Mechanical advantage assurance control of quick-return mechanisms in task space

Quick-return mechanisms are usually controlled by joint-space controllers to avoid instability in the transition between cutting and return phases. These controllers cannot exploit the mechanical advantage associated to the natural mechanism's movement in the task space. It is crucial to guarantee mechanical advantage exploitation to reduce operation time and high-quality cutting finishes. In view of the above, this paper reports the design of a mechanical advantage assurance controller based on: i) a slider physics model that captures all the information associated to the main mechanism's task, and ii) a Jacobian compensator that avoids the controllability problems from the transition between the cutting and return phases. Simulation studies are carried out to verify each component of the proposed controller. A constant cutting velocity task is used as a case of study to demonstrate the mechanical advantage exploitation

Constant speed control of slider-crank mechanisms: a joint-task space hybrid control approach

In this paper, a constant speed control of slider-crank mechanisms for machine tools is proposed. A joint-task space hybrid controller based on a second-order sliding mode control and time-base generator was used to guarantee a constant speed trajectory tracking and a complete turn of the mechanism crank. A switching criterion was implemented in order to avoid the singularities located at the two extreme positions of the slider stroke. A trapezoidal speed profile with parabolic blends was designed directly over task space slider trajectory considering a constant cutting speed, the workpiece dimensions and the slider stroke length. Stability of the second-order sliding mode control was validated with the Lyapunov stability theory. Simulations were carried out to verify this approach

Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans

The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product

An input error method for parameter identification of a class of Euler-Lagrange systems

In this paper, an input error identification algorithm for a class of Euler-Lagrange systems is proposed. The algorithm has a state-observer structure which uses the input error between the real system and an estimated model instead of the output error. Both systems are controlled by two Proportional-Derivative (PD) controllers with the same gain values. An excitation signal is added to the PD controllers to guarantee parameter estimates convergence. Stability of the complete identification method and parameter estimates convergence are assessed via Lyapunov stability theory. Simulation studies are carried out to verify the approach

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

State estimation in multibody systems with rigid or flexible links

In the multibody field the design of state observers proves useful for several tasks, ranging from the synthesis of control schemes and fault detection strategies, to the identication of uncertain parameters. State observers are designed to obtain accurate estimates of unmeasurable or unmeasured variables. Their accuracy and performance depend on both the estimation algorithms and the system models. Indeed, on the one hand the estimation algorithms should be able to cope with multibody system (MBS) nonlinearities. On the other, MB models should be suitable to state estimation, i.e. accurate and computationally efficient. In order to obtain the best results, it has been necessary to develop dierent approaches for rigid-link and flexible-link MBSs. In the case of rigid-link MBSs, state observers based on nonlinear kinematic models (i.e. kinematic constraint equations) have been developed. When compared to dynamic models, kinematic models present some relevant advantages. In particular, they are less complex and much less aected by uncertainty. Additionally, though kinematics-based observers do not require force and torque measurements (often dicult to gather) as inputs, they can be successfully employed for estimating unknown forces: to this purpose a novel two-stage approach is proposed in this dissertation. As far as modeling flexible-link MBSs is concerned, it is more complicated and makes the implementation of kinematics-based observers impossible, since it is not possible to decouple kinematics from dynamics easily. Furthermore, the so called ne motion of such systems is typically described through a large number of elastic coordinates, which in turns leads to high model dimensions, and to very inefficient, if not impossible to synthesize, state observers. In order to address this issue, firstly, a new strategy has been developed to keep model dimensions to a minimum. Such a strategy leads to a signicant reduction in the size of the models, which, in turns, provide an appropriate representation of the system dynamics in a frequency range of interest. The availability of reduced-dimension but accurate models for flexible-link MBSs poses the way to the synthesis of more efficient observers provided that a suitable estimation algorithm is chosen. This thesis also collects results from a large number of numerical and experimental tests carried out to validate the intermediate and nal outcomes of the theoretical investigations

Design and Control of Flapping Wing Micro Air Vehicles

Flapping wing Micro Air Vehicles (MAVs) continues to be a growing field, with ongoing research into unsteady, low Re aerodynamics, micro-fabrication, and fluid-structure interaction. However, research into flapping wing control of such MAVs continues to lag. Existing research uniformly consists of proposed control laws that are validated by computer simulations of quasi-steady blade-element formulae. Such simulations use numerous assumptions and cannot be trusted to fully describe the flow physics. Instead, such control laws must be validated on hardware. Here, a novel control technique is proposed called Bi-harmonic Amplitude and Bias Modulation (BABM) which can generate forces and moments in 5 vehicle degrees of freedom with only two actuators. Several MAV prototypes were designed and manufactured with independently controllable wings capable of prescribing arbitrary wing trajectories. The forces and moments generated by a MAV utilizing the BABM control technique were measured on a 6-component balance. These experiments verified that a prototype can generate uncoupled forces and moments for motion in five degrees of freedom when using the BABM control technique, and that these forces can be approximated by quasi-steady blade-element formulae. Finally, the prototype performed preliminary controlled flight in constrained motion experiments, further demonstrating the feasibility of BABM

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world