Center of Pressure Feedback for Controlling the Walking Stability Bipedal Robots using Fuzzy Logic Controller

This paper presents a sensor-based stability walk for bipedal robots by using force sensitive resistor (FSR) sensor. To perform walk stability on uneven terrain conditions, FSR sensor is used as feedbacks to evaluate the stability of bipedal robot instead of the center of pressure (CoP). In this work, CoP that was generated from four FSR sensors placed on each foot-pad is used to evaluate the walking stability. The robot CoP position provided an indication of walk stability. The CoP position information was further evaluated with a fuzzy logic controller (FLC) to generate appropriate offset angles to be applied to meet a stable situation. Moreover, in this paper designed a FLC through CoP region's stability and stable compliance control are introduced. Finally, the performances of the proposed methods were verified with 18-degrees of freedom (DOF) kid-size bipedal robot

Computer-controlled autonomous model car: A mechatronics project

Mechatronics is a synthesis of mechanical engineering and electronic engineering, and computer engineering, distinct areas that overlap in the design of systems. It represents the interdisciplinary nature of design and development of today\u27s products.;The current research focuses on the design, construction and testing of a computer controlled autonomous model car which can exhibit intelligent behavior such as timed course execution, obstacle detection, and response to sensor inputs. The car is intended as a mechatronics design project that will be integrated into an existing one-semester mechanical engineering undergraduate instrumentation course.;The car was designed around a microprocessor board (Tern Analog Drive) controlled by a 16-bit microcontroller (Tern V104) and equipped with several sensor channels. Two stepper motors were used to propel and guide the car. Photocells were used to detect the path. The control program was written in Turbo C.;The car was tested on a path of reflective white tape about 2 inches wide. The path consists of a 36-inch straight portion followed by a 17-inch radius of curvature curved portion, and completed by a 6-inch straight section with an obstacle at the end. The autonomous car successfully traversed the path and stopped when it detected the obstacle.;It was concluded that a successful mechatronic design project could be developed around the construction and testing of an autonomous car

HARDWARE IMPLEMENTATION OF ARTIFICIAL EPIGENETIC NETWORKS

An extension of Artificial Gene Regulatory Networks (AGRNs), Artificial Epigenetic Networks (AENs) implement an additional layer of bio-inspired control to allow for enhanced performance on certain types of control tasks by facilitating topological self-modification. This work looks to expand the applications of AENs by translating the existent software architecture into a form suitable for implementation on a Field Programmable Gate Array (FPGA). This opens the possibility of AENs being used in applications where high-performance computational resources are impractical, such as robotic control. This thesis develops a more resource efficient architecture for epigenetic networks based on reduced precision integer mathematics, and then translates it into hardware to provide improvements in resource utilisation and execution speed while not sacrificing the unique benefits provided by the epigenetic mechanisms. The application to robotic control is investigated by utilising the hardware AEN to perform various versions of a foraging task, culminating in one designed to replicate a search and rescue scenario. While the AENs did not demonstrate significant performance improvements compared to their non-epigenetic counterparts, this did indicate that not every type of control task benefits from the inclusion of the epigenetic mechanism. In addition, this work investigates another aspect of AENs, specifically the limits of their topological self-modification with respect to reacting to changes in their environment. More specifically, it is asked if an AEN can maintain its ability to perform a specific task when confronted with factors outside of those it has been optimised to handle. While not conclusively demonstrated, there is sufficient evidence that the answer to this question depends on the performance gains imparted by epigenetic behaviors under normal circumstances

Streamlining of the state-dependent Riccati equation controller algorithm for an embedded implementation

In many practical control problems the dynamics of the plant to be controlled are nonlinear. However, in most cases the controller design is based on a linear approximation of the dynamics. One of the reasons for this is that, in general, nonlinear control design methods are difficult to apply to practical problems. The State Dependent Riccati Equation (SDRE) control approach is a relatively new practical approach to nonlinear control that has the simplicity of the classical Linear Quadratic control method. This approach has been recently applied to control experimental autonomous air vehicles with relative success. To make the SDRE approach practical in applications where the computational resources are limited and where the dynamic models are more complex it would be necessary to re-examine and streamline this control algorithm. The main objective of this work is to identify improvements that can be made to the implementation of the SDRE algorithm to improve its performance. This is accomplished by analyzing the structure of the algorithm and the underlying functions used to implement it. At the core of the SDRE algorithm is the solution, in real time, of an Algebraic Riccati Equation. The impact of the selection of a suitable algorithm to solve the Riccati Equation is analyzed. Three different algorithms were studied. Experimental results indicate that the Kleinman algorithm performs better than two other algorithms based on Newton’s method. This work also demonstrates that appropriately setting a maximum number of iterations for the Kleinman approach can improve the overall system performance without degrading accuracy significantly. Finally, a software implementation of the SDRE algorithm was developed and benchmarked to study the potential performance improvements of a hardware implementation. The test plant was an inverted pendulum simulation based on experimental hardware. Bottlenecks in the software implementation were identified and a possible hardware design to remove one such bottleneck was developed

Identification of natural frequency components of articulated flexible structures

M.S.Wayne J. Boo

Robust Navigational Control of a Two-Wheeled Self-Balancing Robot in a Sensed Environment

This research presents an improved mobile inverted pendulum robot called Two-wheeled Self-balancing robot (TWSBR) using a Proportional-Derivative Proportional-Integral (PD-PI) robust control design based on 32-bit microcontroller in a sensed environment (SE). The robot keeps itself balance with two wheels and a PD-PI controller based on the Kalman filter algorithm during the navigation process and is able to stabilize while avoiding acute and dynamic obstacles in the sensed environment. The Proportional (P) control is used to implement turn control for obstacle avoidance in SE with ultrasonic waves. Finally, in a SE, the robot can communicate with any of the Internet of Things (IoT) devices (mobile phone or Personal Computer) which have a Java-based transmission application installed and through Bluetooth technology connectivity for wireless control. The simulation results prove the efficiency of the proposed PD-PI controller in path planning, and balancing challenges of the TWSBR under several environmental disturbances. This shows an improved control system as compared to the existing improved Adaptive Fuzzy Controller

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