Special Issue "Recent Progress in Robot Control Systems: Theory and Applications"

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer Science and Symmetry/Asymmetry".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 20155

Special Issue Editors

Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, China
Interests: robotics; navigation; optimal filtering; orbit determination; hybridization theory
Special Issues, Collections and Topics in MDPI journals
Dr. Chong Li
E-Mail Website
Guest Editor
Associate Professor, Department Automation and Measurement, Ocean University of China, Qingdao, China
Interests: control systems; MEMS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Symmetry and asymmetry are common in engineering science. For example, electronic rotors, aircraft wings, and spacecraft flywheel structures possess excellent symmetry in actuators. Due to machining defects, these controlled objects are practically asymmetric, and external perturbations somehow break the symmetry. Therefore, we need to design sophisticated algorithms to maintain these elegant systems. The design of control systems is critical to the safe operation of various mechanical systems such as space vehicles, maritime robotics, and micromechanical systems. Current research is more than adequate, but more refined, intelligent, low-resource-consumption technologies for control systems algorithms are still in short supply to accommodate the industry's growth. In this Special Issue, “Recent Progress in Robot Control Systems: Theory and Applications,” we aim to attract original research and survey papers reflecting the recent advances in the theory and methodology driving recent progress in control system design and applications.

Please note that all submitted papers must be within the general scope of Symmetry. Potential topics include but are not limited to the following:

  • Human in loop control policy;
  • Online-learning control;
  • Intelligent computing and machine learning;
  • Data-driven approaches and applications;
  • Networked system design and control;
  • Fault-diagnosis and fault-tolerant control,
  • Neural-network-based control;
  • Computational intelligence in control;
  • Control design in MEMS.

Dr. Chengxi Zhang
Dr. Jin Wu
Prof. Dr. Chong Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (15 papers)

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Research

Article
Two-Step Self-Calibration of LiDAR-GPS/IMU Based on Hand-Eye Method
Symmetry 2023, 15(2), 254; https://doi.org/10.3390/sym15020254 - 17 Jan 2023
Viewed by 1182
Abstract
Multi-line LiDAR and GPS/IMU are widely used in autonomous driving and robotics, such as simultaneous localization and mapping (SLAM). Calibrating the extrinsic parameters of each sensor is a necessary condition for multi-sensor fusion. The calibration of each sensor directly affects the accurate positioning [...] Read more.
Multi-line LiDAR and GPS/IMU are widely used in autonomous driving and robotics, such as simultaneous localization and mapping (SLAM). Calibrating the extrinsic parameters of each sensor is a necessary condition for multi-sensor fusion. The calibration of each sensor directly affects the accurate positioning control and perception performance of the vehicle. Through the algorithm, accurate extrinsic parameters and a symmetric covariance matrix of extrinsic parameters can be obtained as a measure of the confidence of the extrinsic parameters. As for the calibration of LiDAR-GPS/IMU, many calibration methods require specific vehicle motion or manual calibration marking scenes to ensure good constraint of the problem, resulting in high costs and a low degree of automation. To solve this problem, we propose a new two-step self-calibration method, which includes extrinsic parameter initialization and refinement. The initialization part decouples the extrinsic parameters from the rotation and translation part, first calculating the reliable initial rotation through the rotation constraints, then calculating the initial translation after obtaining a reliable initial rotation, and eliminating the accumulated drift of LiDAR odometry by loop closure to complete the map construction. In the refinement part, the LiDAR odometry is obtained through scan-to-map registration and is tightly coupled with the IMU. The constraints of the absolute pose in the map refined the extrinsic parameters. Our method is validated in the simulation and real environments, and the results show that the proposed method has high accuracy and robustness. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Facial Expression Recognition Based on Dual-Channel Fusion with Edge Features
Symmetry 2022, 14(12), 2651; https://doi.org/10.3390/sym14122651 - 15 Dec 2022
Viewed by 1237
Abstract
In the era of artificial intelligence, accomplishing emotion recognition in human–computer interaction is a key work. Expressions contain plentiful information about human emotion. We found that the canny edge detector can significantly help improve facial expression recognition performance. A canny edge detector based [...] Read more.
