Amir H. Ghasemi

An optimal fuzzy controller stabilizing the rod and controlling the position of single wheeled inverted pendulums

Stabilizing the angle while controlling the wheel position in single wheel inverted pendulum systems has always been a challenge for control engineers. The current paper presents a novel hierarchically optimized fuzzy controller to overcome this confrontation. The overall strategy of choosing between conflicting linguistic rules and determination of the knowledge-based of the system is discussed and explained in detail. A fuzzy controller is then designed which is optimized in two steps: At the first, genetic algorithm is used in the integer programming mode to partially optimize the knowledge-based of the system; In the second stage, the designed controller is optimized for performance enhancement. Simulation results ensure the stability and performance of the proposed optimal fuzzy controller.

A Control Theoretic Framework for Optimally Locating Passive Vibration Isolators to Minimize Residual Vibration

This paper investigates the problem of optimally locating passive vibration isolators to minimize residual vibration caused by exogenous disturbance forces. The stiffness and damping properties of the isolators are assumed to be known and the task is to determine the isolator locations, which are nonlinearly related to system states. This paper proposes an approach for reformulating the nonlinear isolator placement problem as a LTI control problem by linking the control forces to measured outputs using a feedforward term. Accordingly, the isolator locations show up as a static output feedback gain matrix which is optimized for residual vibration reduction using standard H∞ optimal control methods. Simulations and experiments on SISO and MIMO case studies are used to demonstrate the merits of the proposed approach. Even though presented in the specific context of ultra-precision manufacturing machines, the proposed method is applicable to the optimal design of other passive systems with nonlinear relationships between design variables and system states.Copyright

Orientation Control Using Oscillating Momentum Wheels

ABSTRACT This paper addresses the problem of controlling a rigidbody’s orientation by actuating sinusoidal oscillations of inter-nal momentum wheels. We consider the rotational dynamics ofa rigid body having three momentum wheels (one for each body-fixed axis) that are attached to the body by springs. Each wheelis actuated by an internal sinusoidal torque of fixed frequency.The frequency of all sinusoidal torques is equal, but the am-plitudes and phases can be varied independently. We analyzethe inverse-dynamics problem of determining the amplitudes andphases for each sinusoidal torque such that a desired orientationis achieved. We then present two closed-loop orientation con-trollers based on this analysis. Numerical simulations demon-strate the effectiveness of the control techniques. INTRODUCTION Reaction wheels and magnetic torquers are standardattitude-control actuators for conventional spacecraft [1–5].However, more efficient techniques may be required for smallersatellites, such as CubeSats. In this paper, we study the dynamicsof a free rigid body with momentum wheels that are actuated by

Logic Analytical Modeling of Piezoelectric Energy Harvesters under Random Base Excitation

Many of energy harvesting devices use piezoelectric elements to convert mechanical vibrations into usable electrical energy. The input excitation is usually assumed to be a deterministic harmonic wave, while in practical situations; the mechanical excitation of the media is a random signal. The objective of this research is to study the energy harvesting in piezoelectric devices using the random vibration theory. At the first step a lumped parameter physical model of the device is presented. A mathematical model is then developed by obtaining the normalized differential equations governing the voltage induced in the energy harvesting circuit as well as the length of the piezoelectric material. The random vibration theory is then utilized to derive analytical expressions for the statistical properties of the voltage, power and the length of the piezoelectric material in terms of the statistical properties of the excitation which is assumed to be a band limited white noise. It is shown that with proper selection of the system parameters, the expected value of the harvested power can be effectively maximized. The qualitative and quantitative knowledge resulting from this effort is expected to enable the analysis, optimization, and synthesis of piezoelectric energy harvesting devices.

Role Negotiation in a Haptic Shared Control Framework

Haptic shared control is a promising means for combining the best of human manual control with automatic control, keeping the human in the loop while avoiding automation pitfalls. In this study, we consider a situation in which both human and the automation system recognize an obstacle but choose different paths of avoidance. While the driver and automation have similar perceptions of the situation, the commands they issue are incompatible and their simple sum is most likely dangerous. To resolve this issue, this study is focused on exploring how roles (i.e. leader and follower) in a haptic collaboration can be negotiated and exchanged between the two partners. Specifically, we test the influence of the timing of cues to promote adoption of leader and follower roles in a shared control task. Preliminary results suggest that haptic feedback can enhance drivability and prevent accidents.

Filtered Dynamic Inversion for Time Delay Systems

This paper addresses the problem of command following for linear, multi-input multi-output, time delay systems using filtered dynamic inversion. The dynamic inversion control input is obtained for linear time-delay systems utilizing the ring framework. This control input is combined with a low-pass-filter to construct a high-gain-stabilizing controller. It is shown that the time-delay-filtered-dynamic-inversion (TD-FDI) uses output feedback, reference-model-input feed-forward, and only requires limited model information. Numerical simulations demonstrate that for sufficiently large choice of a single control parameter, TD-FDI makes the L∞ of the command-following error arbitrarily small.Copyright