Optimal control of robots under stochastic uncertainty: robust feedback control

The most important aspect in the optimal control and design of manipulators is the determination of the basic movement, i.e. the calculation of the optimal trajectory on which the robot has to move. Having an optimal reference trajectory and an optimal open-loop control, there is the need of control corrections by applying a certain feedback control. Different attempts exist for this. In this article a method will be shown which is based on classical control theory, that works with cost functions being minimized. The aim is to take into account stochastic parameter variations in order to obtain robust optimal feedback controls. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

IDSSF<Emphasis Type="SmallCaps">LEX</Emphasis>: an intelligent DSS for the design and evaluation of flexible manufacturing systems

This paper describes IDSSFLEX, a computer system for the analysis and evaluation of Flexible Manufacturing System (FMS) design configurations. IDSSFLEX is an intelligent decision support system which selects from among several configurations and control strategy alternatives of design, the most appropriate one for a specific case. In order to accomplish such an objective, the system presents simultaneously the following features: ability to quantify subjective factors, ability to account for individual preferences, and ability to cope with multiple criteria decision making. A case study illustrates the effectiveness of the computer system.     

A Bayesian network structure for operational risk modelling in structured finance operations

This paper is concerned with the design of a Bayesian network structure that is suitable for operational risk modelling. The model's structure is designed specifically from the perspective of a business unit operational risk manager whose role is to measure, record, predict, communicate, analyse and control operational risk within their unit. The problem domain modelled is a functioning structured finance operations unit within a major Australian bank. The network model design incorporates a number of existing human factor frameworks to account for human error and operational risk events within the domain. The design also supports a modular structure, allowing for the inclusion of many operational loss event types, making it adaptable to different operational risk environments.     

医疗保险个人账户机制创新及其可行性研究——基于患者道德风险的分析

我国目前实行“统账结合”的医疗保险模式,其医疗个人账户的设计与统筹账户中设定的起付线、封顶线以及患者自付比例等限制性参数都是为了控制医患双方的“道德风险”及其“串谋”的频率。但本文对患者道德风险产生过程与机理的实地调研表明:在“统账结合”的医疗保险模式下,患者的各种道德风险均是以其个人账户为基础的;我国现行的医疗保险个人账户缴费机制也因此存在进一步改进和创新的空间。本文将根据先验保费原理以及个人账户实行社会医疗保险卡(IC卡)制度,设计出一种新的个人账户缴费机制。这种机制创新无论对于被保险人道德风险的规避,还是缓解个人账户纵向积累的矛盾都将起到重要作用。     

On-line robust nonlinear state estimators for nonlinear bioprocess systems

This paper presents the design of a new robust nonlinear estimator for estimation of states of nonlinear systems. Two approaches are considered based on the state-dependent Riccati equation formulation and the technique of H-infinity control design. The proposed method differs from other well-known state estimators, because not only nonlinear dynamics but also the robustness is taken into account. The proposed method is implemented and tested on a biological wastewater system. The simulation study compares the Extended Kalman Estimator (EKE), the State-Dependent Riccati Estimator (SDRE), and the Extended H-infinity Estimator (EHE) with a new proposed State Dependent H-infinity Estimator (SDHE). The results are compared for different weather conditions, i.e. dry, rain and storm, showing a superior performance of the proposed method.     

Model Based Selection of an Appropriate Control Strategy Application to an Anaerobic Digester

The aim of this work is to develop an integrated control of anaerobic digesters in wastewater treatment plants, to ensure optimal depollution performances. To achieve this goal, we have to summarise our knowledge in a mathematical model, which is an essential tool for control design. Various control strategies can be chosen, but their performances are very different (stabilisation, biogaz production,...). Each of them is evaluated through 3 criteria. Then we present an original linear model for process stability which take into account the input pollution (flow rate, concentration). We show with simulations how this model help us to select the appropriate control strategy and the improvement of depollution efficiency.     

Two-level evolutionary approach to the survivable mesh-based transport network topological design

The complete topology design problem of survivable mesh-based transport networks is to address simultaneously design of network topology, working path routing, and spare capacity allocation based on span-restoration. Each constituent problem in the complete design problem could be formulated as an Integer Programming (IP) and is proved to be NP\mathcal{NP} -hard. Due to a large amount of decision variables and constraints involved in the IP formulation, to solve the problem directly by exact algorithms (e.g. branch-and-bound) would be impractical if not impossible. In this paper, we present a two-level evolutionary approach to address the complete topology design problem. In the low-level, two parameterized greedy heuristics are developed to jointly construct feasible solutions (i.e., closed graph topologies satisfying all the mesh-based network survivable constraints) of the complete problem. Unlike existing “zoom-in”-based heuristics in which subsets of the constraints are considered, the proposed heuristics take all constraints into account. An estimation of distribution algorithm works on the top of the heuristics to tune the control parameters. As a result, optimal solution to the considered problem is more likely to be constructed from the heuristics with the optimal control parameters. The proposed algorithm is evaluated experimentally in comparison with the latest heuristics based on the IP software CPLEX, and the “zoom-in”-based approach on 28 test networks problems. The experimental results demonstrate that the proposed algorithm is more effective in finding high-quality topologies than the IP-based heuristic algorithm in 21 out of 28 test instances with much less computational costs, and performs significantly better than the “zoom-in”-based approach in 19 instances with the same computational costs.     

