Adaptive IDA-PBC for underactuated mechanical systems with constant disturbances

This work investigates the control of nonlinear underactuated mechanical systems with matched and unmatched constant disturbances. To this end, a new control strategy is proposed, which builds upon the interconnection‐and‐damping‐assignment passivity‐based control, augmenting it with an additional term for the purpose of disturbance compensation. In particular, the disturbances are estimated adaptively and then accounted for in the control law employing a new matching condition of algebraic nature. Stability conditions are discussed, and for comparison purposes, an alternative controller based on partial feedback linearization is presented. The effectiveness of the proposed approach is demonstrated with numerical simulations for three motivating examples: the inertia wheel pendulum, the disk‐on‐disk system, and the pendulum‐on‐cart system

Design and Control of a Two-Wheeled Robotic Walker

This thesis presents the design, construction, and control of a two-wheeled inverted pendulum (TWIP) robotic walker prototype for assisting mobility-impaired users with balance and fall prevention. A conceptual model of the robotic walker is developed and used to illustrate the purpose of this study. A linearized mathematical model of the two-wheeled system is derived using Newtonian mechanics. A control strategy consisting of a decoupled LQR controller and three state variable controllers is developed to stabilize the platform and regulate its behavior with robust disturbance rejection performance. Simulation results reveal that the LQR controller is capable of stabilizing the platform and rejecting external disturbances while the state variable controllers simultaneously regulate the system’s position with smooth and minimum jerk control. A prototype for the two-wheeled system is fabricated and assembled followed by the implementation and tuning of the control algorithms responsible for stabilizing the prototype and regulating its position with optimal performance. Several experiments are conducted, confirming the ability of the decoupled LQR controller to robustly balance the platform while the state variable controllers regulate the platform’s position with smooth and minimum jerk control

Dual-mode model predictive control of an omnidirectional wheeled inverted pendulum

This article describes the position and heading control of a novel form of omnidirectional wheeled inverted pendulum platform known as a Collinear Mecanum Drive. This concept uses four collinear Mecanum wheels to balance in a similar manner to a typical two-wheeled inverted pendulum, whilst also being able to simultaneously translate directly along its balance axis. Control is performed using a constrained time-optimal infinite horizon model predictive controller, with feasibility maintained across the full reference input set. Explored in this article is the derivation of the system dynamics model and controller, a systematic approach to selection of controller parameters and analysis of their effect on control performance and complexity, and an evaluation of the controller's efficacy in both simulation and on a real-world experimental prototype for simple and complex trajectories

Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system: A comparative assessment

This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. The particle swarm optimization and spiral dynamic algorithm are used for enhanced performance of the IT2FLC by finding optimised values for input and output controller gains and parameter values of IT2FLC membership function as comparison purpose in order to identify better solution for the system. A new model of triple-link inverted pendulum on two-wheels system, developed within SimWise 4D software environment and integrated with Matlab/Simulink for control purpose. Several tests comprising system stabilization, disturbance rejection and convergence accuracy of the algorithms are carried out to demonstrate the robustness of the control approach. It is shown that the particle swarm optimization-based control mechanism performs better than the spiral dynamic algorithm-based control in terms of system stability, disturbance rejection and reduce noise. Moreover, the particle swarm optimization-based IT2FLC shows better performance in comparison to previous research. It is envisaged that this system and control algorithm can be very useful for the development of a mobile robot with extended functionality

Contributions to ida-pbc with adaptive control for underactuated mechanical systems

This master thesis is devoted to developing an adaptive control scheme for the well- known Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) technique. The main objective of this adaptive scheme is to asymptotically stabilize a class of Underactuated Mechanical Systems (UMSs) in the presence of uncertainties (not necessarily matched). This class of UMSs is characterized by the solvability of the Partial Differential Equation (PDE) resulting from the IDA-PBC technique. Two propositions are stated in this work to design the adaptive IDA-PBC. One of the main properties of these propositions is that even though the parameter estimation conver- gence is not guaranteed, the adaptive IDA-PBC achieves asymptotic stabilization. To illustrate the effectiveness of these propositions, this work performs simulations of the Inertia Wheel Inverted Pendulum (IWIP) system, considering a time-dependent input disturbance, a type of physical damping, i.e., friction (not considered in the standard IDA-PBC methodology), and parameter uncertainties in the system (e.g., inertia).Tesi

Model-free controller design for nonlinear underactuated systems with uncertainties and disturbances by using extended state observer based chattering-free sliding mode control

MakaleWOS:000912458400001Most of the control strategies require a mathematical model or reasonable knowledge that is difficult to obtain for complex systems. Model-free control is a good alternative to avoid the difficulties and complex modeling procedures, especially if the knowledge about the system is insufficient. This paper presents a new control scheme completely independent of the system model. The proposed scheme combines sliding mode control (SMC) with intelligent proportional integral derivative (iPID) control based on a local model and extended state observer (ESO). Although the iPID control makes the proposed method model-free, it cannot guarantee that the tracking errors converge to zero asymptotically except the system is in a steady-state regime. Therefore, the SMC is added to the control scheme to ensure the convergence by minimizing the estimation errors of the observer. The proposed iPIDSMC controller is tested in the presence of different parameter variations and external disturbances on an inverted pendulum - cart (IPC), which is a highly unstable underactuated system with nonlinear coupled dynamics. The proposed controller is compared with the PID, iPID and Hierarchical Sliding Mode Control (HSMC) for a clearer evaluation. Simulation results showed that the proposed controller is extremely insensitive to parameter variations, matched and mismatched disturbances and the control signal of the proposed method is chattering-free, even though it is based on a discontinuous control action

適応制御戦略に基づく車輪型二足歩行ロボットのバランス安定性の向上

Tohoku University林部充宏課

ROS-based Controller for a Two-Wheeled Self-Balancing Robot

In this article, a controller based on a Robot Operating System (ROS) for a two-wheeled self-balancing robot is designed. The proposed ROS architecture is open, allowing the integration of different sensors, actuators, and processing units. The low-cost robot was designed for educational purposes. It used an ESP32 microcontroller as the central unit, an MPU6050 Inertial Measurement Unit sensor, DC motors with encoders, and an L298N integrated circuit as a power stage. The mathematical model is analyzed through Newton-Euler and linearized around an equilibrium point. The control objective is to self-balance the robot to the vertical axis in the presence of disturbances. The proposed control is based on a bounded saturation, which is lightweight and easy to implement in embedded systems with low computational resources. Experimental results are performed in real-time under regulation, conditions far from the equilibrium point, and rejection of external disturbances. The results show a good performance, thus validating the mechanical design, the embedded system, and the control scheme. The proposed ROS architecture allows the incorporation of different modules, such as mapping, autonomous navigation, and manipulation, which contribute to studying robotics, control, and embedded systems