Analytical design of control system mathematical models for mobile robots based on the methods of inverse problems of dynamics and modal PID controllers

Сизых, В. Н.; Antoshkin, S. B.; Daneev, Roman; Bakanov, M.V.; Livshits, A. V.; Aa, Aleksandrov

doi:10.1088/1757-899x/760/1/012053

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…The new mini-batch is randomly determined from the training set and used for the next iteration. The learning rate is decreased during optimization [ 23 ].…”

Section: Methodsmentioning

confidence: 99%

Predictive Control of the Mobile Robot under the Deep Long-Short Term Memory Neural Network Model

Zheng

2022

Computational Intelligence and Neuroscience

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At present, there is a phenomenon of network data packet loss in the trajectory tracking control system, which will degrade or even destabilize the system’s performance. Therefore, this work first explains the theory of the deep long-short term memory (LSTM) neural network model, the kinematic model of mobile robots, and the trajectory tracking error model. The reasons for data packet loss in the control system are analyzed. Second, a prediction model based on the LSTM network is designed according to the theory mentioned above. Finally, the training effect of the LSTM model and the robot trajectory tracking effect based on the model are tested by setting up simulation experiments. The research results are as follows: (1) The pose test error of the mobile robot will eventually tend to zero through the simulation curve generated by the pose parameters (x, y, θ) of the mobile robot. (2) The trajectory tracking error of the deep LSTM neural network prediction and compensation method with the packet loss rate of 5% is less than that with the packet loss rate of 10%. (3) The linear velocity υ of the mobile robot based on the prediction model of the LSTM network varies greatly but is always in the interval (−2, 2). Its angular velocity ω initially fluctuates greatly but gradually tends to zero after about 13 s. (4) When the prediction model tracks the trajectory of the robot, the horizontal position x, the vertical position y, and the angle θ coincide with the reference trajectory. The exploration is conducted to provide a reference for the research on data packet loss in the networked mobile robot trajectory tracking system.

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“…The new mini-batch is randomly determined from the training set and used for the next iteration. The learning rate is decreased during optimization [ 23 ].…”

Section: Methodsmentioning

confidence: 99%

Predictive Control of the Mobile Robot under the Deep Long-Short Term Memory Neural Network Model

Zheng

2022

Computational Intelligence and Neuroscience

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“…Controller x, y generates a control signal ̄1, which creates forces that ensure movement quadrotor in the x, y plane. This controller functions according to the mathematical model ( 5), (6). The controller z generates a control signal ̄2, which affects the movement plant along the third coordinate, its movement given by the (7), (21).…”

Section: The Synthesis Of Control Lawmentioning

confidence: 99%

“…The authors [4]- [6] utilized a control system scheme is implementing the inverse dynamics of a controlled object using a PID (PD) controller. As is known [7], [8], the PID controller requires adjustment; the high-frequency components of the error signal introduce additional noise into the control channel; also, large-amplitude control pulses may appear in cases of a jump change in the error signal.…”

Section: Introductionmentioning

confidence: 99%

Stabilizing the spatial position of a quadrotor by the backstepping procedure

Kucherov

Kozub²,

Sushchenko

et al. 2021

IJEECS

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<div>The paper considers the problem of synthesizing a control law that stabilizes the spatial position of an airborne object. The control object is a quadrotor with nonlinear dynamics. To solve the stabilization problem, a mathematical model of the quadrotor has been developed, taking into account its positionin the Cartesian and Euler coordinate systems. The new control law has been synthesized using the backstepping procedure. This control law is based on the Lyapunov-type stabilization criterion. New results analysis of the quadrotor dynamics, where has been showing the dependence of the control accuracy on the parameter of the stabilization criterion also presented. An algorithm for the directed search of the procedure parameter also has been proposed. It ensures the desired quality of the transient process. Simulation results confirming the results of the oretical research have been presented as well.</div>

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Analytical design of control system mathematical models for mobile robots based on the methods of inverse problems of dynamics and modal PID controllers

Cited by 2 publications

References 7 publications

Predictive Control of the Mobile Robot under the Deep Long-Short Term Memory Neural Network Model

Predictive Control of the Mobile Robot under the Deep Long-Short Term Memory Neural Network Model

Stabilizing the spatial position of a quadrotor by the backstepping procedure

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