A survey of fuzzy control for stabilized platforms

This paper focusses on the application of fuzzy control techniques (fuzzy type-1 and type-2) and their hybrid forms (Hybrid adaptive fuzzy controller and fuzzy-PID controller) in the area of stabilized platforms. It represents an attempt to cover the basic principles and concepts of fuzzy control in stabilization and position control, with an outline of a number of recent applications used in advanced control of stabilized platform. Overall, in this survey we will make some comparisons with the classical control techniques such us PID control to demonstrate the advantages and disadvantages of the application of fuzzy control techniques

Automatic Gain Tuning of a Momentum Based Balancing Controller for Humanoid Robots

This paper proposes a technique for automatic gain tuning of a momentum based balancing controller for humanoid robots. The controller ensures the stabilization of the centroidal dynamics and the associated zero dynamics. Then, the closed-loop, constrained joint space dynamics is linearized and the controller's gains are chosen so as to obtain desired properties of the linearized system. Symmetry and positive definiteness constraints of gain matrices are enforced by proposing a tracker for symmetric positive definite matrices. Simulation results are carried out on the humanoid robot iCub.Comment: Accepted at IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS). 201

Evolution of Neural Networks for Helicopter Control: Why Modularity Matters

The problem of the automatic development of controllers for vehicles for which the exact characteristics are not known is considered in the context of miniature helicopter flocking. A methodology is proposed in which neural network based controllers are evolved in a simulation using a dynamic model qualitatively similar to the physical helicopter. Several network architectures and evolutionary sequences are investigated, and two approaches are found that can evolve very competitive controllers. The division of the neural network into modules and of the task into incremental steps seems to be a precondition for success, and we analyse why this might be so

Stochastic Resonance Can Drive Adaptive Physiological Processes

Stochastic resonance (SR) is a concept from the physics and engineering communities that has applicability to both systems physiology and other living systems. In this paper, it will be argued that stochastic resonance plays a role in driving behavior in neuromechanical systems. The theory of stochastic resonance will be discussed, followed by a series of expected outcomes, and two tests of stochastic resonance in an experimental setting. These tests are exploratory in nature, and provide a means to parameterize systems that couple biological and mechanical components. Finally, the potential role of stochastic resonance in adaptive physiological systems will be discussed

Frequency support characteristics of grid-interactive power converters based on the synchronous power controller

Grid-interactive converters with primary frequency control and inertia emulation have emerged and are promising for future renewable generation plants because of the contribution in power system stabilization. This paper gives a synchronous active power control solution for gridinteractive converters , as a way to emulate synchronous generators for inerita characteristics and load sharing. As design considerations, the virtual angle stability and transient response are both analyzed, and the detailed implementation structure is also given without entailing any difficulty in practice. The analytical and experimental validation of frequency support characteristics differentiates the work from other publications on generator emulation control. The 10 kW simulation and experimental frequency sweep tests on a regenerative source test bed present good performance of the proposed control in showing inertia and droop characteristics, as well as the controllable transient response.Peer ReviewedPostprint (author's final draft

Real Time Optimal Tuning of Quadcopter Attitude Controller Using Particle Swarm Optimization

A real-time novel algorithm for proportional, integral and derivative (PID) controller tuning for quadcopters is introduced. The particle swarm optimization (PSO) method is utilized to search the quadcopter solution space to find the best PID controller parameters. A fuzzy logic (FL) controller is used to provide proper velocity reference signals to serve as tracking set points to be achieved by the PID controller. This nested loop design is proposed for stabilizing the quadcopter, where the fuzzy logic controller (FL) is used in the stable loop (i.e. outer loop) to control the desired angle, while the PID controller is used for the rate loop (i.e. inner loop). Finally, the optimum generated PID parameters were achieved in real time using the PSO search algorithm. The generated parameters were tested successfully using an experimental quadcopter setup at the University of Jordan

Design, Development and Implementation of Intelligent Algorithms to Increase Autonomy of Quadrotor Unmanned Missions

This thesis presents the development and implementation of intelligent algorithms to increase autonomy of unmanned missions for quadrotor type UAVs. A six-degree-of freedom dynamic model of a quadrotor is developed in Matlab/Simulink in order to support the design of control algorithms previous to real-time implementation. A dynamic inversion based control architecture is developed to minimize nonlinearities and improve robustness when the system is driven outside bounds of nominal design. The design and the implementation of the control laws are described. An immunity-based architecture is introduced for monitoring quadrotor health and its capabilities for detecting abnormal conditions are successfully demonstrated through flight testing. A vision-based navigation scheme is developed to enhance the quadrotor autonomy under GPS denied environments. An optical flow sensor and a laser range finder are used within an Extended Kalman Filter for position estimation and its estimation performance is analyzed by comparing against measurements from a GPS module. Flight testing results are presented where the performances are analyzed, showing a substantial increase of controllability and tracking when the developed algorithms are used under dynamically changing environments. Healthy flights, flights with failures, flight with GPS-denied navigation and post-failure recovery are presented

Inertial Stabilization Controller for a 2 DOF Platform

6TH IFAC SYMPOSIUM ON COST ORIENTED AUTOMATION - LCA 2001 () (.2001.BERLIN, ALEMANIA)This paper presents the controller design for the stabilization of a platform of two degrees of freedom. The purpose of this application it is to control the velocities, which are measured in a inertial frame, rejecting the disturbances associated with moving components. A gain-scheduling controller based strategy is proposed, by way of which the desired specifications are accomplished.Ministerio de Ciencia y Tecnología TAP-98-0541Unión Europea 1FD97-078