Matthew W. Dunnigan

System level simulation of a double stator wobble electrostatic micromotor

Abstract System level simulation results of an electrostatic micromotor, based on closed-form expressions of the static and dynamic torque behaviours, are presented. A double stator, double rotor, wobble motor designed and tested at Heriot Watt University is simulated using the high level language very high speed integrated circuits (VHSIC) hardware description language-analogue mixed signal (VHDL-AMS). The analytical torque model is obtained by two conformal mapping transformations of the electrostatic gap region between the stator and rotor surfaces. Torque results obtained by finite element analysis methods and the proposed simulation model show good agreement. Simulation results of the closed-loop control of the excitation of the motor, based on the dynamic model of the torque, are also presented.

Ant Colony Robot Motion Planning

A new approach to robot motion planning is proposed by applying ant colony optimization with the probabilistic roadmap planner (PRM). The PRM is a path planning method that consists of capturing the connectivity of the robots free space in a network called the roadmap. An ant colony robot motion planning (ACRMP) method is proposed that takes the benefit of collective behaviour of ants foraging from a nest to a food source. Two groups of ants are placed at both the nest and food source respectively. A number of ants (agents) are released from the nest (start configuration) and begin to forage (search) towards the food (goal configuration). Each ant has a certain quantity of pheromone to be dropped along the path. The ants track down the pheromone trails previously dropped by the nests ants to accomplish the path between the two points of nest and food respectively. Results from preliminary tests show that the ACRMP is capable of reducing the intermediate configuration between the initial and goal configuration in an acceptable running time

VHDL?AMS modelling and simulation of a planar electrostatic micromotor

System level simulation results of a planar electrostatic micromotor, based on analytical models of the static and dynamic torque behaviours, are presented. A planar variable capacitance (VC) electrostatic micromotor designed, fabricated and tested at LAAS (Toulouse) in 1995 is simulated using the high level language VHDL–AMS (VHSIC (very high speed integrated circuits) hardware description language–analog mixed signal). The analytical torque model is obtained by first calculating the overlaps and capacitances between different electrodes based on a conformal mapping transformation. Capacitance values in the order of 10−16 F and torque values in the order of 10−11 N m have been calculated in agreement with previous measurements and simulations from this type of motor. A dynamic model has been developed for the motor by calculating the inertia coefficient and estimating the friction-coefficient-based values calculated previously for other similar devices. Starting voltage results obtained from experimental measurement are in good agreement with our proposed simulation model. Simulation results of starting voltage values, step response, switching response and continuous operation of the micromotor, based on the dynamic model of the torque, are also presented. Four VHDL–AMS blocks were created, validated and simulated for power supply, excitation control, micromotor torque creation and micromotor dynamics. These blocks can be considered as the initial phase towards the creation of intellectual property (IP) blocks for microsystems in general and electrostatic micromotors in particular.

Global MPPT of solar PV modules using a dynamic PSO algorithm under partial shading conditions

This paper proposes a novel global maximum power point tracking (MPPT) strategy for solar photovoltaic (PV) modules under partial shading conditions using a dynamic particle swarm optimisation (PSO) algorithm. Solar PV modules have non-linear V-P characteristics with local maximum power points (MPPs) under partial shading conditions. In order to continuously harvest maximum power from solar PV modules, it always has to be operated at its global MPP which is determined using the proposed dynamic PSO algorithm. The obtained simulation results are compared with MPPs achieved using the standard PSO, and Perturbation and Observation (P&O) algorithms to confirm the effectiveness of the proposed algorithm under partial shading conditions.

A comparison between robust and adaptive hybrid position/force control schemes for hydraulic underwater manipulators

Tele-operated hydrauilic underwater manipulators are commonly used to perform remote underwater intervention tasks such as weld inspection or mating of connectors Automation of these tasks to use tele-assitance requires a suitable hybrid position/force control scheme, to specify simultaneously the robot motion and contact forces. Classical linear control does not allow for the highly non-linear and time varying robot dynamics in this situation. Adequate control performance requires more advanced controllers. This paper presents and compares two different advanced hybrid control algorithms. The first is based on a modified Variable Structure Control (VSC-HF) with a virtual environment, and the second uses a multivariable self-tuning adaptive controller. A direct comparison of the two proposed control schemes is performed in simulation, using a model of the dynamics of a hydraulic underwater manipulator (a Slingsby TA9) in contact with a surface. These comparisons look at the performance of the controllers under a wide variety of operating conditions, including different environment stiffnesses, positions of the robot and dynamic parameters. Conclusions are drawn based on the relative performance of each controller and on the practicalities of the proposed schemes.

