CPG Control for Biped Hopping Robot in Unpredictable Environment

A CPG control mechanism is proposed for hopping motion control of biped robot in unpredictable environment.Based on analysis of robot motion and biological observation of animal's control mechanism,the motion control task is divided into two simple parts:motion sequence control and output force control.Inspired by a two-level CPG model,a two-level CPG control mechanism is constructed to coordinate the drivers of robot joint,while various feedback information are introduced into the control mechanism.Interneurons within the control mechanism are modeled to generate motion rhythm and pattern promptly for motion sequence control; motoneurons are modeled to control output forces of joint drivers in real time according to feedbacks.The control system can perceive changes caused by unknown perturbations and environment changes according to feedback information,and adapt to unpredictable environment by adjusting outputs of neurons.The control mechanism is applied to a biped hopping robot in unpredictable environment on simulation platform,and stable adaptive motions are obtained.     

Yeast glycolytic oscillations that are not controlled by a single oscillophore: a new definition of oscillophore strength

Biochemical oscillations, such as glycolytic oscillations, are often believed to be caused by a single so-called ‘oscillophore’. The main characteristics of yeast glycolytic oscillations, such as frequency and amplitude, are however controlled by several enzymes. In this paper, we develop a method to quantify to which extent any enzyme determines the occurrence of oscillations. Principles extrapolated from metabolic control analysis are applied to calculate the control exerted by individual enzymes on the real and imaginary parts of the eigenvalues of the Jacobian matrix. We propose that the control exerted by an enzyme on the real part of the smallest eigenvalue, in terms of absolute value, quantifies to which extent that enzyme contributes to the emergence of instability. Likewise the control exerted by an enzyme on the imaginary part of complex eigenvalues may serve to quantify the extent to which that enzyme contributes to the tendency of the system to oscillate. The method was applied both to a core model and to a realistic model of yeast glycolytic oscillations. Both the control over stability and the control over oscillatory tendency were distributed among several enzymes, of which glucose transport, pyruvate decarboxylase and ATP utilization were the most important. The distributions of control were different for stability and oscillatory tendency, showing that control of instability does not imply control of oscillatory tendency nor vice versa. The control coefficients summed up to 1, suggesting the existence of a new summation theorem. These results constitute proof that glycolytic oscillations in yeast are not caused by a single oscillophore and provide a new, subtle, definition for the oscillophore strength of an enzyme.     

A knowledge-based system for the strategic control level of robots in flexible manufacturing cells

The strategic control level synthesis for robots is related to a hierarchical robot control problem. The main control problem at the strategic control level is to select the model and algorithm to be used by the lower control level to execute the given robot task. Usually there are several lower control level models and algorithms that can be used by the robot control system for every robot task. Strategic control level synthesis depends on the particular robot system application. In a typical application, when the robot system is used in a flexible manufacturing system for manipulating various part types, the robot tasks executed by the robot system depend on the manufacturing processes in the system. If the robot system is applied in another flexible manufacturing system, dedicated to other manufacturing processes, another set of robot tasks might be needed to perform the necessary operations. Therefore, the quantity and the kind of knowledge required in the system for the strategic control level differ from one application to another. Such a fact creates the appropriate conditions for employing some artificial intelligence techniques. This article describes a knowledge-based system approach to the strategic control level synthesis problem.     

Feedforward-feedback control of dissolved oxygen concentration in a predenitrification system

As the largest single energy-consuming component in most biological wastewater treatment systems, aeration control is of great interest from the point of view of saving energy and improving wastewater treatment plant efficiency. In this paper, three different strategies, including conventional constant dissolved oxygen (DO) set-point control, cascade DO set-point control, and feedforward-feedback DO set-point control were evaluated using the denitrification layout of the IWA simulation benchmark. Simulation studies showed that the feedforward-feedback DO set-point control strategy was better than the other control strategies at meeting the effluent standards and reducing operational costs. The control strategy works primarily by feedforward control based on an ammonium sensor located at the head of the aerobic process. It has an important advantage over effluent measurements in that there is no (or only a very short) time delay for information; feedforward control was combined with slow feedback control to compensate for model approximations. The feedforward-feedback DO control was implemented in a lab-scale wastewater treatment plant for a period of 60 days. Compared to operation with constant DO concentration, the required airflow could be reduced by up to 8–15% by employing the feedforward-feedback DO-control strategy, and the effluent ammonia concentration could be reduced by up to 15–25%. This control strategy can be expected to be accepted by the operating personnel in wastewater treatment plants.     

