Wind Shear Encountered Landing Control Based on CMACs

Juang, Jih Gau; Cheng, Chung Ju; Yang, Teng

doi:10.4028/www.scientific.net/amm.284-287.2351

Cited by 3 publications

(6 citation statements)

References 10 publications

(9 reference statements)

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“…A welltrained SMC-CPSO with adaptive CMAC control scheme can overcome wind shear to 58 ft/s and turbulence to 133 ft/s. The proposed control scheme has better performance than previous studies [7,[30][31][32][33]36] that used PID control, conventional CMAC, self-organizing CMAC, conventional back-propagation network, counter-propagation network, improved backpropagation network, radial basis function network, and multilayer functional-link network. …”

Section: Discussionmentioning

confidence: 78%

“…By conventional ALS, the PID controller can guide the aircraft to overcome wind shear strength to 11 ft/s [33]. Figs.…”

Section: Simulations In Wind Shear Conditionsmentioning

confidence: 99%

“…In past decades, many researchers have applied intelligent concepts to the problem of intelligent landing control [7][8][9][10][11], but those intelligent concepts are not adaptive to various wind disturbance conditions. In previous studies, wind disturbances were considered, but the limits are low [8,[30][31][32][33]. Here, we propose a new control technique that can overcome the limits and make the controller more robust and adaptive to various wind disturbance conditions.…”

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confidence: 98%

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Disturbance encountered landing system design based on sliding mode control with evolutionary computation and cerebellar model articulation controller

Juang

2015

Applied Mathematical Modelling

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a b s t r a c tCurrently, most aircraft have an automatic landing system (ALS) installed. In normal flight conditions, an aircraft automatic landing system can significantly reduce the pilot's workload. Conventional automatic landing systems are designed by the use of gain scheduling or traditional adaptive control techniques; once the flight conditions or wind disturbance intensity is beyond the limits of the system, the pilot must turn off the automatic landing system and manually take over the aircraft landing procedures. The purpose of this study is to integrate the cerebellar model articulation controller (CMAC) and the sliding mode control (SMC) into the aircraft landing system. Genetic algorithm (GA), particle swarm optimization (PSO) and chaotic particle swarm optimization (CPSO) are used to adjust the parameters of the sliding mode control. The proposed intelligent control system can not only effectively improve the landing system to counter wind disturbance, but also help the pilots guide the aircraft to a safe landing in difficult environments. In addition, Lyapunov theory is applied to derive adaptive learning rules for the control system. Furthermore, the TI C6713 rapid property is utilized to develop an embedded control system for a digital signal processing (DSP) controller. The realization of on-line real-time control can thereby be achieved.

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Section: Discussionmentioning

confidence: 78%

“…By conventional ALS, the PID controller can guide the aircraft to overcome wind shear strength to 11 ft/s [33]. Figs.…”

Section: Simulations In Wind Shear Conditionsmentioning

confidence: 99%

mentioning

confidence: 98%

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Disturbance encountered landing system design based on sliding mode control with evolutionary computation and cerebellar model articulation controller

Juang

2015

Applied Mathematical Modelling

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“…Different combinational control schemes are tested. PID control can only overcome wind strength at 11 ft/sec [17]. Fig.…”

Section: Simulationsmentioning

confidence: 99%

A Hybrid Intelligent System for Wind Shear Encountered Aircraft Landing Control

Juang

2015

AMM

Self Cite

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This paper presents sliding mode control (SMC) to aircraft automatic landing system (ALS), and uses genetic algorithm (GA), particle swarm optimization (PSO) and chaos particle swarm optimization (CPSO) to adjust controller parameters. When wind shear is encountered, the aircraft automatic landing system can not be used in such environment during serious wind speed changes. The proposed intelligent control scheme can help the pilots guide the aircraft to a safe landing in wind shear condition. PID control and cerebella model articulation controller (CMAC) are applied to the controller design.

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“…The SMC's parameters are adjusted using a Genetic Algorithm, Chaotic Particle Swarm Optimization (CPSO), and Particle Swarm Optimization (PSO). An intelligent landing scheme based on different CAMCs is presented in [16]. The Lyapunov theory is used for stability analysis and adaptive learning rules.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Landing of an UAV Using H∞ Based Model Predictive Control

Latif

Shahzad²,

Bhatti

et al. 2022

Drones

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Possibly the most critical phase of an Unmanned Air Vehicle (UAV) flight is landing. To reduce the risk due to pilot error, autonomous landing systems can be used. Environmental disturbances such as wind shear can jeopardize safe landing, therefore a well-adjusted and robust control system is required to maintain the performance requirements during landing. The paper proposes a loop-shaping-based Model Predictive Control (MPC) approach for autonomous UAV landings. Instead of conventional MPC plant model augmentation, the input and output weights are designed in the frequency domain to meet the transient and steady-state performance requirements. Then, the H∞ loop shaping design procedure is used to synthesize the state-feedback controller for the shaped plant. This linear state-feedback control law is then used to solve an inverse optimization problem to design the cost function matrices for MPC. The designed MPC inherits the small-signal characteristics of the H∞ controller when constraints are inactive (i.e., perturbation around equilibrium points that keep the system within saturation limits). The H∞ loop shaping synthesis results in an observer plus state feedback structure. This state estimator initializes the MPC problem at each time step. The control law is successfully evaluated in a non-linear simulation environment under moderate and severe wind downburst. It rejects unmeasured disturbances, has good transient performance, provides an excellent stability margin, and enforces input constraints.

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Wind Shear Encountered Landing Control Based on CMACs

Cited by 3 publications

References 10 publications

Disturbance encountered landing system design based on sliding mode control with evolutionary computation and cerebellar model articulation controller

Disturbance encountered landing system design based on sliding mode control with evolutionary computation and cerebellar model articulation controller

A Hybrid Intelligent System for Wind Shear Encountered Aircraft Landing Control

Autonomous Landing of an UAV Using H∞ Based Model Predictive Control

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