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.     

Maximizing biogas production from the anaerobic digestion

This paper presents an optimal control law policy for maximizing biogas production of anaerobic digesters. In particular, using a simple model of the anaerobic digestion process, we derive a control law to maximize the biogas production over a period T using the dilution rate as the control variable. Depending on initial conditions and constraints on the actuator (the dilution rate D(·)), the search for a solution to the optimal control problem reveals very different levels of difficulty. In the present paper, we consider that there are no severe constraints on the actuator. In particular, the interval in which the input flow rate lives includes the value which allows the biogas to be maximized at equilibrium. For this case, we solve the optimal control problem using classical tools of differential equations analysis. Numerical simulations illustrate the robustness of the control law with respect to several parameters, notably with respect to initial conditions. We use these results to show that the heuristic control law proposed by Steyer et al., 1999 [20] is optimal in a certain sense. The optimal trajectories are then compared with those given by a purely numerical optimal control solver (i.e. the “BOCOP” toolkit) which is an open-source toolbox for solving optimal control problems. When the exact analytical solution to the optimal control problem cannot be found, we suggest that such numerical tool can be used to intuiter optimal solutions.     

基于子载波选择配对及功率优化分配的多跳中继系统研究

为了提升OFDM协作通信系统的网络覆盖率及网络容量,提出了一种基于子载波选择配对及功率优化分配的多跳中继OFDM系统优化算法。首先,通过在OFDM的系统模型上进行中继配对和非中继配对的性能分析,将子载波选择配对转换为一个整数规划问题,并采用基于匈牙利算法的规划方法进行配对矩阵的计算。接着,根据OFDM系统的功率分配问题,通过KKT条件对中继功率及电源功率进行优化,从而实现中继系统的功率优化分配 。最终的仿真结果表明,与统计质量QoS保证的资源分配方案以及OFDM中继系统异构服务的资源分配算法相比,所提出的方法在提高网络覆盖率和容量上均表现出更好的效果。     

Optimal design of adaptive type-2 neuro-fuzzy systems: A review

Type-2 fuzzy logic systems have extensively been applied to various engineering problems, e.g. identification, prediction, control, pattern recognition, etc. in the past two decades, and the results were promising especially in the presence of significant uncertainties in the system. In the design of type-2 fuzzy logic systems, the early applications were realized in a way that both the antecedent and consequent parameters were chosen by the designer with perhaps some inputs from some experts. Since 2000s, a huge number of papers have been published which are based on the adaptation of the parameters of type-2 fuzzy logic systems using the training data either online or offline. Consequently, the major challenge was to design these systems in an optimal way in terms of their optimal structure and their corresponding optimal parameter update rules. In this review, the state of the art of the three major classes of optimization methods are investigated: derivative-based (computational approaches), derivative-free (heuristic methods) and hybrid methods which are the fusion of both the derivative-free and derivative-based methods.     

污水处理厂污泥厌氧消化优化设计与运行探讨

对国内典型的污水处理厂污泥厌氧消化系统进行调研发现,厌氧消化系统的运行管理尚存在诸多问题。在总结白龙港污水处理厂污泥厌氧消化调试与运行管理经验的基础上,针对厌氧消化工艺存在的普遍性问题,提出了厌氧消化系统设计和运行管理方面的建议,以促进工艺设计优化,提高运行管理水平。     

Optimal Control of Switching Times in Switched Stochastic Systems

In this paper, we solve an optimal control problem for switched stochastic systems using calculus of variations, where the objective is to minimize a cost functional defined on the state and the switching times are the sole control variables. In particular, we focus on the problem in which a pre‐specified sequence of active subsystems is given. For one switching time case, the derivative of the cost functional with respect to the switching time is derived, which has an especially simple form and can be directly used in gradient descent algorithms to locate the optimal switching instant. Then, we propose an approach to deal with the problem with multi‐switching times case. Finally, two numerical examples are given, highlighting the viability and advantages of the proposed methodology.     

EOQ Model: The Case in Which the Placing of Orders Is Rewarded

The first models of optimization of inventory management costs have undergone few changes since they were developed at the beginning of the last century. It is only with the passage of time that new scenarios have appeared with the introduction of new systems of production, and consequently of new strategies in the logistics chain. In this article, we analyze and propose a revision of the basic inventory model of economic order quantity first defined by Harris in 1913 for a scenario in which the owner of the stock receives a bonus or reward each time he replenishes his stock. This situation arises when the supplier receives a benefit (which he then shares with the customer) when managing his stock replenishment. An array of nested models is shown to illustrate this scenario, from which the constraints of previous scenarios have been removed. The model provides insights into the negotiation of batch size between supplier and buyer in a win‐win environment in the specific situation in which the supplier gives a bonus to the buyer at each stock replenishment. © 2011 Wiley Periodicals, Inc.     

Optimal blank design based on finite element method for blades of large Francis turbines

Metal pressing process that is widely used in industries has advantages over casting process for producing large Francis turbine blades from thick plates. Prior to the pressing process, blank design is firstly performed to determine flat blanks. The traditional trial and error approach is not applicable to blade design for Francis turbines that are not standard due to hydraulic characteristics of power plant sites. The rapid development of computing technology makes it possible to obtain optimal flat blanks by numerical modelling and simulation. In this paper, inverse finite element approach is investigated for blank design and an elasto-plastic model has been built using the well-known commercial software ANSYS. Numerical simulations for blade unfolding models with thick shell elements, solid elements and shell elements have given results with negligible differences. Unfolding tests with simple geometries have been carried out and the numerical results agree well with the analytical solutions. A large and thick shape of a Francis turbine blade for a hydropower plant has been successfully unfolded by inverse FE model. Sensibility analysis shows that the middle surface of the flat blank is independent of blade thickness. For ensuring the machining of the blade after the pressing process, a new contour is obtained by extending the boundary of the flat blank provided by the numerical model. This research may provide a useful tool for optimal blank design of Francis turbine blades.     

红外制导导弹最优导引律工程实现方法研究

为了研究提高导引精度,用最优控制理论推导出的最优比例导引律,给出了一种只需目标视线角速率信息的最优比例导引律工程实现方法,方法不需要最优比例导引律中的相对速度、目标加速度和剩余时间等信息,与基于小离轴角的假设推导得出的经典的比例导引律相比,可满足近距格斗导弹大离轴发射和攻击高机动目标的要求。经仿真结果证明,最优比例导引律的工程实现方法尤其适合不带测距功能的红外制导导弹,与需要剩余时间估计算法的方法相比具有更强的工程可实现性。     

Adaptive signal processing of asset price dynamics with predictability analysis

In this paper we illustrate the optimal filtering of log returns of commodity prices in which both the mean and volatility are modulated by a hidden Markov chain with finite state space. The optimal estimate of the Markov chain and the parameters of the price model are given in terms of discrete-time recursive filters. We provide an application on a set of high frequency gold price data for the period 1973-2006 and analyse the h-step ahead price predictions against the Diebold-Kilian metric. Within the modelling framework where the mean and volatility are switching regimes, our findings suggest that a two-state hidden Markov model is sufficient to describe the dynamics of the data and the gold price is predictable up to a certain extent in the short term but almost impossible to predict in the long term. The proposed model is also benchmarked with ARCH and GARCH models with respect to price predictability and forecasting errors.