Multi-mode control based on HSIC for double pendulum robot

Double pendulum robot has four equilibrium points: Down-Down, Down-Up, Up-Down, and Up-Up. Define the transfer control from one equilibrium point to another equilibrium point as acrobatic action of DPR, and there are total of 20 acrobatic actions. This paper proposes the multi-mode control algorithm based on Human Simulated Intelligent Control theory for the realization process of those acrobatic actions, which has the structure of multi sub-controllers and multi control modes. As an example, the acrobatic action from Down-Up to Up-Down is realized in simulation and real-time experiments, and the results demonstrate the effectiveness of the proposed algorithm

Push Recovery for Humanoid Robots using Linearized Double Inverted Pendulum

Biped robots have come a long way in imitating a human being\u27s anatomy and posture. Standing balance and push recovery are some of the biggest challenges for such robots. This work presents a novel simplified model for a humanoid robot to recover from external disturbances. The proposed Linearized Double Inverted Pendulum, models the dynamics of a complex humanoid robot that can use ankle and hip recovery strategies while taking full advantage of the advances in controls theory research. To support this, an LQR based control architecture is also presented in this work. The joint torque signals are generated along with ankle torque constraints to ensure the Center of Pressure stays within the support polygon. Simulation results show that the presented model can successfully recover from external disturbances while using minimal effort when compared to other widely used simplified models. It optimally uses the the torso weight to generate angular momentum about the pelvis of the robot to counter-balance the effects of external disturbances. The proposed method was validated on simulated `TigerBot-VII\u27, a humanoid robot

The Implementation and Comparison of Fuzzy Logic Control Systems to Modern Control Methods on Low-Cost Hardware

Modern control engineering provides many options to automate systems for which a mathematical model is required. Another control does not rely on the mathematical model of the system and is known as fuzzy logic control. In this study, a literature review is conducted on existing control systems strategies such as proportional integral and derivative (PID), linear quadratic regulator (LQR), and fuzzy logic controller (FLC), the complexity of the systems they control, and their strengths and weaknesses. In addition, a series of experiments are conducted, both through simulations in MATLAB Simulink and using their implementation using the actual physical hardware to test the effectiveness of said controllers. The effect of changing fuzzy logic membership functions is also determined. The settling times of controllers are compared using a physical prototype of a mechanical arm. Lastly, dead zone correction techniques are addressed and implemented

Fuzzy-Immune-Regulated Adaptive Degree-of-Stability LQR for a Self-Balancing Robotic Mechanism: Design and HIL Realization

This letter formulates a fuzzy-immune adaptive system for the online adjustment of the Degree-of-Stability (DoS) of Linear-Quadratic-Regulator (LQR) procedure to strengthen the disturbance attenuation capacity of a self-balancing mechatronic system. The fuzzy-immune adaptive system uses pre-configured control input-based rules to alter the DoS parameter of LQR for dynamically relocating the closed-loop system's eigenvalues in the complex plane's left half. The corresponding changes in the eigenvalues are conveyed to the Riccati equation, which eventually yields the self-adjusting LQR gains. This arrangement allows for the flexible manipulation of the applied control effort and the response speed as the error conditions change. The efficacies of the self-tuning LQR scheme are verified by performing custom-designed hardware-in-the-loop experiments on the Quanser rotary inverted pendulum system. As compared to the DoS-LQR, the proposed controller improves the pendulum's transient recovery time, overshoots, input demands, and offsets by 32.3%, 50.5%, 33.9%, and 33.3%, respectively, under disturbances. These experimental outcomes verify that the proposed self-tuning LQR law considerably improves the system's disturbance attenuation capability

The control strength quantification analysis of outer pendulum rod for double inverted pendulum

Due to the complexity of the dynamics characteristics of an inverted pendulum, and the problem that the linearization analyze method cannot satisfy the controlling requirement, a nonlinear dynamics analyze method was proposed. Through decoupling the dynamics model of a double inverted pendulum, the outer pendulum rod motion equation was derived. And then, aiming at the control strength function of outer pendulum rod, the qualitative and quantitative relationship between spatial position of pendulum rod and the control strength of outer rod, and the quantification relationship between dynamics parameters and the control strength of outer rod were separately analyzed. And the simulation verified the correctness of the analysis

Pendulum: Controlling an inverted pendulum using fuzzy logic

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CYCLOIDAL GAIT WITH DOUBLE SUPPORT PHASE FOR THE NAO HUMANOID ROBOT

The commercial Nao humanoid robot has 11 DOF in legs. Even if these legs include 12 revolute joints, only 11 actuators are employed to control the walking of the robot. Under such conditions, the mobility of the pelvis and that of the oscillating foot are mutually constrained at each step. Besides, the original gait provided by the manufacturer company of the Nao employs only single support phases during the walking. Because of both issues, the reduced mobility in legs and the use of only single support phases, the stability of the walking is affected. To contribute to improving such stability, in this paper an approach is proposed that incorporates a double support phase and a gait based on cycloidal time functions for motions of the pelvis and those of the oscillating foot. To assess the stability of the walking an index is applied, which is based on the notion of zero-moment point (ZMP) of the static foot at each step. Results of experimental tests show that the proposed gait enhances the stability of the robot during the walking