A Comfort Oriented Control Strategy for Semi-Active Suspensions Based on Half Car Model

This paper is devoted to the design of a novel semi-active comfort-oriented control strategy based on the “half-car” modeling of the vehicle. The half car model is an effective description of the vertical behaviors in a vehicle like a motorcycle, since it is able to represent both the heave and pitch dynamics. A recent control strategy (the “Mix-1-Sensor”) have been proven to be the quasi-optimal control strategy when the system is described with a quarter car model and the comfort objective is the control goal. This paper presents an analysis of the performances of the Mix-1-Sensor implemented in a half car: this strategy is able to guarantee a quasi optimal performance in terms of heave dynamics but it is not able to manage the pitch dynamics efficiently. A pitch-oriented extension of this strategy is proposed in order to guarantee a better filtering of the pitch dynamics.

Controllability and Observability of a Large Scale Thermodynamical System via Connectability Approach

This study presents a new approach to determine the controllability and observability of a large scale nonlinear dynamic thermal system using graph-theory. The novelty of this method is in adapting graph theory for nonlinear class and establishing a graphic condition that describes the necessary and sufficient terms for a nonlinear class system to be controllable and observable, which equivalents to the analytical method of Lie algebra rank condition. The directed graph (digraph) is utilized to model the system, and the rule of its adaptation in nonlinear class is defined. Subsequently, necessary and sufficient terms to achieve controllability and observability condition are investigated through the structural property of a digraph called connectability. It will be shown that the connectability condition between input and states, as well as output and states of a nonlinear system are equivalent to Lie-algebra rank condition (LARC). This approach has been proven to be easier from a computational point of view and is thus found to be useful when dealing with a large system.

Model Identification and Operating Load Characterization for a Small Horizontal Axis Wind Turbine Rotor Using Integrated Blade Sensors

One of the primary challenges in diagnostic health monitoring and control of wind turbines is compensating for the variable nature of wind loads. Given the sometimes large variations in wind speed, direction, and other operational variables (like wind shear), this paper proposes a data-driven, online rotor model identification approach. A 2 m diameter horizontal axis wind turbine rotor is first tested using experimental modal analysis techniques. Through the use of the Complex Mode Indication Function, the dominant natural frequencies and mode shapes of dynamic response of the rotor are estimated (including repeated and pseudo-repeated roots). The free dynamic response properties of the stationary rotor are compared to the forced response of the operational rotor while it is being subjected to wind and rotordynamic loads. It is demonstrated that both narrowband (rotordynamic) and broadband (wind driven) responses are amplified near resonant frequencies of the rotor. Blade loads in the flap direction of the rotor are also estimated through matrix inversion for a simulated set of rotor blade input forces and for the operational loading state of the wind turbine in a steady state condition. The analytical estimates are shown to be accurate at frequencies for which the ordinary coherence functions are near unity. The loads in operation are shown to be largest at points mid-way along the span of the blade and on one of the three blades suggesting this method could be used for usage monitoring. Based on these results, it is proposed that a measurement of upstream wind velocity will provide enhanced models for diagnostics and control by providing a leading indicator of disturbances in the loads.

Dynamic Modeling of Mechanical Draft Counter-Flow Wet Cooling Tower With Modelica

Cooling towers are important equipments for the heating, ventilation and air conditioning systems in commercial buildings, rejecting the process heat generation to the atmosphere. Dynamic modeling of cooling tower is beneficial for control design and fault detection and diagnostics of the chilled-water systems. This paper proposes a simple and yet effective dynamic model for a typical mechanical draft counter-flow cooling tower. The finite volume method is applied to the one-dimensional heat and mass transfer analysis. With control volumes defined separately for the water and air sides, the dynamic equations are constructed with the mass and energy balances. The steady-state performance of the proposed model is evaluated with the experimental data from literature. The transient behavior is simulated under the changes of tower inlet conditions, with the performance to be evaluated in the future with field test data.