Optimal risk management of human alveolar echinococcosis with vermifuge

In this study, we develop a bioeconomic model of human alveolar echinococcosis (HAE) and formulate the optimal strategies for managing the infection risks in humans by applying optimal control theory. The model has the following novel features: (i) the complex transmission cycle of HAE has been tractably incorporated into the framework of optimal control problems and (ii) the volume of vermifuge spreading to manage the risk is considered a control variable. With this model, we first obtain the stability conditions for the transmission dynamics under the condition of constant control. Second, we explicitly introduce a control variable of vermifuge spreading into the analysis by considering the associated control costs. In this optimal control problem, we have successfully derived a set of conditions for a bang-bang control and singular control, which are mainly characterized by the prevalence of infection in voles and foxes and the remaining time of control. The analytical results are demonstrated by numerical analysis and we discuss the effects of the parameter values on the optimal strategy and the transmission cycle. We find that when the prevalence of infection in foxes is low and the prevalence of infection in voles is sufficiently high, the optimal strategy is to expend no effort in vermifuge spreading.     

芽孢杆菌与杀菌剂复配防治植物病害的研究进展

芽孢杆菌属包含多种植物病原物的拮抗菌,可广泛用于植物病害防治.然而单独利用生防菌进行生物防治常由于环境因素影响而无法达到较好的防治效果,可通过与低剂量杀菌剂复配使用来提高防治效率.本文对生防芽孢杆菌与杀菌剂复配使用进行植物病害综合防治的研究现状、防效、研究方法等进行综述,芽孢杆菌与杀菌剂复配使用不仅保障了防治效果,还大...     

A parameter optimization approach for the optimal control of large-scale musculoskeletal systems.

This paper describes a computational method for solving optimal control problems involving large-scale, nonlinear, dynamical systems. Central to the approach is the idea that any optimal control problem can be converted into a standard nonlinear programming problem by parameterizing each control history using a set of nodal points, which then become the variables in the resulting parameter optimization problem. A key feature of the method is that it dispenses with the need to solve the two-point, boundary-value problem derived from the necessary conditions of optimal control theory. Gradient-based methods for solving such problems do not always converge due to computational errors introduced by the highly nonlinear characteristics of the costate variables. Instead, by converting the optimal control problem into a parameter optimization problem, any number of well-developed and proven nonlinear programming algorithms can be used to compute the near-optimal control trajectories. The utility of the parameter optimization approach for solving general optimal control problems for human movement is demonstrated by applying it to a detailed optimal control model for maximum-height human jumping. The validity of the near-optimal control solution is established by comparing it to a solution of the two-point, boundary-value problem derived on the basis of a bang-bang optimal control algorithm. Quantitative comparisons between model and experiment further show that the parameter optimization solution reproduces the major features of a maximum-height, countermovement jump (i.e., trajectories of body-segmental displacements, vertical and fore-aft ground reaction forces, displacement, velocity, and acceleration of the whole-body center of mass, pattern of lower-extremity muscular activity, jump height, and total ground contact time).     

Comparing apples and oranges--model-based assessment of different tsetse-transmitted trypanosomosis control strategies

The current control strategies for tsetse-transmitted trypanosomosis in cattle (trypanocidal drugs, tsetse control and trypanotolerant cattle) are briefly reviewed and their adoption rates in different geographic regions of sub-Saharan Africa are presented. The impact of these control strategies and the potential use of vaccines, should they be developed, on trypanosomosis transmission were compared using a mathematical model. The relative trypanosomosis prevalence compared with no control was estimated across a range of control coverages (from none to complete control coverage) by varying the change in specific model parameters influenced by individual control measures. Based on this comparison, the relative rankings of the effect of control strategies on reducing disease prevalence were: vector control, vaccination, and drug use, in that order. In this model, trypanotolerance was assumed to decrease disease prevalence, but not to influence transmission. Differences in the predicted impact of control measures on the transmission of human sleeping sickness are discussed. Finally, the role of transmission model outputs as inputs for economic models to guide investment decisions for trypanosomosis control is emphasised.     

