基于虚拟完整约束的欠驱动起重机控制方法

欠驱动系统的控制是非线性控制的一个重要领域,欠驱动系统指系统控制输入个数小于自由度个数的非线性系统.目前,欠驱动非线性系统动力学和控制研究的主要方法包括线性二次型最优控制方法和部分反馈线性化方法等,如何使系统持续的稳定在平衡位置一直是研究的难点.虚拟约束方法是指通过选择一个周期循环变化的变量作为自变量来设计系统的周期运动.该文以典型的欠驱动模型起重机为例,采用虚拟约束方法,使系统能够在平衡位置稳定或周期振荡运动.首先,通过建立虚拟约束,减少系统自由度变量;然后,通过部分反馈线性化理论推导出系统的状态方程;最后,通过线性二次调节器设计反馈控制器.仿真结果表明,重物在反馈控制下可以在竖直位置的附近达到稳定状态,反映了虚拟约束方法对欠驱动系统的有效性.     

Stabilization of the motion of a spherical robot using feedbacks

The paper is concerned with the problem of stabilizing a spherical robot of combined type during its motion. The focus is on the application of feedback for stabilization of the robot which is an example of an underactuated system. The robot is set in motion by an internal wheeled platform with a rotor placed inside the sphere. The results of experimental investigations for a prototype of the spherical robot are presented.     

Modelling and application of the self-locking phenomenon in the context of a non-discrete impact clutch

This paper describes an application of the self locking phenomenon in order to realize a non-discrete impact clutch. It is used to generate velocity jumps in an underactuated robot manipulator. Due to control reasons the impacts have to be made possible at arbitrary times, which calls for a non-discrete device. Different design alternatives are listed and a numerical simulation as well as a possible mechanical design of the self-locking mechanism are presented. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

State feedback linearization of nonlinear control systems on homogeneous time scales

The paper addresses the state feedback linearization problem for nonlinear systems, defined on homogeneous time scale. Necessary and sufficient solvability conditions are given within the algebraic framework of differential one-forms. The conditions concerning the exact dynamic state feedback linearization are equivalent to the property of differential flatness of the system. An output function which defines a right invertible system without zero-dynamics is shown to exist if and only if the basis of some space of one-forms can be transformed, via polynomial matrix operator over the field of meromorphic functions, into a system of exact one-forms. The results extend the corresponding results for the continuous-time case.     

Decentralized Reliable Control of Interconnected Time-Delay Systems Against Sensor Failures

In this paper, we study the problem of designing decentralized reliable feedback control methods under a class of control failures for a class of linear interconnected continuous-time systems having internal subsystem time-delays and additional time-delay couplings. These failures are described by a model that takes into consideration possible outages or partial failures in every single actuator of each decentralized controller. The decentralized control design is performed through two steps. First, a decentralized stabilizing reliable feedback control set is derived at the subsystem level through the construction of appropriate Lyapunov-Krasovskii functional and, second, a feasible linear matrix inequalities procedure is then established for the effective construction of the control set under different feedback schemes. Two schemes are considered: the first is based on state-measurement and the second utilizes static output-feedback. The decentralized feedback gains in both schemes are determined by convex optimization over linear matrix inequalities. We characterize decentralized linear matrix inequality-based feasibility conditions such that every local closed-loop subsystem of the linear interconnected delay system is delay-dependent robustly asymptotically stable with an γ-level ℒ₂-gain. The developed results are tested on a representative example.     

An optimal control approach to the design of periodic orbits for mechanical systems with impacts

In this paper we study the problem of designing periodic orbits for a special class of hybrid systems, namely mechanical systems with underactuated continuous dynamics and impulse events. We approach the problem by means of optimal control. Specifically, we design an optimal control based strategy that combines trajectory optimization, dynamics embedding, optimal control relaxation and root finding techniques. The proposed strategy allows us to design, in a numerically stable manner, trajectories that optimize a desired cost and satisfy boundary state constraints consistent with a periodic orbit. To show the effectiveness of the proposed strategy, we perform numerical computations on a compass biped model with torso.     

Computation of bounded feed-forward control for underactuated multibody systems using nonlinear optimization

Underactuation occurs, when only some generalized coordinates have a control input. For end-effector trajectory tracking a combined feed-forward and feedback control is often a suitable approach. Feed-forward control design based on an inverse model for underactuated multibody systems is presented. The starting point is the transformation of the multibody system into a nonlinear input-output normal-form. The inverse model follows from this and consists of chains of differentiators, driven internal dynamics and an algebraic part. Especially when using the end-effector as system output the internal dynamics is often unbounded. In order to obtain a viable feed-forward control, a bounded solution must be determined. For this task the internal dynamics is solved as a nonlinear optimization problem. Thereby, the coordinates of the internal dynamics define the objective function which is minimized. The equation of the internal dynamics must be fulfilled at each point of a discrete time grid. In addition continuity of the solution is achieved by adding as equality constraint an integration formula, e.g. trapezoidal rule. The optimization problem is then solved by a SQP-method. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Decentralized Reliable Control of Interconnected Systems with Time-Varying Delays

