Investigation of optimal bipedal walking gaits subject to different energy-based objective functions

Optimal bipedal walking gaits subject to different energy-based objective functions are investigated using a simple planar rigid body model of a bipedal robot with upper body, thighs and shanks. The robot's segments are connected by revolute joints actuated by electric motors. The actuators' torques are generated by a trajectory tracking controller to produce periodic walking gaits. A numerical optimization routine is used to find optimal reference trajectories for average speeds in the range of 0.3 – 2.3 m/s to investigate the influence of different objective functions. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A damped bipedal inverted pendulum for human–structure interaction analysis

The bipedal inverted pendulum with damping has been adopted to simulate human–structure interaction recently. However, the lack of analysis and verification has provided motivation for further investigation. Leg damping and energy compensation strategy are required for the bipedal inverted pendulum to regulate gait patterns on vibrating structures. In this paper, the Hunt–Crossley model is adopted to get zeros contact force at touch down, while energy compensation is achieved by adjusting the stiffness and rest length of the legs. The damped bipedal inverted pendulum can achieve stable periodic gait with a lower energy input and flatter attack angle so that more gaits are available, compared to the template, referred to as spring-load inverted pendulum. The measured and simulated vertical ground reaction force-time histories are in good agreement. In addition, the dynamic load factors are also within a reasonable range. Parametric analysis shows that the damped bipedal inverted pendulum can achieve stable gaits of 1.6 to 2.4 Hz with a reasonable first harmonic dynamic load factor, which covers the normal walking step frequency. The proposed model in this paper can be applied to human–structure interaction analysis.     

Generating human-like reaching movements with a humanoid robot: A computational approach

This paper presents a computational approach for transferring principles of human motor control to humanoid robots. A neurobiological model, stating that the energy of motoneurons is minimized and that dynamic and static efforts are processed separately, is considered. This paradigm is used to produce humanoid robot's reaching movements obeying the rules of human kinematics. A nonlinear programming problem is solved to determine optimal trajectories. The optimal movements are then encoded by using a basis of motor primitives determined by principal component analysis. Finally, generalization to new movements is obtained by solving of a low-dimensional optimization problem in the operational space.     

Generating a reference trajectory with defined kinematics for the IRb-6 manipulator

The fundamental problem in industrial robots control concerns algorithms generating reference trajectories.References [1–4] suggest generating algorithms of a reference trajectory, which are based on an arbitrary discretization of the manipulator's internal coordinates. Each point of discretization in the external space approximating a reference trajectory corresponds to known discretized internal coordinates of the manipulator.In [5–7], iteration methods of determining the internal coordinates corresponding to external coordinates of the reference trajectory point have been suggested. In this method of internal coordinates, determining the point of the reference trajectory is being approached in successive steps of an iterative computation. In [5], a modified iterative method of generation of a straight segment reference trajectory has been presented.Analytic formulae, which are the solution of an inverse problem of manipulator kinematics, enable design of trajectory generating algorithms which compute, in one step only, the internal coordinates of points lying exactly on the reference trajectory, with the accuracy resulting from the computer register length.In this paper, the author has presented an original PLAN2 computer algorithm generating reference trajectories of motion for a task. The kinematics of those trajectories is defined at selected points through which a task is to be passed, the distances between them being optional. The algorithm is based on formulae which are analytic solutions to an inverse problem for an IRb-6 manipulator kinematics.     

Multi-train trajectory optimization for energy-efficient timetabling

This paper proposes a novel approach for energy-efficient timetabling by adjusting the running time allocation of given timetables using train trajectory optimization. The approach first converts the arrival and departure times to time window constraints in order to relax the given timetable. Then a train trajectory optimization method is developed to find optimal arrival/departure times and optimal energy-efficient speed profiles within the relaxed time windows. The proposed train trajectory optimization method includes two types, a single-train trajectory optimization (STTO), which focuses on optimizing individual train movements within the relaxed arrival and departure time windows, and a multi-train trajectory optimization (MTTO), which computes multi-train trajectories simultaneously with a shared objective of minimizing multi-train energy consumption and an additional target of eliminating conflicts between trains. The STTO and MTTO are re-formulated as a multiple-phase optimal control problem, which has the advantage of accurately incorporating varying gradients, curves and speed limits and different train routes. The multiple-phase optimal control problem is then solved by a pseudospectral method. The proposed approach is applied in case studies to fine-tune two timetables, for a single-track railway corridor and a double-track corridor of the Dutch railway. The results suggest that the proposed approach is able to improve the energy efficiency of a timetable.     

