Adaptive Model Predictive Control of a Quadrotor

Chikasha, Piwai Nigel; Dube, Chioniso

doi:10.1016/j.ifacol.2017.12.029

Cited by 34 publications

(8 citation statements)

References 9 publications

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“…In the above-mentioned solution, MPC is active in trajectory planning and tracking, since it considers various software and hardware constraints in the design and can achieve a finite-time online optimization [21][22][23]. The quadrotor should meet the constraints imposed by the control input and the terminal state while autonomously landing, rendering MPC an effective control strategy.…”

Section: Introductionmentioning

confidence: 99%

“…(1) Upon combining MPC trajectory planning and INDI flight control, a novel visionbased landing system is developed, able to land rapidly and accurately on a maneuvering platform with a certain disturbance rejection capability. (2) Compared with the previous research on MPC-based trajectory tracking control for quadrotors [16,23,28], the proposed method with variable sampling time reduces the requirements of the onboard computer while ensuring the landing accuracy. (3) At variance with what is used in other landing systems, we employ distinct objective functions for the different modes correspondingly, to realize the real-time-optimized landing of the quadrotor.…”

Section: Introductionmentioning

confidence: 99%

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Autonomous Landing of a Quadrotor on a Moving Platform via Model Predictive Control

Guo

Tang²,

Wang

et al. 2022

Aerospace

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Landing on a moving platform is an essential requirement to achieve high-performance autonomous flight with various vehicles, including quadrotors. We propose an efficient and reliable autonomous landing system, based on model predictive control, which can accurately land in the presence of external disturbances. To detect and track the landing marker, a fast two-stage algorithm is introduced in the gimbaled camera, while a model predictive controller with variable sampling time is used to predict and calculate the entire landing trajectory based on the estimated platform information. As the quadrotor approaches the target platform, the sampling time is gradually shortened to feed a re-planning process that perfects the landing trajectory continuously and rapidly, improving the overall accuracy and computing efficiency. At the same time, a cascade incremental nonlinear dynamic inversion control method is adopted to track the planned trajectory and improve robustness against external disturbances. We carried out both simulations and outdoor flight experiments to demonstrate the effectiveness of the proposed landing system. The results show that the quadrotor can land rapidly and accurately even under external disturbance and that the terminal position, speed and attitude satisfy the requirements of a smooth landing mission.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Autonomous Landing of a Quadrotor on a Moving Platform via Model Predictive Control

Guo

Tang²,

Wang

et al. 2022

Aerospace

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“…Other methods, such as nonlinear inverse dynamics [9], including feedback linearisation [11], adaptive control [12] and sliding mode controllers [13], have also been applied with moderate success.…”

Section: Introductionmentioning

confidence: 99%

Optimised Tuning of a PID-Based Flight Controller for a Medium-Scale Rotorcraft

Mpanza

Pedro

2021

Algorithms

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This paper presents the parameter optimisation of the flight control system of a singlerotor medium-scale rotorcraft. The six degrees-of-freedom (DOF) nonlinear mathematical model of the rotorcraft is developed. This model is then used to develop proportional–integral–derivative (PID)-based controllers. Since the majority of PID controllers installed in industry are poorly tuned, this paper presents a comparison of the optimised tuning of the flight controller parameters using particle swarm optimisation (PSO), genetic algorithm (GA), ant colony optimisation (ACO) and cuckoo search (CS) optimisation algorithms. The aim is to find the best PID parameters that minimise the specified objective function. Two trim conditions are investigated, i.e., hover and 10 m/s forward flight. The four algorithms performed better than manual tuning of the PID controllers. It was found, through numerical simulation, that the ACO algorithm converges the fastest and finds the best gains for the selected objective function in hover trim conditions. However, for 10 m/s forward flight trim, the GA algorithm was found to be the best. Both the tuned flight controllers managed to reject a gust wind of up to 5 m/s in the lateral axis in hover and in forward flight.

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“…Multiple control schemes, such as proportional-integralderivative (PID) [6][7][8], backstepping control [9,10], adaptive control [11][12][13], model predictive control (MPC) [14,15], sliding mode control (SMC) [16][17][18], intelligent control [19][20][21], H ∞ control [22], robust control [23,24], are applied to the attitude control of the quadrotor. In this introduction, the trajectory tracking control of the quadrotor under modeling uncertainties and unknown disturbances is concerned.…”

Section: Introductionmentioning

confidence: 99%

“…The adaptive gains are obtained to compensate the unknown disturbances. A recursive least squares (RL-S) algorithm is introduced to estimate model parameters of a quadrotor in [15], and an adaptive MPC is presented by using the model parameters. In [18], a high-order sliding mode observer (SMO) is introduced to estimate the lumped disturbances.…”

Section: Introductionmentioning

confidence: 99%

Robust Dual-Channel Disturbance Rejection Attitude Control for a Quadrotor UAV: Theory and Experiment

Pan

Xiong

2021

Preprint

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In this paper, a robust dual-channel disturbance rejection control based on an inner-outer loop control framework is proposed for the attitude control of the quadrotor under modeling uncertainties and unknown disturbances. In the outer loop, a tracking differentiator is introduced to obtain smooth tracking signals and their derivatives. In addition, an outer loop controller is developed with the tracking signals set as the desired signals. In the inner loop, a robust dual-channel disturbance rejection controller based on a sliding mode observer is constructed, which contains an inner disturbance rejection channel (IDRC) and an outer disturbance rejection channel (ODRC). In the IDRC, a disturbance rejection compensator is designed to obtain the disturbance compensation values and to compensate a part of the lumped disturbances in the attitude dynamic model. In the ODRC, an inner loop controller with variable-gain switching terms and constant-gain switching terms is designed, whose switching terms are used to compensate the remaining part of the lumped disturbances in the attitude dynamic model. By using the proposed control scheme, the robustness is guaranteed, and the chattering phenomenon caused by the variable-gain switching terms is greatly reduced. The stability of the proposed scheme is analyzed by using the Lyapunov theory. Finally, the effectiveness is tested by the platform experiments.

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Adaptive Model Predictive Control of a Quadrotor

Cited by 34 publications

References 9 publications

Autonomous Landing of a Quadrotor on a Moving Platform via Model Predictive Control

Autonomous Landing of a Quadrotor on a Moving Platform via Model Predictive Control

Optimised Tuning of a PID-Based Flight Controller for a Medium-Scale Rotorcraft

Robust Dual-Channel Disturbance Rejection Attitude Control for a Quadrotor UAV: Theory and Experiment

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