In this paper, we study the problem of designing decentralized reliable feedback control methods under a class of control failures for a class of linear interconnected continuous-time systems having internal subsystem time-delays and additional time-delay couplings. These failures are described by a model that takes into consideration possible outages or partial failures in every single actuator of each decentralized controller. The decentralized control design is performed through two steps. First, a decentralized stabilizing reliable feedback control set is derived at the subsystem level through the construction of appropriate Lyapunov-Krasovskii functional and, second, a feasible linear matrix inequalities procedure is then established for the effective construction of the control set under different feedback schemes. Two schemes are considered: the first is based on state measurement and the second utilizes static output feedback. The decentralized feedback gains in both schemes are determined by convex optimization over LMIs. We characterize decentralized linear matrix inequalities (LMIs)-based feasibility conditions such that every local closed-loop subsystem of the linear interconnected delay system is delay-dependent robustly asymptotically stable with a γ-level ℒ₂-gain. The developed results are tested on a representative example.     

Optimization of a Class of Nonlinear Dynamic Systems: New Efficient Method without Lagrange Multipliers

This paper deals with optimization of a class of nonlinear dynamic systems with n states and m control inputs commanded to move between two fixed states in a prescribed time. Using conventional procedures with Lagrange multipliers, it is well known that the optimal trajectory is the solution of a two-point boundary-value problem. In this paper, a new procedure for dynamic optimization is presented which relies on tools of feedback linearization to transform nonlinear dynamic systems into linear systems. In this new form, the states and controls can be written as higher derivatives of a subset of the states. Using this new form, it is possible to change constrained dynamic optimization problems into unconstrained problems. The necessary conditions for optimality are then solved efficiently using weighted residual methods.     

An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty

This study presents an interval-parameter fuzzy two-stage stochastic programming (IFTSP) method for the planning of water-resources-management systems under uncertainty. The model is derived by incorporating the concepts of interval-parameter and fuzzy programming techniques within a two-stage stochastic optimization framework. The approach has two major advantages in comparison to other optimization techniques. Firstly, the IFTSP method can incorporate pre-defined water policies directly into its optimization process and, secondly, it can readily integrate inherent system uncertainties expressed not only as possibility and probability distributions but also as discrete intervals directly into its solution procedure. The IFTSP process is applied to an earlier case study of regional water resources management and it is demonstrated how the method efficiently produces stable solutions together with different risk levels of violating pre-established allocation criteria. In addition, a variety of decision alternatives are generated under different combinations of water shortage.     

An approach for optimization of robot-generated rigid-body interpolation using dynamic criteria

The present paper describes an approach for generating spatial trajectories in multibody systems including rigid–body rotations such that dynamic criteria such as forces, accelerations, velocities, etc. as well as limiting restrictions for the motion–generating mechanical device, e.g., a robot, can be considered. The task is to find a rigid–body interpolation that fulfills optimality criteria at the target trajectory as well as in the mechanical system. Application of general optimization methods fails due to the difficulty of finding feasible initial guesses that will converge. The present approach proposes to decouple the general problem into two stages, a first stage in which a pure trajectory optimization is carried out without regard of the mechanical system, and a second stage in which the carrying mechanical system is incorporated. The trajectory planning involves the use of splines of 5–th order as well as an SQP optimization for determining the spline support points as design variables. The approach is illustrated for the example of the generalized waiter problem. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Linear Versus Quadratic Estimators in Linearized Models

In nonlinear regression models an approximate value of an unknown parameter is frequently at our disposal. Then the linearization of the model is used and a linear estimate of the parameter can be calculated. Some criteria how to recognize whether a linearization is possible are developed. In the case that they are not satisfied, it is necessary to take into account either some quadratic corrections or to use the nonlinear least squares method. The aim of the paper is to find some criteria for an ordering linear and quadratic estimators.     

Stability analysis of fractional order neutral-type systems considering time varying delays,nonlinear perturbations,and input saturation

This article investigates the robust stability of fractional order neutral-type systems involving nonlinear perturbations and time varying delays in the presence of input saturation. Design criteria, expressed in terms of linear matrix inequalities, are derived with the aid of the Lyapunov Krasovskii functional for the state feedback controller. Based on the cone complementarity linearization method, an optimization problem is also formulated for finding the controller gains subject to maximizing the domain of attraction. The main results are confirmed by numerical simulations.     