Simulation-based optimisation of wastewater flow and composition for on-site treatment in the food and beverage industry utilising reference nets in combination with genetic algorithms

This study introduces the concept of computer modelling and simulation of complex bioprocesses and systems using an approach that combines the reference net formalism with machine learning and optimisation techniques. Reference nets are an extension of high level Petri Nets, which can be used as a central visualisation and modelling tool. The net-in-net paradigm used by reference nets makes it possible to model complex processes, such as those found in the food and beverage industry. A plugin/interface system based on the java programming language allows implementation of advanced mathematical modelling techniques at specific points in entire system simulations. Separate optimisation tools can also run and modify existing reference net models for fast solutions to efficiency problems. We present an example system that simulates a specific section of a beer brewery using the reference net formalism, which is optimised using a genetic algorithm. We show in detail how the different software packages can be combined for a simulation based optimisation approach. The optimisation technique specifically addresses the wastewater pollution load in regard to its chemical oxygen demand. A beer brewery was chosen as an example for this study due to the constantly increasing requirements to lower energy and water consumption in this industry. One possibility to lower the energy and water demands is to effectively treat wastewater produced by the brewery, which can introduce cost savings by providing recycled water and biogas. Most approaches to wastewater treatment are end-of-pipe solutions that do not consider the brewery as a whole. A brewery contains many processes that can be running concurrently and interacting with one another (e.g. brewing, clean-in-place and bottling) with each process producing varying amounts of wastewater with different pollution loads. Optimisation of the scheduling of the different processes with respect to the wastewater production will allow for more effective wastewater treatment, and therefore cost and energy savings. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A Two Phase Mixture Model based on Bone Observation

An optimization method is developed to describe the mechanical behaviour of the human cancellous bone. The method is based on a mixture theory. A careful observation of the behaviour of the bone material leads to the hypothesis that the bone density is controlled by the principal stress trajectories (Wolff's law). The basic idea of the developed method is the coupling of a scalar value via an eigenvalue problem to the principal stress trajectories. On the one hand this theory will permit a prediction of the reaction of the biological bone structure after the implantation of a prosthesis, on the other hand it may be useful in engineering optimization problems. An analytical example shows its efficiency. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Robust control of chaos in Chua’s circuit based on internal model principle

The paper treats the question of robust control of chaos in Chua’s circuit based on the internal model principle. The Chua’s diode has polynomial non-linearity and it is assumed that the parameters of the circuit are not known. A robust control law for the asymptotic regulation of the output (node voltage) along constant and sinusoidal reference trajectories is derived. For the derivation of the control law, the non-linear regulator equations are solved to obtain a manifold in the state space on which the output error is zero and an internal model of the k-fold exosystem (k = 3 here) is constructed. Then a feedback control law using the optimal control theory or pole placement technique for the stabilization of the augmented system including the Chua’s circuit and the internal model is derived. In the closed-loop system, robust output node voltage trajectory tracking of sinusoidal and constant reference trajectories are accomplished and in the steady state, the remaining state variables converge to periodic and constant trajectories, respectively. Simulation results are presented which show that in the closed-loop system, asymptotic trajectory control, disturbance rejection and suppression of chaotic motion in spite of uncertainties in the system are accomplished.     