The numerical method for the optimal supporting position and related optimal control for the catalytic reaction system

This paper considers the numerical approximation for the optimal supporting position and related optimal control of a catalytic reaction system with some control and state constraints, which is governed by a nonlinear partial differential equations with given initial and boundary conditions. By the Galerkin finite element method, the original problem is projected into a semi-discrete optimal control problem governed by a system of ordinary differential equations. Then the control parameterization method is applied to approximate the control and reduce the original system to an optimal parameter selection problem, in which both the position and related control are taken as decision variables to be optimized. This problem can be solved as a nonlinear optimization problem by a particle swarm optimization algorithm. The numerical simulations are given to illustrate the effectiveness of the proposed numerical approximation method.     

Integrated control of oriental fruit moth (Lepidoptera: Tortricidae) in peach orchards using insecticide and mating disruption

The efficacy of an integrated and a conventional oriental fruit moth, Grapholita molesta (Busck), control program was compared using 4-ha blocks of peach at three Niagara Peninsula farms during 1997-1999. In the integrated program, chlorpyrifos was used to control first-generation larvae and mating disruption using Isomate M100 pheromone dispensers was used to control the second and third generations. In the conventional program, chlorpyrifos was used to control first-generation larvae and pyrethroids were used to control larvae of the later generations. The average release rate of pheromone was 23.7-26.4 mg/ha/h over a period of 86-91 d. The pheromone treatment reduced the capture of moths in pheromone-baited traps on average by 98%, suggesting a high level of disruption. The integrated program provided control of oriental fruit moth similar to the control provided by a conventional program. The mean percentage of peach shoots infested with first- and second-generation larvae, and fruit infested with third-generation larvae was not significantly greater in the integrated-program blocks during the 3-yr study. The elimination of insecticide sprays from the integrated-program blocks did not result in an increase in damage caused by plant bugs. The incidence of damage caused by other pests was negligible in both the integrated and conventional blocks.     

Long-term studies on the economic impact of ticks on Sanga cattle in Zambia

Three different tick control policies were tested in groups of traditionally managed Sanga cattle in the Central Province of Zambia over a period of 3 years. One group was given strategic tick control using 12 pyrethroid acaricide spray applications between the onset and the end of the wet season (October to March). The productivity of this herd was compared with that of a group with no tick control and a group under an intensive tick control regimen of spraying every week in the wet season and every 2 weeks in the dry season (36 applications per year). The highest output was associated with intensive tick control, followed by strategic control and then no tick control policies. However, when the costs of tick control were taken into account, the strategic tick control policy produced the best economic result, followed by the intensive and then the no tick control policies. Neither the strategic nor the intensive tick control policy was sufficient to prevent the transmission of East Coast fever (ECF) infection when this disease was introduced to the area.     

A modular control design method for a flexible manufacturing cell including error handling

This paper introduces a new modular control design method for a cell controller with integrated error handling. To make the complexity of the cell controller manageable, its control logic is separated into two parts: resource allocation control and operation control. To create the operation control not only quickly but correctly, modular operation blocks integrated with error handling are developed. An algorithm automatically generates the operation control. The operation control created by the proposed method is proved to have desired control behaviors. The method is applied to an example system.     

Multi-Objective Evolutionary Optimization of Biological Pest Control with Impulsive Dynamics in Soybean Crops

The biological pest control in agriculture, an environment-friendly practice, maintains the density of pests below an economic injury level by releasing a suitable quantity of their natural enemies. This work proposes a multi-objective numerical solution to biological pest control for soybean crops, considering both the cost of application of the control action and the cost of economic damages. The system model is nonlinear with impulsive control dynamics, in order to cope more effectively with the actual control action to be applied, which should be performed in a finite number of discrete time instants. The dynamic optimization problem is solved using the NSGA-II, a fast and trustworthy multi-objective genetic algorithm. The results suggest a dual pest control policy, in which the relative price of control action versus the associated additional harvest yield determines the usage of either a low control action strategy or a higher one.     

Biological control and sustainable food production

The use of biological control for the management of pest insects pre-dates the modern pesticide era. The first major successes in biological control occurred with exotic pests controlled by natural enemy species collected from the country or area of origin of the pest (classical control). Augmentative control has been successfully applied against a range of open-field and greenhouse pests, and conservation biological control schemes have been developed with indigenous predators and parasitoids. The cost-benefit ratio for classical biological control is highly favourable (1:250) and for augmentative control is similar to that of insecticides (1:2-1:5), with much lower development costs. Over the past 120 years, more than 5000 introductions of approximately 2000 non-native control agents have been made against arthropod pests in 196 countries or islands with remarkably few environmental problems. Biological control is a key component of a 'systems approach' to integrated pest management, to counteract insecticide-resistant pests, withdrawal of chemicals and minimize the usage of pesticides. Current studies indicate that genetically modified insect-resistant Bt crops may have no adverse effects on the activity or function of predators or parasitoids used in biological control. The introduction of rational approaches for the environmental risk assessment of non-native control agents is an essential step in the wider application of biological control, but future success is strongly dependent on a greater level of investment in research and development by governments and related organizations that are committed to a reduced reliance on chemical control.     