In the era of artificial intelligence, accomplishing emotion recognition in human–computer interaction is a key work. Expressions contain plentiful information about human emotion. We found that the canny edge detector can significantly help improve facial expression recognition performance. A canny edge detector based dual-channel network using the OI-network and EI-Net is proposed, which does not add an additional redundant network layer and training. We discussed the fusion parameters of α and β using ablation experiments. The method was verified in CK+, Fer2013, and RafDb datasets and achieved a good result. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Autonomous Navigation and Obstacle Avoidance for Small VTOL UAV in Unknown Environments
Symmetry 2022, 14(12), 2608; https://doi.org/10.3390/sym14122608 - 09 Dec 2022
Cited by 1 | Viewed by 1271
Abstract
This paper takes autonomous exploration in unknown environments on a small co-axial twin-rotor unmanned aerial vehicle (UAV) platform as the task. The study of the fully autonomous positioning in unknown environments and navigation system without global navigation satellite system (GNSS) and other auxiliary [...] Read more.
This paper takes autonomous exploration in unknown environments on a small co-axial twin-rotor unmanned aerial vehicle (UAV) platform as the task. The study of the fully autonomous positioning in unknown environments and navigation system without global navigation satellite system (GNSS) and other auxiliary positioning means is carried out. Algorithms that are based on the machine vision/proximity detection/inertial measurement unit, namely the combined navigation algorithm and indoor simultaneous location and mapping (SLAM) algorithm, are not only designed theoretically but also realized and verified in real surroundings. Additionally, obstacle detection, the decision-making of avoidance motion and motion planning methods such as Octree are also proposed, which are characterized by randomness and symmetry. The demonstration of the positioning and navigation system in the unknown environment and the verification of the indoor obstacle-avoidance flight were both completed through building an autonomous navigation and obstacle avoidance simulation system. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Industrial Robot Contouring Control Based on Non-Uniform Rational B-Spline Curve
Symmetry 2022, 14(12), 2533; https://doi.org/10.3390/sym14122533 - 30 Nov 2022
Cited by 1 | Viewed by 676
Abstract
This paper presents a novel algorithm about the industrial robot contouring control based on the NURBS (non-uniform rational B-spline) curve. First, aiming at the error between the industrial robot’s actual trajectory and the desired trajectory, the contour error is proposed as the trajectory [...] Read more.
This paper presents a novel algorithm about the industrial robot contouring control based on the NURBS (non-uniform rational B-spline) curve. First, aiming at the error between the industrial robot’s actual trajectory and the desired trajectory, the contour error is proposed as the trajectory evaluation index, and the estimation algorithm of contour error based on the tangent approximation is proposed. Based on the tangent approximation algorithm, the estimation algorithm of contour error in the local task coordinate frame is proposed to realize the transformation from the Cartesian coordinate frame to the local task coordinate frame. Second, according to the configuration of the industrial robot, a modified cross-coupling control scheme based on the local task coordinate frame is designed. Finally, the Bernoulli’s lemniscate curves are constructed by NURBS curve and five-order polynomial curve, respectively, and they are symmetrical. The contrast experiment is designed using the two types of constructed Bernoulli’s lemniscate curves as the incentive trajectory. Through the analysis and comparison between the obtained uniaxial tracking error and the contour error curve of the two incentive trajectories, it is concluded that the incentive trajectory constructed by the NURBS curve has better contour control performance than that constructed by the five-order polynomial curve. The results drawn from this paper lay a certain foundation for the future high-precision contouring control of industrial robots. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Redundant Posture Optimization for 6R Robotic Milling Based on Piecewise-Global-Optimization-Strategy Considering Stiffness, Singularity and Joint-Limit
Symmetry 2022, 14(10), 2066; https://doi.org/10.3390/sym14102066 - 04 Oct 2022
Cited by 1 | Viewed by 966
Abstract
Robotic machining has obtained growing attention recently because of the low cost, high flexibility and large workspace of industrial robots (IRs). Multiple degrees of freedom of IRs improve the dexterity of machining while causing the problem of redundancy. Meanwhile, the performance of IRs, [...] Read more.