Novel design of adaptive neural network controller for a class of non-affine nonlinear systems

The tracking control problem is studied for a class of uncertain non-affine systems. Based on the principle of sliding mode control (SMC), using the neural networks (NNs) and the property of the basis function, a novel adaptive design scheme is proposed. A novel Lyapunov function, which depends on both system states and control input variable, is used for the development of the control law and the adaptive law. The approach overcomes the drawback in the literature. In addition, the lumped disturbances are taken in account. By theoretical analysis, it is proved that tracking errors asymptotically converge to zero. Finally, simulation results demonstrate the effectiveness of the proposed approach.     

Reliable controller for nonlinear multiagent system with additive time varying delay and nonlinear actuator faults

In this paper, the problem of nonlinear multiagent system with reliable control is taken into account. The prescribed system consists of additive time-varying delay, actuator faults with both linear and nonlinear functions. The main focus of this paper is to design a reliable control which guarantees the stability and consensus condition of the proposed system. Actuator faults with linear and nonlinear functions are considered in the control input. From the implementation of integral inequality, the linear matrix inequality format is derived by constructing the suitable Lyapunov Krasovskii functional for the specified system. Terminally numerical examples are furnished for the efficiency of the specified method.     

Stochastic shape sensitivity in powder metallurgy processing

Stochastic shape sensitivity in forming process of powder metallurgy materials is analyzed. For this purpose the rigid-poroplastic material model has been assumed. The theoretical formulation for stochastic shape sensitivity is described which presents probabilistic distributions taking into account random initial and boundary conditions. The control volume approach is discussed. Stochastic finite element equations for rigid – poroplastic materials are solved for the first two probabilistic moments. Numerical simulations were performed to illustrate shape sensitivity problems in the process of compression of rigid-poroplastic cylinder. The differences in deterministic and stochastic sensitivities are presented. The results derived can be used for the subsequent quantitative stochastic shape design as well as stochastic shape optimization.     

Decentralized Control of Nonlinear Large-Scale Systems Using Dynamic Output Feedback

In this paper, a class of nonlinear large-scale systems with similar subsystems is studied. Both matched and unmatched uncertainties are considered by utilizing their bounding functions, and the interconnections take a more general form than considered previously. Based on a constrained Lyapunov equation, a nonlinear dynamic output feedback decentralized controller is presented. Unlike existing results, matched uncertainties are considered in the control design; by using a decomposition of the interconnections, the known and uncertain interconnections are treated separately; thus, the robustness is improved and conservativeness is reduced significantly. The computation effort for solving the Lyapunov equation is greatly reduced by taking into account the similar subsystem structure. Finally, simulation is used to illustrate the effectiveness of our results.     

Dual-Sampling-Rate Moving-Horizon Control of a Class of Linear Systems with Input Saturation and Plant Uncertainty

Moving-horizon control is a type of sampled-data feedback control in which the control over each sampling interval is determined by the solution of an open-loop optimal control problem. We develop a dual-sampling-rate moving-horizon control scheme for a class of linear, continuous-time plants with strict input saturation constraints in the presence of plant uncertainty and input disturbances. Our control scheme has two components: a slow-sampling moving-horizon controller for a nominal plant and a fast-sampling state-feedback controller whose function is to force the actual plant to emulate the nominal plant. The design of the moving-horizon controller takes into account the nonnegligible computation time required to compute the optimal control trajectory.We prove the local stability of the resulting feedback system and illustrate its performance with simulations. In these simulations, our dual-sampling-rate controller exhibits performance that is considerably superior to its single-sampling-rate moving-horizon controller counterpart.     

Optimal control of dengue epidemic outbreaks under limited resources

In this paper, we reflect upon control intervention practices habitually exerted by healthcare authorities in tropical areas that suffer from incidental outbreaks of dengue fever, in particular, the city of Cali, Colombia. Such control interventions, principally based on the insecticide spraying, are carried out sporadically in order to overcome an ongoing epidemic or at least to reduce its size. It is worth pointing out that control actions of this type do not usually account for sufficient budget because epidemic outbreaks are difficult to predict. In practical terms, these occasional control interventions are performed by spraying, as quickly as possible, all existing stock of insecticide (regardless of its lethality) and employing all available manpower. The goal of this paper is to design better strategies for insecticide-based control actions, which are capable of preventing more human infections at no additional cost, and to reveal the obsolescence of current vector eradication practices. Our approach relies on dynamic optimization, where the number of averted human infections is maximized under budget constraint and subject to a simple dengue transmission model amended with one control variable that stands for the insecticide spraying. As a result, we obtain structurally robust control intervention policies that demonstrate better performance and higher resilience to possible budget limitations than traditional modus operandi.     