Genetic algorithms with filters for optimal control problems in fed-batch bioreactors

When using a genetic algorithm (GA) to solve optimal control problems that can arise in a fed-batch bioreactor, the most obvious direct approach is to rely on a finite dimensional discretization of the optimal control problem into a nonlinear programming problem. Usually only the control function is discretized, and the continuous control function is approximated by a series of piecewise constant functions. Even though the piecewise discretized controls that the GA produces for the optimal control problem may give good performances, the control policies often show very high activity and differ considerably from those obtained using a continuous optimization strategy. The present study introduces a few filters into a real-coded genetic algorithm as additional operators and investigates the smoothing capabilities of the filters employed. It is observed that inclusion of a filter significantly smoothens the optimal control profile and often encourages the convergence of the algorithm. The applicability of the technique is illustrated by solving two previously reported optimal control problems in fed-batch bioreactors that are known to have singular arcs.     

Human stick balancing: an intermittent control explanation

There are two issues in balancing a stick pivoting on a finger tip (or mechanically on a moving cart): maintaining the stick angle near to vertical and maintaining the horizontal position within the bounds of reach or cart track. The (linearised) dynamics of the angle are second order (although driven by pivot acceleration), and so, as in human standing, control of the angle is not, by itself very difficult. However, once the angle is under control, the position dynamics are, in general, fourth order. This makes control quite difficult for humans (and even an engineering control system requires careful design). Recently, three of the authors have experimentally demonstrated that humans control the stick angle in a special way: the closed-loop inverted pendulum behaves as a non-inverted pendulum with a virtual pivot somewhere between the stick centre and tip and with increased gravity. Moreover, they suggest that the virtual pivot lies at the radius of gyration (about the mass centre) above the mass centre. This paper gives a continuous-time control-theoretical interpretation of the virtual-pendulum approach. In particular, by using a novel cascade control structure, it is shown that the horizontal control of the virtual pivot becomes a second-order problem which is much easier to solve than the generic fourth-order problem. Hence, the use of the virtual pivot approach allows the control problem to be perceived by the subject as two separate second-order problems rather than a single fourth-order problem, and the control problem is therefore simplified. The theoretical predictions are verified using the data previously presented by three of the authors and analysed using a standard parameter estimation method. The experimental data indicate that although all subjects adopt the virtual pivot approach, the less expert subjects exhibit larger amplitude angular motion and poorly controlled translational motion. It is known that human control systems are delayed and intermittent, and therefore, the continuous-time strategy cannot be correct. However, the model of intermittent control used in this paper is based on the virtual pivot continuous-time control scheme, handles time delays and moreover masquerades as the underlying continuous-time controller. In addition, the event-driven properties of intermittent control can explain experimentally observed variability.     

广东省林业有害生物的发生与防控

本文介绍了广东省林业有害生物的发生和防控概况,阐述了广东省以林业有害生物生态控制和绿色防控为导向,在立体化监测的基础上,建立树种合理配植避灾、检疫御灾、持续控制与应急控制相结合减灾的防控技术体系,以及林业有害生物防控技术规范化、标准化,防控工作社会化的保障体系,切实保护森林资源。     

Inverse biomimetics: How robots can help to verify concepts concerning sensorimotor control of human arm and leg movements

Simulation test, hardware test and behavioral comparison test are proposed to experimentally verify whether a technical control concept for limb movements is logically precise, physically sound, and biologically relevant. Thereby, robot test-beds may play an integral part by mimicking functional limb movements. The procedure is exemplarily demonstrated for human aiming movements with the forearm: when comparing competitive control concepts, these movements are described best by a spring-like operating muscular-skeletal device which is assisted by feedforward control through an inverse internal model of the limb – without regress to a forward model of the limb. In a perspective on hopping, the concept of exploitive control is addressed, and its comparison to concepts derived from classical control theory advised.