Robotic machining has obtained growing attention recently because of the low cost, high flexibility and large workspace of industrial robots (IRs). Multiple degrees of freedom of IRs improve the dexterity of machining while causing the problem of redundancy. Meanwhile, the performance of IRs, such as their stiffness and dexterity, is affected by their position and posture obviously. Therefore, a redundant posture optimization method for robotic milling is proposed to improve the machining performance of the robot. The multiple characteristics of the robot are considered, including the joint-limit, singularity and stiffness, which have symmetry in its workspace. Firstly, the joint-limit is regarded as the constraint. And a symmetrical and effective constraint method is proposed to simply guarantee that all the interpolation points can avoid joint interference. Then, the performance indices of singularity and stiffness are designed as the optimization target. On this basis, the piecewise-global-optimization-strategy (PGOS) is proposed for redundant optimization. Owning to the PGOS, all the given planned tool points in their corresponding segment are considered simultaneously to avoid the gradual deterioration in traditional methods, which is especially suitable for the machining process with a continuous path. Moreover, the computational load of the optimization solution is considered and limited by the designed segmentation strategy. Finally, a series of comparative simulations are conducted to validate the good performance of the proposed method. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Flight Conflict Detection Algorithm Based on Relevance Vector Machine
Symmetry 2022, 14(10), 1992; https://doi.org/10.3390/sym14101992 - 23 Sep 2022
Viewed by 660
Abstract
In response to the problems of slow running speed and high error rates of traditional flight conflict detection algorithms, in this paper, we propose a conflict detection algorithm based on the use of a relevance vector machine. A set of symmetrical historical flight [...] Read more.
In response to the problems of slow running speed and high error rates of traditional flight conflict detection algorithms, in this paper, we propose a conflict detection algorithm based on the use of a relevance vector machine. A set of symmetrical historical flight data was used as the training set of the model, and we used the SMOTE resampling method to optimize the training set. We obtained relatively symmetrical training data and trained it with the relevance vector machine, improving the kernels through an intelligent algorithm. We tested this method with new symmetrical flight data. The improved algorithm greatly improved the running speed and was able to effectively reduce the missed alarm rate of in-flight conflict detection symmetrically, thus effectively ensuring flight safety. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Performance Analysis on the Small-Scale Reusable Launch Vehicle
Symmetry 2022, 14(9), 1862; https://doi.org/10.3390/sym14091862 - 06 Sep 2022
Viewed by 920
Abstract
According to the symmetrical characteristics of a new type of Reusable Launch Vehicle (RLV) in the recovery phase, we studied the basic aerodynamic model data of Starship and the aerodynamic data with rudder deflection, and the causes of its aerodynamic coefficients are expounded. [...] Read more.
