Flight control of tethered kites in autonomous pumping cycles for airborne wind energy

Energy harvesting based on tethered kites benefits from exploiting higher wind speeds at higher altitudes. The setup considered in this paper is based on a pumping cycle. It generates energy by winching out at high tether forces, driving an electrical generator while flying crosswind. Then it winches in at a stationary neutral position, thus leaving a net amount of generated energy.The focus of this paper is put on the flight control design, which implements an accurate direction control towards target points and allows for a flight with an eight-down pattern. An extended overview on the control system approach, as well as details of each element of the flight controller, is presented. The control architecture is motivated by a simple, yet comprehensive model for the kite dynamics.In addition, winch strategies based on an optimization scheme are presented. In order to demonstrate the real world functionality of the presented algorithms, flight data from a fully automated pumping-cycle operation of a small-scale prototype are given. The setup is based on a 30 m² kite linked to a ground-based 50 kW electrical motor/generator by a single line.     

Non-diagonal H∞ weighting function design: Exploiting spatio-temporal deformations in precision motion control

Model-based control design requires a careful specification of performance and robustness requirements. In typical norm-based control designs, performance and robustness requirements are specified in a scalar optimization criterion, even for complex multivariable systems. This paper aims to develop a novel approach for the formulation of this optimization criterion for multivariable motion systems that exhibit spatio-temporal deformations. To achieve this, characteristics of the underlying system are exploited to design multivariable weighting functions. In contrast to pre-existing approaches, which typically lead to diagonal weighting functions, the proposed approach enables the design of non-diagonal weighting functions. Extensive experimental results confirm that the proposed procedure can significantly improve the performance of an industrial motion system compared to earlier approaches.     

Mooring system diagnosis and structural reliability control for position moored vessels

Early diagnosis and fault-tolerant control are essential for safe operation of floating platforms where mooring systems maintain vessel position and must withstand environmental loads. This paper considers two critical faults, line breakage and loss of a buoyancy element and employs vector statistical change detection for timely diagnosis of faults. Diagnosis design is scrutinised and a procedure is proposed based on specified false alarm probability and estimation of the distribution of the test statistics on which change detection is based. A structural reliability index is applied for monitoring the safety level of each mooring line and a set-point chasing algorithm accommodates the effects of line failure, as an integral part of the reliability-based set-point chasing control algorithm. The feasibility of the diagnosis and of the fault-tolerant control strategy is verified in model basin tests.     

Experimental investigation of stochastic parafoil guidance using a graphics processing unit

Control of autonomous systems subject to stochastic uncertainty is a challenging task. In guided airdrop applications, random wind disturbances play a crucial role in determining landing accuracy and terrain avoidance. This paper describes a stochastic parafoil guidance system which couples uncertainty propagation with optimal control to protect against wind and parameter uncertainty in the presence of impact area obstacles. The algorithm uses real-time Monte Carlo simulation performed on a graphics processing unit (GPU) to evaluate robustness of candidate trajectories in terms of delivery accuracy, obstacle avoidance, and other considerations. Building upon prior theoretical developments, this paper explores performance of the stochastic guidance law compared to standard deterministic guidance schemes, particularly with respect to obstacle avoidance. Flight test results are presented comparing the proposed stochastic guidance algorithm with a standard deterministic one. Through a comprehensive set of simulation results, key implementation aspects of the stochastic algorithm are explored including tradeoffs between the number of candidate trajectories considered, algorithm runtime, and overall guidance performance. Overall, simulation and flight test results demonstrate that the stochastic guidance scheme provides a more robust approach to obstacle avoidance while largely maintaining delivery accuracy.     

Real-time nonlinear MPC and MHE for a large-scale mechatronic application

Progress in optimization algorithms and in computational hardware made deployment of Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) possible to mechatronic applications. This paper aims to assess the computational performance of NMPC and MHE for rotational start-up of Airborne Wind Energy systems. The capabilities offered by an automatic code generation tool are experimentally verified on a real physical system, using a model comprising 27 states and 4 inputs at a sampling frequency of 25 Hz. The results show the feedback times less than 5 ms for the NMPC with more than 1500 variables.     

Economic selection of process mean and lot‐sizing decisions for multi‐newsvendor supply chain

Two related problems are integrated in this paper, the first is the targeting problem and another is production/inventory decisions in a supply chain. The supply chain under consideration consists of a supplier of raw material, a single producer, and multiple newsvendors. The producer can adjust the process mean before starting the production run. Once set to a certain target value, the process mean is not changed until the production lot is completed. At the end of a production run, the producer screens the lot and uses specification limits to evaluate the quality of the item. Nonconforming items are scrapped with no salvage value; however, conforming items are delivered to newsvendors who are subjected to random demand. If demand on a newsvendor in a season is lower than anticipated, surplus items will be returned to the producer at a certain transportation cost. We first develop a mathematical model that maximizes the expected total profit of the supply chain. Then, a table for two special functions is devised to simplify the solution method and is used to find the optimal solution of the proposed model. We also study the significance of this integration by comparing the performance of the proposed model with an independent model where the process mean selection and lot‐sizing decisions are found separately.     

Simultaneous optimization of photostrictive actuator locations,numbers and light intensities for structural shape control using hierarchical genetic algorithm

The present paper introduces an investigation into simultaneous optimization of the PbLaZrTi-based actuator configuration and corresponding applied light intensity for morphing beam structural shapes. A finite element formulation for multiphysics analysis of coupled opto-electro-thermo-mechanical fields in PbLaZrTi ceramics is derived and verified with the theoretical solution and the commercial software ANSYS. This element is then used to simulate beam bending shape control using the orthotropic PbLaZrTi actuators and the simultaneous optimization. In this procedure, the controlling and geometrical variables are simultaneously optimized via a hierarchical genetic algorithm. A bi-coded chromosome is proposed in a hierarchical mode, which consists of some control genes (i.e. actuator location and number) and parametric genes (i.e. applied light intensity). Whether the parametric gene is activated or not is managed by the value of the first-grade control genes. The numerical results demonstrate that the achieved beam bending shapes correlate remarkably well with the expected ones and the simultaneous optimization of photostrictive actuator locations, numbers and light intensities can result in optimal actuator layout with less PbLaZrTi actuators and irradiated light energy. The simulation results also show that the hierarchical genetic algorithm has more superior performance over the conventional real-coded genetic algorithm.     

Smith模糊PID匀速升温控制策略研究

针对电加热炉匀速升温过程模型建立困难、调节过程滞后等问题,提出了一种基于炉体散热补偿的Smith模糊PID控制算法。通过炉体散热补偿建立针对被控量升温速率的一阶线性纯滞后模型;采用Smith预估器消除纯滞后特性带来的影响,提高系统的稳定性,加快调节过程;引入模糊PID控制,克服Smith预估补偿环节鲁棒性差的弱点,实现参数的自适应调整,并提高了稳态精度,实现了高精度的匀速升温控制。试验结果表明,该控制策略的控制偏差低于5%,明显优于常规PID控制。