatic motor outflow independently of supraspinal structures (i.e. the spinal rhythm generator represents a spinal central command). Important adjustments occur in the heart and blood vessels during exercise in order to provide the appropriate oxygen delivery to match the metabolic demand of contracting skeletal muscle. The coupling of somatic motor and sympathetic outflows is mediated by supraspinal neural mechanisms (supraspinal central command) in humans and animals (Fig. 1). In humans, intense intermittent static exercise produced a one-to-one synchronization of somatic motor activity with muscle sympathetic nerve activity that was purportedly directed to skeletal muscle vasculature (Victor et al. 1995). This synchronization persisted in the presence of both partial neuromuscular blockade (i.e. to increase central command) and after local anaesthetic block of the arm nerves to eliminate afferent feedback from skeletal muscle. Likewise, electrical and chemical stimulation of the hypothalamic locomotor region in decorticate cats after neuromuscular blockade evokes fictive locomotion that produces increases in arterial blood pressure (Waldrop et al. 1996) and synchronization of sympathetic nerve activity with hindlimb motor nerve activity (Hajduczok et al. 1991). And, as seen in humans, the synchronization of somatic motor activity and sympathetic discharge was unaffected by peripheral feedback mechanisms. These findings suggest that central command signals of supraspinal origin can regulate and co-ordinate sympathetic and somatomotor outflows during exercise. Figure 1 Synchronization of somatic motor outflow and sympathetic efferent activity during exercise is mediated by supraspinal and spinal mechanisms. The important work of Chizh et al. (1998) extends our understanding of the synchronization of somatic motor activity and sympathetic outflow by highlighting the role of a spinal somato-sympathetic generator (Fig. 1). Also, the coupling of somato-sympathetic neural outflows in the spinal cord may represent an exquisite mechanism to finely tune sympathetic discharge to the segmental level of somatic motor outflow during exercise. Finally, {fontsize the degree to which supraspinal central command signals influence the somato-sympathetic spinal generator needs to be studied to further our understanding of somato-sympathetic coupling during volitional exercise.