According to the symmetrical characteristics of a new type of Reusable Launch Vehicle (RLV) in the recovery phase, we studied the basic aerodynamic model data of Starship and the aerodynamic data with rudder deflection, and the causes of its aerodynamic coefficients are expounded. At the same time, we analyzed its stability and maneuverability. According to the flying quality requirements, the lateral-directional model of Starship in the return phase at a high angle of attack is analyzed. Finally, we analyzed the lateral heading stability and control deviation of Starship by using the criterion and nonlinear open-loop simulations. The results show that the Starship has pitching and rolling stability, but it only has heading stability in some ranges of angle of attack, and there is no heading stability at a conventional large angle of attack. At the same time, after modal analysis and comparison of flight quality, it can be seen that the longitudinal long-period model of the starship degenerates into a real root and it is stable and convergent. The lateral heading roll mode is at level 2 flight quality, the helical mode is at level 1 flight quality, and the Dutch roll mode diverges, which needs to be stabilized and controlled later. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Design of Thrust Vectoring Vertical/Short Takeoff and Landing Aircraft Stability Augmentation Controller Based on L1 Adaptive Control Law
Symmetry 2022, 14(9), 1837; https://doi.org/10.3390/sym14091837 - 04 Sep 2022
Cited by 2 | Viewed by 940
Abstract
Aiming at the conversion process of thrust vectoring vertical/short takeoff and landing (V/STOL) aircraft with a symmetrical structure in the transition stage of takeoff and landing, there is a problem with the coupling and redundancy of the control quantities. To solve this problem, [...] Read more.
Aiming at the conversion process of thrust vectoring vertical/short takeoff and landing (V/STOL) aircraft with a symmetrical structure in the transition stage of takeoff and landing, there is a problem with the coupling and redundancy of the control quantities. To solve this problem, a corresponding inner loop stabilization controller and control distribution strategy are designed. In this paper, a dynamic system model and a dynamic model are established. Based on the outer loop adopting the conventional nonlinear dynamic inverse control, an L1 adaptive controller is designed based on the model as the inner loop stabilization control to compensate the mismatch and uncertainty in the system. The key feature of the L1 adaptive control architecture is ensuring robustness in the presence of fast adaptation, so as to achieve a unified performance boundary in transient and steady-state operations, thus eliminating the need for adaptive rate gain scheduling. The control performance and robustness of the controller are verified by inner loop simulation and the shooting Monte Carlo approach. The simulation results show that the controller can still track the reference input well and has good robustness when there is a large parameter perturbation. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
A Multi-Scale and Lightweight Bearing Fault Diagnosis Model with Small Samples
Symmetry 2022, 14(5), 909; https://doi.org/10.3390/sym14050909 - 29 Apr 2022
Cited by 3 | Viewed by 1230
Abstract
Currently, deep-learning-based methods have been widely used in fault diagnosis to improve the diagnosis efficiency and intelligence. However, most schemes require a great deal of labeled data and many iterations for training parameters. They suffer from low accuracy and over fitting under the [...] Read more.
Currently, deep-learning-based methods have been widely used in fault diagnosis to improve the diagnosis efficiency and intelligence. However, most schemes require a great deal of labeled data and many iterations for training parameters. They suffer from low accuracy and over fitting under the few-shot scenario. In addition, a large number of parameters in the model consumes high computing resources, which is far from practical. In this paper, a multi-scale and lightweight Siamese network architecture is proposed for the fault diagnosis with few samples. The architecture proposed contains two main modules. The first part implements the feature vector extraction of sample pairs. It is composed of two lightweight convolutional networks with shared weights symmetrically. Multi-scale convolutional kernels and dimensionality reduction are used in these two symmetric networks to improve feature extraction and reduce the total number of model parameters. The second part takes charge of calculating the similarity of two feature vectors to achieve fault classification. The proposed network is validated by multiple datasets with different loads and speeds. The results show that the model has better accuracy, fewer model parameters and a scale compared to the baseline approach through our experiments. Furthermore, the model is also proven to have good generalization capability. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Velocity-Free State Feedback Fault-Tolerant Control for Satellite with Actuator and Sensor Faults
Symmetry 2022, 14(1), 157; https://doi.org/10.3390/sym14010157 - 13 Jan 2022
Cited by 1 | Viewed by 1060
Abstract
A velocity-free state feedback fault-tolerant control approach is proposed for the rigid satellite attitude stabilization problem subject to velocity-free measurements and actuator and sensor faults. First, multiplicative faults and additive faults are considered in the actuator and the sensor. The faults and system [...] Read more.
