
This paper presents a study on controlling a rotary inverted pendulum (RIP) system using a hierarchical sliding mode control (HSMC) approach. The objective is to swing up and stabilize the pendulum at a desired position. The proposed HSMC controller addresses the underactuation challenge through a hierarchical structure of sliding surfaces. The particle swarm optimization (PSO) algorithm is used to optimize the controller parameters. Simulations were performed to evaluate the performance of the HSMC controller at different initial pendulum angles, demonstrating its effectiveness in achieving swing-up and stabilization. The integration of the PSO algorithm enhances the controller’s adaptability and robustness, emphasizing the benefits of combining optimization algorithms with controller parameter tuning for underactuated systems like the RIP.
Artificial intelligence, Swing, Sliding mode control, swing-up and stabilization, Sliding Mode Control, FOS: Mechanical engineering, hierarchical sliding mode control, Control (management), Hydraulic Systems Control and Optimization, Mode (computer interface), Quantum mechanics, rotary inverted pendulum, Adaptive Control, Yaw Stability Control, tuning controller, Engineering, Double inverted pendulum, Control theory (sociology), T1-995, Inverted pendulum, Finite-Time Stability, Technology (General), particle swarm optimization, Mechanical Engineering, Physics, Active Steering, Computer science, Mechanical engineering, Operating system, Control and Systems Engineering, Advanced Vehicle Dynamics Control Systems, Physical Sciences, Automotive Engineering, Nonlinear system, Robotic Control and Stabilization Techniques
Artificial intelligence, Swing, Sliding mode control, swing-up and stabilization, Sliding Mode Control, FOS: Mechanical engineering, hierarchical sliding mode control, Control (management), Hydraulic Systems Control and Optimization, Mode (computer interface), Quantum mechanics, rotary inverted pendulum, Adaptive Control, Yaw Stability Control, tuning controller, Engineering, Double inverted pendulum, Control theory (sociology), T1-995, Inverted pendulum, Finite-Time Stability, Technology (General), particle swarm optimization, Mechanical Engineering, Physics, Active Steering, Computer science, Mechanical engineering, Operating system, Control and Systems Engineering, Advanced Vehicle Dynamics Control Systems, Physical Sciences, Automotive Engineering, Nonlinear system, Robotic Control and Stabilization Techniques
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