The Lightweight Robot ElRob: Interesting Aspects in Modeling and Control

The articulated robot ElRob, consisting of flexible links and joints, is considered in several publications. Recent developments are presented in this work. The overall goal of the research is to decrease the effects of structural elasticities in lightweight robots. For this purpose model-based control concepts are investigated and very accurate and efficient kinematic and dynamic models are necessary. The robot is split into groups of bodies, the so called subsystems, with separated describing velocities and coordinate systems. To obtain structured equations of motion the Projection Equation is used. The beams are modelled using the floating frame of reference formulation and a Ritz-approach. Because of its flexibility, the examined robot is an underactuated system leading to special difficulties. As an example is it not possible to compute the desired joint angles with respect to a reference path in task space for the flexible system (inverse kinematic problem). Different methods to solve this drawback and other problems resulting from flexibility are discussed with special focus on feed forward control and different feedback control concepts. The resulting end point error, the necessary control input and other interesting results for the laboratory experiment are presented and compared. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Forced nonlinear oscillation of underactuated systems: the balance board example

In this contribution we consider a mechanical model of the so-called balance board or “indoboard” system, which is an unstable underactuated mechanical system. Instead of stabilizing one equilibrium point we investigate the asymptotic stabilization of a closed orbit, which results in a nonlinear oscillation. To this end the system is considered in coordinates of the real Jordan normal form, which facilitates the construction of a Control-Lyapunov function. On this basis, a nonlinear feedback law which renders the periodic orbit asymptotically stable is easily derived via Sontags formula. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Nonlinear goal programming using multi-objective genetic algorithms

Goal programming is a technique often used in engineering design activities primarily to find a compromised solution which will simultaneously satisfy a number of design goals. In solving goal programming problems, classical methods reduce the multiple goal-attainment problem into a single objective of minimizing a weighted sum of deviations from goals. This procedure has a number of known difficulties. First, the obtained solution to the goal programming problem is sensitive to the chosen weight vector. Second, the conversion to a single-objective optimization problem involves additional constraints. Third, since most real-world goal programming problems involve nonlinear criterion functions, the resulting single-objective optimization problem becomes a nonlinear programming problem, which is difficult to solve using classical optimization methods. In tackling nonlinear goal programming problems, although successive linearization techniques have been suggested, they are found to be sensitive to the chosen starting solution. In this paper, we pose the goal programming problem as a multi-objective optimization problem of minimizing deviations from individual goals and then suggest an evolutionary optimization algorithm to find multiple Pareto-optimal solutions of the resulting multi-objective optimization problem. The proposed approach alleviates all the above difficulties. It does not need any weight vector. It eliminates the need of having extra constraints needed with the classical formulations. The proposed approach is also suitable for solving goal programming problems having nonlinear criterion functions and having a non-convex trade-off region. The efficacy of the proposed approach is demonstrated by solving a number of nonlinear goal programming test problems and an engineering design problem. In all problems, multiple solutions (each corresponding to a different weight vector) to the goal programming problem are found in one single simulation run. The results suggest that the proposed approach is an effective and practical tool for solving real-world goal programming problems.     

Perspectives on Constructive and Functional Optimizing of a Serial Robot with Four Degrees of Freedom Destined for Special Applications

This paper deals with aspects on the dynamic modulation of the robots mechanical structure, using Lagrangian formalism, choosing the adequate DC servomotors, translation modules constituting the TTRT robot, the constructive solution and modelling the three translation subassemblies of the studied robot, with the intention that, in the end, based on a dynamic-organologic algorithm, a functional optimization of the robot be brought out within a workcell destined for special applications, so that the energetic consumption be as low as possible. This paper also presents the organological calculi and solutions for the efficient design of modules specific to mechanical structures of industrial serial-modular robots. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Orbital stabilization of a class of underactuated mechanical systems

Typically, the aim of a controller is to stabilize an equilibrium or a reference trajectory. For underactuated mechanical systems this objective might not be achievable because of the occurance of limit cycles due to discontinuous effects like actuator backlash or Coulomb friction. Therefore, an alternative approach is to explicitly impose a stable periodic orbit on the system by a suited controller. This way at least amplitude, frequency and settling time can be influenced directly. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Using artificial reaction force to design compliant mechanism with multiple equality displacement constraints

Monolithic compliant mechanisms are elastic workpieces which transmit force and displacement from an input position to an output position. Continuum topology optimization is suitable to generate the optimized topology, shape and size of such compliant mechanisms. The optimization strategy for a single input single output compliant mechanism under volume constraint is known to be best implemented using an optimality criteria or similar mathematical programming method. In this standard form, the method appears unsuitable for the design of compliant mechanisms which are subject to multiple outputs and multiple constraints. Therefore an optimization model that is subject to multiple design constraints is required. With regard to the design problem of compliant mechanisms subject to multiple equality displacement constraints and an area constraint, we here present a unified sensitivity analysis procedure based on artificial reaction forces, in which the key idea is built upon the Lagrange multiplier method. Because the resultant sensitivity expression obtained by this procedure already compromises the effects of all the equality displacement constraints, a simple optimization method, such as the optimality criteria method, can then be used to implement an area constraint. Mesh adaptation and anisotropic filtering method are used to obtain clearly defined monolithic compliant mechanisms without obvious hinges. Numerical examples in 2D and 3D based on linear small deformation analysis are presented to illustrate the success of the method.