Design of a robust nonlinear controller for a synchronous generator connected to an infinite bus

This article presents a new design of robust finite‐time controller which replaces the traditional automatic voltage regulator for excitation control of the third‐order model synchronous generator connected to an infinite bus. The effects of system uncertainties and external noises are fully taken into account. Then a single input robust controller is proposed to regulate the system states to reach the origin in a given finite time. The designed robust finite‐time excitation controller can refine the system behaviors in convergence and robustness against model uncertainties and external disturbances. The robustness and finite‐time stability of the closed‐loop system are analytically proved using the finite‐time control idea and Lyapunov stability theorem. The suitability and robustness of the designed controller are shown in contrast with two other strong nonlinear control strategies. The main advantages of the proposed controller are as follows: a) robustness against system uncertainties and external noises; b) convergence to the equilibrium point in a given finite time; and c) the use of a single control input. © 2015 Wiley Periodicals, Inc. Complexity 21: 203–213, 2016     

Appearance of horseshoes chaos on a buckled beam controlled by disseminated couple forces

This paper shows the appearance of horseshoes chaos on a buckled beam controlled by concentrated moments applied at suitable points. The distance between the stable and unstable manifolds of the control system are derived and analyzed taking into account the asymmetric characteristics of the potential brought by the control design. The structure of basin boundaries are obtained and confirmed by the analytical investigation.     

Dynamics modeling and experiments of wave driven robot

Wave driven robots (WDRs) take ocean energies as the power sources and are often used for long-term monitoring of the marine environment. The unique multi-body joint structure and special operation mechanism of a WDR make the dynamics modeling problem unusual. The dynamic model of a WDR was put forward by taking the interconnection of forces and motions between the float body (float) and the submerged glider (glider) into account. Numerical simulation of longitudinal motion and the comparison between simulation and tank test of reciprocating steering motion of the "Ocean Rambler" WDR were carried out. The dynamic model proposed in this paper was consistent with the motion characteristics of "Ocean Rambler" WDR. Simulations of PID heading control demonstrated the unique control characteristics of the WDR, which proved the significance of the established dynamic model of the WDR in control algorithm design.     

Passive damping of bridge vibrations by tuned liquid column gas dampers

Sealed tuned liquid column gas dampers, i.e. with a gas spring effect taken into account, TLCGD, are ideally suited to increase the effective structural damping of bridges when vibrating in the critical low frequency band, substituting the classical mechanical damper (TMD). The evident features of TLCGD are no moving mechanical parts, cheap and easy implementation, low maintenance costs and simple modification of the natural frequency (by means of altering the equilibrium gas pressure). Modal tuning in analogy to the classical mechanical damper, TMD, in the design stage is subsequently followed by fine-tuning in state space, rendering the absorber parameter (frequency and damping) optimal and, when designing smaller units in parallel action, yields the control even more robust. The equilibrium gas-pressure is the main control parameter to optimize the absorber frequency when the volume of the individual gas vessel above the liquid-gas interface is properly selected. U- or V-shaped TLCGD with horizontal extension maximized, are proposed to reduce dominating horizontal vibrations of long-span bridges (including pedestrian bridges), and in the case of the cantilever method of bridge construction to allow the increase of the maximum length of the cantilever, despite of wind-gusts. An alternate design, VTLCGD provides the control force vertically, and thus counteracts dominating vertical, traffic-induced vibrations. The horizontal length of the absorber is kept to a minimum. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Mixed-integer models for topology optimization in sheet metal design

Topology optimization lies at the heart of many design tasks in mechanical engineering. For those sheet metal products that consist of a bundle of separate channels (such as conduits) we formulate the design task as a linear mixed-integer optimization problem. The design goal is to find a topology where each channel has a given cross section area, using a minimum amount of sheet met al. In addition to a light-weight design, stiffness should also be taken into account. The entire approach is demonstrated in the design of a conduit with five separate channels. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Finding the optimum domain of a nonlinear wave optimal control system by measures

We will explain a new method for obtaining the nearly optimal domain for optimal shape design problems associated with the solution of a nonlinear wave equation. Taking into account the boundary and terminal conditions of the system, a new approach is applied to determine the optimal domain and its related optimal control function with respect to the integral performance criteria, by use of positive Radon measures. The approach, say shape-measure, consists of two steps; first for a fixed domain, the optimal control will be identified by the use of measures. This function and the optimal value of the objective function depend on the geometrical variables of the domain. In the second step, based on the results of the previous one and by applying some convenient optimization techniques, the optimal domain and its related optimal control function will be identified at the same time. The existence of the optimal solution is considered and a numerical example is also given.     

Sliding mode control of a denitrifying biofilter

Biological denitrification in a fixed-bed reactor is increasingly popular for water treatment. With the advent of more stringent criteria for nitrate and nitrite concentrations in treated water and the need to control and optimize the addition of a carbon source (for denitrification purposes), dynamical models taking into account the process behavior, are of particular interest and become a necessity for control optimization. The control of biotechnological processes is highly complex because the behavior of microorganisms used for various purposes such as microbial growth, metabolite production or consumption of harmful substrates, remains relatively unknown. The aim of this paper is to design a robust control law capable of governing biochemical reactions characterizing the behavior of such reactors, thereby regulating the concentration of residual substrates at the reactor outlet, by acting either on the influent flow rate or on the supplied ethanol concentration.