Force Balancing Design and Trajectory Tracking Control of Real-Time Controllable Mechanisms
Date
2002
Authors
Ouyang, Puren
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
Type
Thesis
Degree Level
Abstract
Real-time controllable (RTC) mechanisms refer to those mechanisms driven by RTC
actuators or servomotors. There are many benefits to an R TC mechanism that is force
balanced. A novel method called the Adjusting Kinematic Parameters method for force
balancing of R TC mechanisms is more promising than the Counterweights method. The
motivation of the research described in this thesis is to overcome the problems with the
present Adjusting Kinematic Parameters method and further extend it to be more general
and robust.
The extended Adjusting Kinematic Parameters method is presented in this thesis. This
method can work for any general mass distribution of a closed-loop RTC mechanism,
and is extended to incorporate the masses of adjusting sliding blocks. The extended
Adjusting Kinematic Parameters method has been verified to be consistently better than
the Counterweights method for closed-loop RTC mechanisms.
The generic task of an RTC mechanism is trajectory tracking. Trajectory planning is
needed for trajectory tracking. A new method for trajectory planning that can achieve C3
continuity is developed in this thesis. The new method, based on quintic polynomials for
trajectory planning, can insure that the trajectory has a smooth acceleration curve and a
continuous jerk on the trajectory.
The dynamics of an R TC mechanism is important for developing a better controller to
achieve optimal trajectory tracking performance. To study the extended AKP method,
the dynamic model of a 2 degree of freedom RTC mechanism is developed with
consideration of the off-line mass center of a link using the reduced order method.
Stability analysis for the Proportional Derivative (PD) control applied to the closed-loop
RTC mechanism is discussed.
Dynamic control is an essential part of an RTC mechanism. Based on the analysis of the
existing Nonlinear P D control method and the Computed Torque Control method, a
novel PD-based control method, namely, the Evolutionary PD control method, is
proposed. The Evolutionary PD method incorporates plant dynamics into the control law
in such a way that the control law is the result of the superposition of a series of runs of a
controlled plant system.
Case studies are carried out for force balanced mechanisms using the extended Adjusting
Kinematic Parameters method, the Counterweights method, and the unbalanced
mechanism in terms of the joint forces, trajectory tracking performance, and fluctuation
of the torques in the actuators. Three control laws (i.e., PD control, Nonlinear PD
control, and Evolutionary PD control) are used to perform the feedback control for
several case studies. All the simulation results show that the extended Adjusting
Kinematic Parameters method is better than the Counterweights method with respect to
the reduction of joint forces and trajectory tracking errors. It is also shown that the Evolutionary PD control law is a promising control law when compared with the
PDlNonlinear PD control laws in terms of the selection of control gain and high
trajectory tracking performance.