On the Suitability of Different Online Gait Generation Methods for Pre-Defined Footsteps

Detailed dynamical modeling is the basis for simulation and model based control. In this contribution the Projection Equation is used for the modeling of a biped walking machine, resulting in the equations of motion which are needed for gait generation and verification of its stability. For biped robots one main issue is the generation of stable trajectories for the center of mass (CoM). Several different approaches based on the Zero Moment Point (ZMP) scheme have been presented in the past. Due to the complex dynamic structure of bipedal robots most of the considered algorithms use a linear inverted pendulum as a simplified model. This results in a decoupling of the ZMP equations in lateral and forward direction, but limits the trajectories to a constant height of the CoM. An extension of the well known LQR theory by future reference values has been proposed. This model based approach seems to perform quite well, but does not allow the consideration of constraints on the position of the ZMP. This limitation is removed by the use of Model Predictive Control (MPC) with inequality constraints. By extending this approach to a time invariant one the restriction to a constant height of the CoM is no longer necessary. Both methods as well as the time invariant approach for variable CoM heights have been evaluated in simulations and will be experimentally verified on a real robot soon. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Is the statement of Murphy's law valid?

Murphy's Law is not a law in the formal sense yet popular science often compares it with the Second Law of Thermodynamics as both the statements point toward a more disorganized state with time. In this article, we first construct a mathematically equivalent statement for Murphy's Law and then disprove it using the intuitive idea that energy differences will level off along the paths of steepest descent, or along trajectories of least action. © 2015 Wiley Periodicals, Inc. Complexity 21: 374–380, 2016     

环境规制强度影响能源效率的门槛效应研究——基于PSTR模型

利用非径向-SBM和CCR模型测算了我国30个省市(暂不包括西藏和港澳台地区)2007-2016年间的环境规制强度以及能源效率,构建面板平滑转移回归模型(PSTR),分析了环境规制强度对我国能源效率的连续非线性变化的影响.研究结果显示,全国环境规制强度对我国能源效率存在非线性效应,二者之间呈倒“U”型关系.环境规制强度小于门槛值0.6376时,环境规制对能源效率产生创新补偿效应,当环境规制强度高于门槛值0.6376时,环境规制对能源效率产生遵循成本效应.而我国东西部地区的环境规制强度与地区能源效率间却存在着与之相反的“U”型效应.     

Running uphill: energy needs and Naismith's Rule

In this note we make two points, from which follows a suggestion for running uphill:(1) an athlete's energy needs in running up a slope of gradient θ at a speed V may be considered to have three additive elements: that needed to stay alive; that needed to run at a speed V on the level; that needed to lift the body at a rate V sin θ.(2) corresponding to Naismith's rule of 1 to 8, in whole numbers, for walking or running in mountainous country (1 foot of ascent is equivalent to 8 feet on the level), the rule for running on a treadmill is 1 to 3 and the rule for running on roads is 1 to 4 or 5.This result suggests that, if possible, a runner should zigzag up slopes steeper than 1 in 8 on the fells and zigzag up slopes greater than 1 in 4 or 5 on roads.     

Value and information: A profit maximizing strategy for Maxwell's demon

Applications of Lagrange's method of undetermined multipliers in physics and economics suggest some analogies between the two disciplines. Applying Jaynes' approach to information theory reveals the long standing problem of Maxwell's demon in thermodynamics as a constrained optimization problem where information and energy are dual concepts. Temperature emerges as the energetic price of information. This approach highlights the economic features of the Maxwell demon discussed by Bridgman. It also suggests that an analog to temperature (or the price of information) should be present in any optimization problem constrained by costly information. A trivial economics example is presented where generalized temperature measures informational efficiency in the sense of Grossman and Stiglitz.     

Computational Simulation of Bone Remodeling using Design Space Topology Optimization

The law of bone remodeling, commonly referred to as Wolff's Law, asserts that the internal trabecular bone adapts to external loadings, reorienting with the principal stress trajectories to optimize mechanical efficiency creating a naturally optimum structure. The current study utilized an advanced structural optimization algorithm, called design space toptimization (DSO), to perform a three-dimensional computational bone remodeling simulation on the human proximal femur and analyse the results to determine the validity of Wolff's hypothesis. DSO optimizes the layout of material by iteratively distributing it into the areas of highest loading, while simultaneously changing the design domain to increase computational efficiency. The large-scale simulation utilized a 175 µm mesh resolution with over 23.3 million elements. The resulting anisotropic trabecular architecture was compared to both Wolff's trajectory hypothesis and natural femur samples from literature using radiography. The results qualitatively showed several anisotropic trabecular regions that were comparable to the natural human femur. The realistic simulated trabecular geometry suggests that the DSO method can accurately predict bone adaptation due to mechanical loading and that the proximal femur is an optimum structure as Wolff hypothesized. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems

In this paper, the problem of characterizing adaptive output feedback control laws for a general class of unknown MIMO linear systems is considered. Specifically, the presented control approach relies on three components, i.e., a predictor, a reference model and a controller. The predictor is designed to predict the system’s output with arbitrary accuracy, for any admissible control input. Subsequently, a full state feedback control law is designed to control the predictor output to approach the reference system, while the reference system tracks the desired trajectory. Ultimately, the control objective of driving the actual system output to track the desired trajectories is achieved by showing that the system output, the predictor output and the reference system trajectories all converge to each other.     

The training institution efficiency of the semiconductor institute programme in Taiwan—application of spatiotemporal ICA with DEA approach

Despite the fact that Taiwan’s high-tech industry has gradually secured a leading position in the world, enterprises in Taiwan have striven to strengthen their technical advancement by providing employees with various internal or external training programmes. These institutional training programmes are designed to sustain competitive advantage, enhance the quality of manpower and improve operational efficiency. Much literature assesses the efficiency of an internal training programme that is initiated by a firm, but only a little literature studies the efficiency of an external training programme that is led by a government. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, the DEA's capability to discriminate efficient decision-making units from inefficient decision-making units requires much improvement (Adler and Yazhemsky). In this paper, a two-stage approach of integrating spatiotemporal independent component analysis (stICA) and DEA is developed for efficiency measurement. stICA is used to search for latent source signals where no relevant signal mixture mechanisms are available; and DEA is used to measure the relative efficiencies of decision-making units (DMUs). We suggest using stICA first to extract the input variables for generating independent components (IC), then selecting the ICs representing the independent sources of input variables, and finally inputting the selected ICs as new variables in the DEA model. To find the effects of environmental variables on the estimated efficiency scores, the Tobit–Bayes (censored) regression is applied. A simulated dataset and the training institution dataset provided by the Semiconductor Institute in Taiwan is used for analysis. The empirical result shows that the proposed method can not only separate performance differences between the training institutions but also improve the discriminatory capability of the DEA's efficiency measurement. The study results can serve as a reference for training institutions wishing to enhance their training efficiency.     

Impulse and continuous control of piecewise deterministic Markov processes

In this paper we consider the problem of impulse and continuous control on the jump rate and post jump location parameters of piecewise-deterministic Markov processes (PDP's). In a companion paper we studied the optimal stopping with continuous control problem of PDP's assuming only absolutely continuity along trajectories hypothesis on the final cost function. In this paper we apply these results to obtain optimality equations for the impulse and continuous control problem of PDP's in terms of a set of quasi-variational inequalities as well as on the first jump time operator of the process. No continuity or differential assumptions on the whole state space, neither stability assumptions on the parameters of the problem are required. It is shown that if the post intervention operator satisfies some locally lipschitz continuity along trajectories properties then so will the value function of the impulse and continuous control problem.     

The time-optimal control problem in Banach spaces

We show here that a variant of Pontryagin's maximum principle holds for time-optimal trajectories of the systemu′ = Au + f that begin and end at the domain ofA. HereA is the infinitesimal generator of a strongly continuous semigroupS(·) in the reflexive Banach spaceE. This partly generalizes a result of Balakrishnan ([1]) where no conditions are assumed on the trajectories but whereS(t) is supposed to beonto for allt ≥ 0. A weakened version of the maximum principle is then proved forall time-optimal trajectories whenA generates an analytic semigroup andE is a Hilbert space. Finally, the results are modified to handle two examples involving the heat equation where the spaceE is not reflexive.     

Limiting Absorption Principle for the Dissipative Helmholtz Equation

Adapting Mourre's commutator method to the dissipative setting, we prove a limiting absorption principle for a class of abstract dissipative operators. A consequence is the uniform resolvent estimate for the high-frequency Helmholtz equation when trapped classical trajectories meet the region where the absorption coefficient is non-zero. We also give the resolvent estimate in Besov spaces.