Controller Design of Multiinput Multioutput Time-Delay Large-Scale System by Chia-Wei Lin, Tzuu-Hseng S. Li, Chung-Cheng Chen

“…We have simulated the two-inverted-pendulum system coupled by a spring for networked control systems which has been used as a test bed for the study of decentralized control of large-scale systems.…”
Get full text

Proportional PDC Design-Based Robust Stabilization and Tracking Control Strategies for Uncertain and Disturbed T-S Model by Chekib Ghorbel, Amira Tiga, Naceur Benhadj Braiek

“…Finally, to illustrate the merit of our purpose, numerical simulation studies of stabilizing and tracking an inverted pendulum system are presented.…”
Get full text

STABILITY CONTROL MODELLING UNDER DYNAMIC MOTION SCENARIO OF A DIFFERENTIAL DRIVE ROBOT by ADEDOTUN O. OWOJORI, KAYODE F. AKINGBADE, WALIU O. APENA, ERASTUS O. OGUNTI

“…Basically, differential drive robotic system describes an unstable, nonlinear system related to an inverted pendulum. The research attempts to harness the parameters obtained from a computer-aided design tool (Solid works) to model the system for complete stability control and dynamic motion of the system within a planned trajectory. …”
Get full text

The right way to ride the wrong bike: An exploration of Klein's 'unridable' bicycle. by B D Coller

“…The secret is revealed through an exploration of the dynamics and control of the bike that contains three elements: (1) modeling the physics of the actively steered bicycle as an inverted pendulum riding atop a carriage; (2) recognizing that the steer kinematics leads to competing physical mechanisms which an aspiring rider might exploit; and (3) examining limitations of controllability and stabilizability of the system from a state space perspective. …”
Get full text

Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
Get full text

Motion Intention Analysis-Based Coordinated Control for Amputee-Prosthesis Interaction by Fei Wang, Shiguang Wen, Chengdong Wu, Yuzhong Zhang, Jincheng Li

“…In homogeneous configuration, two identical artificial legs (ALs) were used to simulate the symmetrical lower limbs of a healthy person. Linear inverted pendulum model combining with ZMP stability criterion was used to generate the gait trajectories of ALs. …”
Get full text

Benchmarking Standing Stability for Bipedal Robots by Juan A. JUANCASTANO, Eugenio Manuel Espuela, Jaime Ramos Rojas, Enrico Mingo Hoffman, Chengxu Zhou

“…This paper presents a standardized benchmarking procedure based on the Linear Inverted Pendulum Model and the Capture Point concept to normalize the maximum angular momentum before falling. …”
Get full text

Flexible Model Predictive Control for Bounded Gait Generation in Humanoid Robots by Tianbo Yang, Yuchuang Tong, Zhengtao Zhang

“…Traditional Model Predictive Control (MPC) methods based on Linear Inverted Pendulum (LIP) or Cart–Table (C-T) methods are straightforward and linear but inadequate for robots with flexible joints and linkages. …”
Get full text