CAD enabled trajectory optimization and accurate motion control for repetitive tasks

As machine users generally only define the start and end point of the movement, a large trajectory optimization potential rises for single axis mechanisms performing repetitive tasks. However, a descriptive mathematical model of the mecha- nism needs to be defined in order to apply existing optimization techniques. This is usually done with complex methods like virtual work or Lagrange equations. In this paper, a generic technique is presented to optimize the design of point-to-point trajectories by extracting position dependent properties with CAD motion simulations. The optimization problem is solved by a genetic algorithm. Nevertheless, the potential savings will only be achieved if the machine is capable of accurately following the optimized trajectory. Therefore, a feedforward motion controller is derived from the generic model allowing to use the controller for various settings and position profiles. Moreover, the theoretical savings are compared with experimental data from a physical set-up. The results quantitatively show that the savings potential is effectively achieved thanks to advanced torque feedforward with a reduction of the maximum torque by 12.6% compared with a standard 1/3-profil

Human Like Adaptation of Force and Impedance in Stable and Unstable Tasks

Abstract—This paper presents a novel human-like learning con-troller to interact with unknown environments. Strictly derived from the minimization of instability, motion error, and effort, the controller compensates for the disturbance in the environment in interaction tasks by adapting feedforward force and impedance. In contrast with conventional learning controllers, the new controller can deal with unstable situations that are typical of tool use and gradually acquire a desired stability margin. Simulations show that this controller is a good model of human motor adaptation. Robotic implementations further demonstrate its capabilities to optimally adapt interaction with dynamic environments and humans in joint torque controlled robots and variable impedance actuators, with-out requiring interaction force sensing. Index Terms—Feedforward force, human motor control, impedance, robotic control. I

To develop an efficient variable speed compressor motor system

This research presents a proposed new method of improving the energy efficiency of a Variable Speed Drive (VSD) for induction motors. The principles of VSD are reviewed with emphasis on the efficiency and power losses associated with the operation of the variable speed compressor motor drive, particularly at low speed operation.The efficiency of induction motor when operated at rated speed and load torque is high. However at low load operation, application of the induction motor at rated flux will cause the iron losses to increase excessively, hence its efficiency will reduce dramatically. To improve this efficiency, it is essential to obtain the flux level that minimizes the total motor losses. This technique is known as an efficiency or energy optimization control method. In practice, typical of the compressor load does not require high dynamic response, therefore improvement of the efficiency optimization control that is proposed in this research is based on scalar control model.In this research, development of a new neural network controller for efficiency optimization control is proposed. The controller is designed to generate both voltage and frequency reference signals imultaneously. To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. The simulation of the proposed controller for variable speed compressor is presented. The results obtained clearly show that the efficiency at low speed is significant increased. Besides that the speed of the motor can be maintained. Furthermore, the controller is also robust to the motor parameters variation. The simulation results are also verified by experiment

Nonlinear Dual-Mode Control of Variable-Speed Wind Turbines with Doubly Fed Induction Generators

This paper presents a feedback/feedforward nonlinear controller for variable-speed wind turbines with doubly fed induction generators. By appropriately adjusting the rotor voltages and the blade pitch angle, the controller simultaneously enables: (a) control of the active power in both the maximum power tracking and power regulation modes, (b) seamless switching between the two modes, and (c) control of the reactive power so that a desirable power factor is maintained. Unlike many existing designs, the controller is developed based on original, nonlinear, electromechanically-coupled models of wind turbines, without attempting approximate linearization. Its development consists of three steps: (i) employ feedback linearization to exactly cancel some of the nonlinearities and perform arbitrary pole placement, (ii) design a speed controller that makes the rotor angular velocity track a desired reference whenever possible, and (iii) introduce a Lyapunov-like function and present a gradient-based approach for minimizing this function. The effectiveness of the controller is demonstrated through simulation of a wind turbine operating under several scenarios.Comment: 14 pages, 9 figures, accepted for publication in IEEE Transactions on Control Systems Technolog

Amplitude and frequency control of a vibratory pile driver

Abstract—This paper describes the digital control of a vibratory pile driver in which the vibration is generated via two tandem pairs of electrically driven, geared, contra-rotating eccentrics. Experimental results are included to show the controller-induced system dynamics for a variety of load condtions, and to highlight the fact that, if the relative phase of the eccentric pairs is not controlled, the natural tendency at high excitation frequency is for the pile driver to operate with a low vibration amplitude. An analytical technique for identifying the system parameters is presented, and analytical performance predictions are compared with experimental results. Analysis of the power flow in the system shows that, although significant power transfer occurs between the two electrical drives, the net power dissipation during pile driving is relatively low

Stability Analysis and Robust Controller Design of Indirect Vector Controlled Induction Motor

The thesis considers stability analysis and controller design through different performance measures for indirect vector controlled induction motor (IVCIM).These problems are known to be complex due to nonlinearity, large order and multi-loop scenario. Some new approaches and results on IVCIM are proposed in this work. IVCIM dynamics is well known for having different bifurcation behavior, viz., saddle-node, Hopf, Bogdanov–Takens and Zero–Hopf bifurcations due to rotor resistance variation. These bifurcations affect the control performance and may lead to stalling or permanent damage of motor. A numerical analysis of these bifurcations for proportional integral (PI) controlled IVCIM is made in this thesis using full-order induction motor model (stator dynamics is included). This analysis aids to determine the allowable bifurcation parameter variation range as well as suitable choice of speed-loop gains to avoid these. Some new observations on the bifurcation behavior are made. Simulation and experimental results are presented validating the bifurcation behaviors. For improving dynamic performance in the presence of load torque and rotor resistance variation, a new method for designing PI gains is proposed for IVCIM. The inner-loop current PI controllers are tuned simultaneously along with the speed controller. This method is implemented using a static output feedback scheme in which iterative linear matrix inequality (ILMI) based∞control technique is employed. Such a design makes stator currents and speed response to be robust against rotor resistance and load variations. A comparison between proposed design and a conventional one is shown using simulation and experimental results that validate the superiority of the proposed approach. Owing to multi-loop and nonlinear system behavior, IVCIM dynamics is known to have coupling in between the two inner-loop stator current components (flux and torque). Such coupling affects the dynamic torque output of the motor. Decoupling of the stator currents are important for smoother torque response of IVCIM. Conventionally, additional feedforward decoupler is used to take care of the coupling that requires exact knowledge of the motor parameters and additional circuitry or signal processing. A method is proposed to design the regulating PI gains while minimizing coupling without any requirement of additional decoupler. The variation of the coupling terms for change in load torque is considered as the performance measure. The same ILMI based∞control design approach is used to obtain the controller gains. A comparison between the conventional feedforward decoupling and proposed decoupling scheme is presented through simulation and experimental results that establish the effectiveness of the proposed method riding over its simplicity. Finally, since the PI controller can yield limited performance, a dynamic controller is designed for the IVCIM drive system. In the design process, iron-loss dynamics are incorporated into induction motor model to fetch benefit through better performance. A sequential design method is used for the controller design in which, first, the inner-loop controllers are designed. The designed inner-loop controllers is then used for designing the outer speed-loop controller. The proposed design employs ILMI based∞control design for dynamic output feedback controller that makes stator currents and speed response to be robust against disturbances. A comparison among proposed dynamic controller design, PI controller and compensator design is shown using simulation and experimental results demonstrate enhanced performance of the proposed controller and suitability for industrial purpose