A Simple Design Approach for Excitation Controller and Power System Stabilizer

This paper proposes a simple design procedure to solve the problem of controlling generator transient stability following large disturbances in power systems. A state-feedback excitation controller and power system stabilizer are designed to guarantee robustness against uncertainty in the system parameters. These controllers ensure satisfactory swing damping and quick decay of the voltage regulation error over a wide range of operating conditions. The controller performance is evaluated in a case study in which a three-phase short-circuit fault near the generator terminals in a four-bus power system is simulated.

Predictive Energy Management for Parallel Hydraulic Hybrid Passenger Vehicle

In this paper, a model predictive control (MPC) approach is presented for solving the energy management problem in a parallel hydraulic hybrid vehicle. The hydraulic hybrid vehicle uses variable displacement pump/motors to transfer energy between the mechanical and hydraulic domains and a high pressure accumulator for energy storage. A model of the parallel hydraulic hybrid powertrain is presented which utilizes the Simscape/Simhydraulics toolboxes of Matlab. These toolboxes allow for a concise description of the relevant powertrain dynamics. The proposed MPC regulates the engine torque and pump/motor displacement in order to track a desired velocity profile while maintaining desired engine conditions. In addition, logic is applied to the MPC to prevent high frequency cycling of the engine. Simulation results demonstrate the capability of the proposed control strategy to track both a desired engine torque and vehicle velocity.

Development of Control System by Nonlinear Compensation Using Digital Acceleration Control

Proportional-Integral-Derivative (PID) control has been most commonly used to operate mechanical systems. In PID control, however, there are limits to the accuracy of the resulting movement because of the influence of gravity, friction, and interaction of joints. We have proposed a digital acceleration control (DAC) that is robust over these modeling errors. One of the most practicable advantages of DAC is robustness against modeling errors. However, it does not always work effectively. If there are modeling errors in the inertia term of the model, the DAC controller cannot control a mechanical system properly. Generally an inertia term is easily modeled in advance, but it has a possibility to change. Therefore, we propose an online estimation method of an inertia term by using a system identification method. By using the proposed method, the robustness of DAC is considerably improved. This paper shows the simulation results of the proposed method using 2-link manipulator.

Vehicle Sideslip Angle Estimation Using Two Single-Antenna GPS Receivers

Knowing vehicle sideslip angle accurately is critical for active safety systems such as Electronic Stability Control (ESC). Vehicle sideslip angle can be measured through optical speed sensors, or dual-antenna GPS. These measurement systems are costly (∼$5k to $100k), which prohibits wide adoption of such systems. This paper demonstrates that the vehicle sideslip angle can be estimated in real-time by using two low-cost single-antenna GPS receivers. Fast sampled signals from an Inertial Measurement Unit (IMU) compensate for the slow update rate of the GPS receivers through an Extended Kalman Filter (EKF). Bias errors of the IMU measurements are estimated through an EKF to improve the sideslip estimation accuracy. A key challenge of the proposed method lies in the synchronization of the two GPS receivers, which is achieved through an extrapolated update method. Analysis reveals that the estimation accuracy of the proposed method relies mainly on vehicle yaw rate and longitudinal velocity. Experimental results confirm the feasibility of the proposed method.

Linear Stability Control of Offshore Wind Turbines

Offshore wind farms in deep water are becoming an attractive prospect for harnessing renewable energy and reducing dependence on fossil fuels. One area of major concern with offshore wind turbines is stability control. The same strong winds that give deep water turbines great potential for energy capture also pose a threat to stability, along with potentially strong wave forces. We examine development of state space controllers for active stabilization of a spar-buoy floating turbine. We investigate linear state feedback with a state observer and evaluate response time and disturbance rejection of decoupled SISO controllers.

Process Dynamics and Control Analysis for Electrospinning Nanofibers

In many emerging, high value electrospinning applications, the diameter distribution of electrospun fibers has important implications for the product’s performance and process reproducibility. However, the current state-of-the-art electrospinning process results in diameter distribution variations, both during a run and run-to-run. To address these problems, a vision-based, open loop system has been developed to better understand the process dynamics. The effects of process parameters on fiber diameter distributions are investigated, process dynamics are identified, and the relation between measurable variables and the resulting fiber diameter distribution is analyzed.