A velocity-free state feedback fault-tolerant control approach is proposed for the rigid satellite attitude stabilization problem subject to velocity-free measurements and actuator and sensor faults. First, multiplicative faults and additive faults are considered in the actuator and the sensor. The faults and system states are extended into a new augmented vector. Then, an improved sliding mode observer based on the augmented vector is presented to estimate unknown system states and actuator and sensor faults simultaneously. Next, a velocity-free state feedback attitude controller is designed based on the information from the observer. The controller compensates for the effects of actuator and sensor faults and asymptotically stabilizes the attitude. Finally, simulation results demonstrate the effectiveness of the proposed scheme. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Improved Path Planning for Indoor Patrol Robot Based on Deep Reinforcement Learning
Symmetry 2022, 14(1), 132; https://doi.org/10.3390/sym14010132 - 11 Jan 2022
Cited by 10 | Viewed by 1836
Abstract
To solve the problems of poor exploration ability and convergence speed of traditional deep reinforcement learning in the navigation task of the patrol robot under indoor specified routes, an improved deep reinforcement learning algorithm based on Pan/Tilt/Zoom(PTZ) image information was proposed in this [...] Read more.
To solve the problems of poor exploration ability and convergence speed of traditional deep reinforcement learning in the navigation task of the patrol robot under indoor specified routes, an improved deep reinforcement learning algorithm based on Pan/Tilt/Zoom(PTZ) image information was proposed in this paper. The obtained symmetric image information and target position information are taken as the input of the network, the speed of the robot is taken as the output of the next action, and the circular route with boundary is taken as the test. The improved reward and punishment function is designed to improve the convergence speed of the algorithm and optimize the path so that the robot can plan a safer path while avoiding obstacles first. Compared with Deep Q Network(DQN) algorithm, the convergence speed after improvement is shortened by about 40%, and the loss function is more stable. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Finite-Time Controller for Flexible Satellite Attitude Fast and Large-Angle Maneuver
Symmetry 2022, 14(1), 45; https://doi.org/10.3390/sym14010045 - 30 Dec 2021
Cited by 1 | Viewed by 979
Abstract
In order to deal with the fast, large-angle attitude maneuver with flexible appendages, a finite-time attitude controller is proposed in this paper. The finite-time sliding mode is constructed by implementing the dynamic sliding mode method; the sliding mode parameter is constructed to be [...] Read more.
In order to deal with the fast, large-angle attitude maneuver with flexible appendages, a finite-time attitude controller is proposed in this paper. The finite-time sliding mode is constructed by implementing the dynamic sliding mode method; the sliding mode parameter is constructed to be time-varying; hence, the system could have a better convergence rate. The updated law of the sliding mode parameter is designed, and the performance of the standard sliding mode is largely improved; meanwhile, the inherent robustness could be maintained. In order to ensure the system’s state could converge along the proposed sliding mode, a finite-time controller is designed, and an auxiliary term is designed to deal with the torque caused by flexible vibration; hence, the vibration caused by flexible appendages could be suppressed. System stability is analyzed by the Lyapunov method, and the superiority of the proposed controller is demonstrated by numerical simulation. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Fault-Diagnosis Sensor Selection for Fuel Cell Stack Systems Combining an Analytic Hierarchy Process with the Technique Order Performance Similarity Ideal Solution Method
Symmetry 2021, 13(12), 2366; https://doi.org/10.3390/sym13122366 - 08 Dec 2021
Cited by 6 | Viewed by 1648
Abstract
Multi-Criteria Decision Making (MCDM) methods have rapidly developed and have been applied to many areas for decision making in engineering. Apart from that, the process to select fault-diagnosis sensor for Fuel Cell Stack system in various options is a multi-criteria decision-making (MCDM) issue. [...] Read more.
