P.I.D. equivalent of optimal regulator

Mukhopadhyay, S.

doi:10.1049/el:19780555

Cited by 24 publications

(22 citation statements)

References 1 publication

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“…The model has one fast pole (236.3 rad/s), attributed to the immediate conservation of momentum effect of moving the arms, and one slower pole (16.77 rad/s), which is approximately equal to the nominal gait frequency, and thus attributed to the gait and stepping dynamics. Similar to the approach in [16], the PD feedback law is given by…”

Section: Tuning Of the Feedback Parametersmentioning

confidence: 99%

Omnidirectional bipedal walking with direct fused angle feedback mechanisms

Allgeuer

Behnke

2016

2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)

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An omnidirectional closed-loop gait based on the direct feedback of orientation deviation estimates is presented in this paper. At the core of the gait is an open-loop central pattern generator. The orientation feedback is derived from a 3D nonlinear attitude estimator, and split into the relevant angular deviations in the sagittal and lateral planes using the concept of fused angles. These angular deviations from expected are used by a number of independent feedback mechanisms, including one that controls timing, to perform stabilising corrective actions. The tuning of the feedback mechanisms is discussed, including an LQR-based approach for tuning the transient sagittal response. The actuator control scheme and robot pose representations in use are also addressed. Experimental results on an igus Humanoid Open Platform demonstrate the core concept of this paper, that if the sensor management and feedback chains are carefully constructed, comparatively simple model-free and robot-agnostic feedback mechanisms can successfully stabilise a generic bipedal gait.

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Section: Tuning Of the Feedback Parametersmentioning

confidence: 99%

Omnidirectional bipedal walking with direct fused angle feedback mechanisms

Allgeuer

Behnke

2016

2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)

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“…So know we have two combinations of circuits one is PI-D and I-PD. As suggested in [11], [12] the types are type B and type C respectively.…”

Section: A Types Of Pid Controllersmentioning

confidence: 99%

A Comparative Analysis of Algorithms for Controlling the Attitude of an Unmanned Aerial Vehicle

Khan¹,

Saleem²,

Mushtaq³

et al. 2016

JOACE

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is one of the stimulating problems in robotics. In this regard, we are conducting a survey which investigates an adaptive approach for controlling the attitude of flying robot. This paper aims to present the comparison between different controllers to be used in a dynamic model of a UAV's platform. A survey has been conducted on different types of PID algorithms, which has been considered in three structures with respect of optimal control signal applied to the actuators. A comparative analysis is performed on different stabilizing algorithms. For better performance of Quad-rotor during the hover mode, the cascade control system has been proposed. Another approach Linear Quadratic Regulator is discussed in this paper. All the results are based on the simulation. According to our survey, both PID and LQR should be used for most balanced Quadcopter. 

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“…The present work uses the model structure exposed in [6,12,15] as a starting point but, as a novel contribution, introduces a nonlinear time-varying mathematic model of the rotors used in the DJI F-450 quadrotor (Figure 1), that is used to perform a more detailed and realistic analysis of the control system through numerical simulations. Several methods have been published to control the fly of SUAV [1,2,5,[9][10][11]13,14,[28][29][30][31][32][33][34][35]. In the present work, we propose a control law structure based on a combination of PID and LQR/LQG algorithms but, in contrast to those exposed in others works [5,[30][31][32][33][34][35], a modified LQR/LQG controller is used to obtain the optimal pre-tuning parameters of four PID controllers, commonly employed for attitude and altitude control in multirotor systems (hover maneuver).…”

Section: Introductionmentioning

confidence: 99%

“…Several methods have been published to control the fly of SUAV [1,2,5,[9][10][11]13,14,[28][29][30][31][32][33][34][35]. In the present work, we propose a control law structure based on a combination of PID and LQR/LQG algorithms but, in contrast to those exposed in others works [5,[30][31][32][33][34][35], a modified LQR/LQG controller is used to obtain the optimal pre-tuning parameters of four PID controllers, commonly employed for attitude and altitude control in multirotor systems (hover maneuver). Additionally, the uncertainty affecting the measurements are taken into account through the errors and noise modeling of a LIDAR, an optical flow camera, and a MEMS type MARG (Magnetic, Angular Rate, Gravity) sensor.…”

Section: Introductionmentioning

confidence: 99%

MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

Guardeño¹,

López²,

Sánchez³

2019

Preprint

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In this work a new pre-tuning multivariable PID controllers method for quadrotors is put forward. A procedure based on LQR/LQG theory is proposed for attitude and altitude control. With the aim of analyzing performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, togheter with sensors drift/bias properties and noise characteristics of low-cost comercial sensors typically used in this type of applications (such as MARG with MEMS technology and LIDAR) are considered. In order to estimate the state vector and compensate bias/drift effects on rate gyros of the MARG, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robutsness analysis of the control system is carried out by means of numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show that the proposed pre-tuning method for multivariable PID controller is robust with respect to: a) parametric uncertainty in the plant model, b) disturbances acting at the plant input, c) sensors measurement and estimation errors.One crucial concern to allow the indoor operation of a SUAV is the attitude and position estimation, typically based on the use of inertial measurement units (IMU) and cameras [6,8,[17][18][19][20][21]. To estimate the attitude, position and velocity state variables of the vehicle from the measurements provided by the sensors, a variety of methods are used, such as Kalman filters (KF) [6,18,22,23], extended Kalman filters (EKF) [23][24][25] and complementary filters [4,27] among others.Preprints (www.preprints.org) | NOT PEER-REVIEWED |

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P.I.D. equivalent of optimal regulator

Cited by 24 publications

References 1 publication

Omnidirectional bipedal walking with direct fused angle feedback mechanisms

Omnidirectional bipedal walking with direct fused angle feedback mechanisms

A Comparative Analysis of Algorithms for Controlling the Attitude of an Unmanned Aerial Vehicle

MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

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