Motion planning and contact control for a tele-assisted hydraulic underwater robot

Implementing tele-assistance or supervisory control for autonomous subsea robots requires atomic actions that can be called from high level task planners or mission managers. This paper reports on the design and implementation of a particular atomic action for the case of a subsea robot carrying out tasks in contact with the surrounding environment.Subsea vehicles equipped with manipulators can have upward of 11 degrees of freedom (DOF), with degenerate and redundant inverse kinematics. Distributed local motion planning is presented as a means to specify the motion of each robot DOF given a goal point or trajectory. Results are presented to show the effectiveness of the distributed versus non-distributed approach, a means to deal with local minima difficulties, and the performance for trajectory following with and without saturated joint angles on a robot arm.Consideration is also given to the modelling of hydraulic underwater robots and to the resulting design of hybrid position/force control strategies. A model for a hydraulically actuated robot is developed, taking into account the electrohydraulic servovalve, the bulk modulus of oil, piston area, friction, hose compliance and other arm parameters. Open and closed-loop control results are reported for simulated and real systems.Finally, the use of distributed motion planning and sequential position/force control of a Slingsby TA-9 hydraulic underwater manipulator is described, to implement an atomic action for tele-assistance. The specific task of automatically positioning and inserting a Tronic subsea mateable connector is illustrated, with results showing the contact conditions during insertion.

Maximum power point tracking of solar photovoltaic panels using advanced perturbation and observation algorithm

An efficient maximum power point tracking (MPPT) scheme is necessary to improve the efficiency of a solar photovoltaic (PV) panel. This paper proposes an advanced perturbation and observation (P&O) algorithm for tracking the maximum power point (MPP) of a solar PV panel. Solar PV cells have a non-linear V-I characteristic with a distinct MPP which depends on environmental factors such as temperature and irradiation. In order to continuously harvest maximum power from the solar PV panel, it always has to be operated at its MPP. The proposed P&O algorithm can reduce the main drawbacks commonly related to the P&O algorithm. This is achieved with determining the short-circuit current before each perturbation and observation stage. The obtained simulation results are compared with MPPs achieved using the conventional P&O algorithm under various atmospheric conditions. The results show that the advanced P&O algorithm is better than the conventional P&O algorithms for tracking MPPs of solar PV panels. Additionally, it is simple and can be easily implemented in digital signal processor (DSP).

Self-tuning position and force control of an underwater hydraulic manipulator

Current generation unmanned underwater vehicles, equipped with robotic manipulators, are teleoperated and consequently place a large workload burden on the human operator. A greater degree of automation could improve the efficiency and accuracy with which underwater tasks are carried out. These tasks can involve manipulator motion that is both unconstrained and/or constrained. For unconstrained motion, where a trajectory requires following, a prerequisite is good joint angle control. An adaptive self-tuning pole-placement controller is used for joint angle control. Practical results show the benefits compared to the conventional fixed-gain control. For constrained motion, simultaneous controls of position and force are often required. An adaptive hybrid position/force controller is proposed and compared to a fixed-gain version. Simulation and practical results illustrate the merits and drawbacks of each scheme.

Position control of a robotic manipulator using a Radial Basis Function Network and a simple vision system

This paper describes a new practical approach for approximating the inverse kinematics of a manipulator using a RBFN (radial basis function network). In fact, there are several traditional methods based on the known geometry of the manipulator to calculate the relationship between the joint variable space and the world coordinate space. However, these traditional methods are impractical if the manipulator geometry cannot be easily determined, in a robot-vision system for example. Therefore, a neural network with its inherent learning ability can be an effective alternative solution for the inverse kinematics problem. In this paper, a training approach using the strict interpolation method combined with the LMS (least mean square) is presented. The strict interpolation method with regularly spaced position training patterns in the workspace can produce an appropriate approximation of the inverse kinematic function. Additionally, the LMS algorithm can improve the approximate function iteratively through on-line training with arbitrary position patterns. The combination of these techniques can deal with variation in the set-up of the visual system used to measure the position of the manipulator in the workspace. To verify the performance of the proposed approach, a practical experiment has been performed using a Mitsubishi PA10-6CE manipulator observed by a webcam. All application programmes, such as robot servo control, neural network, and image processing tool, were written in C/C++ and run in a real robotic system. The experimental results prove that the proposed approach is effective.

An adaptive region boundary-based control scheme for an autonomous underwater vehicle

A new control concept is proposed for an autonomous underwater vehicle (AUV) where the desired target is defined as a boundary rather than a point or a region. The inverse Jacobian is utilized in the adaptive control law for compensation of the persistent effects i.e.: the restoring forces. The unit quaternion representation is used for the AUVs attitude representation. The stability analysis is carried out using a Lyapunov-like function. Simulation results are presented to access the effectiveness of the proposed control scheme.