Multi-Criteria Decision Making (MCDM) methods have rapidly developed and have been applied to many areas for decision making in engineering. Apart from that, the process to select fault-diagnosis sensor for Fuel Cell Stack system in various options is a multi-criteria decision-making (MCDM) issue. However, in light of the choosing of fault diagnosis sensors, there is no MCDM analysis, and Fuel Cell Stack companies also urgently need a solution. Therefore, in this paper, we will use MCDM methods to analysis the fault-diagnosis sensor selection problem for the first time. The main contribution of this paper is to proposed a fault-diagnosis sensor selection methodology, which combines the rank reversal resisted AHP and TOPSIS and supports Fuel Cell Stack companies to select the optimal fault-diagnosis sensors. Apart from that, through the analysis, among all sensor alternatives, the acquisition of the optimal solution can be regarded as solving the symmetric or asymmetric problem of the optimal solution, which just maps to the TOPSIS method. Therefore, after apply the proposed fault-diagnosis sensor selection methodology, the Fuel Cell Stack system fault-diagnosis process will be more efficient, economical, and safe. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization
Symmetry 2021, 13(11), 2208; https://doi.org/10.3390/sym13112208 - 19 Nov 2021
Cited by 4 | Viewed by 1303
Abstract
This paper is devoted to the problem of prescribed performance trajectory tracking control for symmetrical underactuated unmanned surface vessels (USVs) in the presence of model uncertainties and input quantization. By combining backstepping filter mechanisms and adaptive algorithms, two robust control architectures are investigated [...] Read more.
This paper is devoted to the problem of prescribed performance trajectory tracking control for symmetrical underactuated unmanned surface vessels (USVs) in the presence of model uncertainties and input quantization. By combining backstepping filter mechanisms and adaptive algorithms, two robust control architectures are investigated for surge motion and yaw motion. To guarantee the prespecified performance requirements for position tracking control, the constrained error dynamics are transformed to unconstrained ones by virtue of a tangent-type nonlinear mapping function. On the other hand, the inaccurate model can be identified through radial basis neural networks (RBFNNs), where the minimum learning parameter (MLP) algorithm is employed with a low computational complexity. Furthermore, quantization errors can be effectively reduced even when the parameters of the quantizer remain unavailable to designers. Finally, the effectiveness of the proposed controllers is verified via theoretical analyses and numerical simulations. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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Article
Energy Efficiency Enhanced Landing Strategy for Manned eVTOLs Using L1 Adaptive Control
Symmetry 2021, 13(11), 2125; https://doi.org/10.3390/sym13112125 - 08 Nov 2021
Cited by 5 | Viewed by 1787
Abstract
A new landing strategy is presented for manned electric vertical takeoff and landing (eVTOL) vehicles, using a roll maneuver to obtain a trajectory in the horizontal plane. This strategy rejects the altitude surging in the landing process, which is the fatal drawback of [...] Read more.
A new landing strategy is presented for manned electric vertical takeoff and landing (eVTOL) vehicles, using a roll maneuver to obtain a trajectory in the horizontal plane. This strategy rejects the altitude surging in the landing process, which is the fatal drawback of the conventional jumping strategy. The strategy leads to a smoother transition from the wing-borne mode to the thrust-borne mode, and has a higher energy efficiency, meaning a better flight experience and higher economic performance. To employ the strategy, a five-stage maneuver is designed, using the lateral maneuver instead of longitudinal climbing. Additionally, a control system based on L1 adaptive control theory is designed to assist manned driving or execute flight missions independently, consisting of the guidance logic, stability augmentation system and flight management unit. The strategy is verified with the ET120 platform, by Monte Carlo simulation for robustness and safety performance, and an experiment was performed to compare the benefits with conventional landing strategies. The results show that the performance of the control system is robust enough to reduce perturbation by at least 20% in all modeling parameters, and ensures consistent dynamic characteristics between different flight modes. Additionally, the strategy successfully avoids climbing during the landing process with a smooth trajectory, and reduces the energy consumed for landing by 64%. Full article
(This article belongs to the Special Issue Recent Progress in Robot Control Systems: Theory and Applications)
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