Integrated SolidWorks and Simscape platform for the design and control of an inverted pendulum system

Alkamachi, Ahmed

doi:10.2478/jee-2020-0018

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…12, No. 6, December 2022: 5911-5922 5912 design some mechanical applications, for example, inverted pendulum systems, without the need to derive the complex differential equations [11]. Despite the number of self-balancing platforms' previous physical design built by integration components (mechanical, electronic, and hydraulic) to compensate for the platform's tilt by external disturbance signal or moving on the uneven ground.…”

Section: Introductionmentioning

confidence: 99%

A self-balancing platform on a mobile car

Tawfeeq

Salloom

Alkamachi

2022

IJECE

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<span lang="EN-US">In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, and industry. In this paper, the physical prototype of a proposed self-balancing platform that described the self-balancing attitude in the (X-axis, Y-axis, or biaxial) under the influence of road disturbance has been introduced. In the physical prototype, the inertial measurement unit (IMU) sensor will sense the disturbance in (X-axis, Y-axis, and biaxial). With the determined error, the corresponding electronic circuit, DC servo motors, and the Arduino software, the platform overcame the tilt angle(disturbance). Optimization of the proportional-integral-derivative (PID) controllers’ coefficients by the genetic algorithm method effectively affected the performance of the platform, as the platform system is stable and the platform was able to compensate for the tilt angle in (X-axis, Y-axis, and both axes) and overcome the error in a time that does not exceed four seconds. Therefore, a proposed self-balancing platform’s physical prototype has a high balancing accuracy and meets operational requirements despite the platform’s simple design.</span>

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Section: Introductionmentioning

confidence: 99%

A self-balancing platform on a mobile car

Tawfeeq

Salloom

Alkamachi

2022

IJECE

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“…Still, Simscape Multibody software works in the Simulink environment and interface with Simulink and Matlab flawlessly [6] [7]. The Simulink and Simscape software has been used to build and control the inverted pendulum system without the need to derive a complicated system of mathematical differential equations [8].…”

Section: Introductionmentioning

confidence: 99%

Simulation of a Self-Balancing Platform on the Mobile Car

Tawfeeq¹,

Salloom²,

Alkamachi³

2021

alkej

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In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, industry. This paper introduced the simulated model of a proposed self-balancing platform that described the self–balancing attitude in (X-axis, Y-axis, or both axis) under the influence of road disturbance. To simulate the self-balanced platform's performance during the tilt, an integration between Solidworks, Simscape, and Simulink toolboxes in MATLAB was used. The platform's dynamic model was drawn in SolidWorks and exported as a STEP file used in the Simscape Multibody environment. The system is controlled using the proportional-integral-derivative (PID) controller to maintain the platform leveled and compensate for any road disturbances. Several road disturbances scenarios were designed in the x-axis, y-axis, or both axis (the pitch and roll angles) to examine the controller effectiveness. The simulation results indicate that that the platform completed self-balancing under the effect of disturbance (10° and -10°) on the X-axis, Y-axis, and both axes in less than two milliseconds. Therefore, a proposed self-balancing platform's simulated model has a high self-balancing accuracy and meets operational requirements despite its simple design.

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Section: System Modellingmentioning

confidence: 99%

“…On the other hand, some researchers have not established mathematical dynamical equations, rather, they have used physical software model instead; for instance, the single inverted pendulum based on track model presented by Alkamachi (2020). Alkamachi (2020), is that the Simscape transformation is not needed as researchers can import the dynamic model from Visual Nastran 4D to Simulink directly. Furthermore, Zabihifar et al (2020) also presented an adaptive neural network to stabilise a rotary inverted pendulum model, using the multibody dynamics software, namely ADAMS, which is a product of MSC software company, similar to the one used in Ahmad & Siddique (2011).…”

Section: System Modellingmentioning

confidence: 99%

Nonlinear optimal control and its application to a two-wheeled robot

Kokkrathoke¹

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This research studies two advanced nonlinear optimal control techniques, i.e., the freezing control and the iteration scheme, and their associated applications, such as a single inverted pendulum (IP) on a cart system and a two-wheeled robot (TWR) system. These techniques are applied to stabilise the highly unstable nonlinear systems in the vertical upright position when facing different initial pitch angles. Different linear optimal controllers (linear quadratic regulator and linear quadratic Gaussian) and nonlinear optimal controllers are designed and applied to the models for concurrent control of all state variables. The controlled systems are tested in simulation and the best performing control design is eventually implemented on a robot prototype built with an educational kit – the LEGO EV3, after practical factors such as motor voltage limitation, gyro sensor drift and model uncertainties have been considered, analysed and dealt with. Simulations and experiments on the TWR robot prototype demonstrate the superiority of the nonlinear freezing optimal control technique, showing larger operation ranges of the robot pitch angle and better response performances (i.e., shorter rise time, less overshoot and reduced settling time) than the linear optimal control methods. In particular, a novel mixing method to create a new nonlinear model (Model AB) from two different models on the same physical prototype with an increased controllable region of the TWR system is introduced, for the first time, for the calculations of optimal feedback gains for the system. Significantly, the utilisation of this mixed model, combined with the nonlinear freezing controller, achieves true global control of the TWR, even from an initial pitch angle of 90° (i.e., the horizontal position), when a motor with a saturated voltage of 48V and nominal torque of 298 mNm is adopted in simulation tests. This is wider than the angle achievable from the primary model (Model A) and any other single feedback control method on TWR reported in the literature. Robustness tests when introducing model uncertainties by adding mass and height on the TWR also illustrate excellent control performances from the nonlinear optimal control in both simulations and hardware implementations.

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Integrated SolidWorks and Simscape platform for the design and control of an inverted pendulum system

Cited by 3 publications

References 18 publications

A self-balancing platform on a mobile car

A self-balancing platform on a mobile car

Simulation of a Self-Balancing Platform on the Mobile Car

Nonlinear optimal control and its application to a two-wheeled robot

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