Energy-Optimal Control of Over-Actuated Systems - with Application to a Hybrid Feed Drive

Over-actuated (or input-redundant) systems are characterized by the use of more actuators than the degrees of freedom to be controlled. They are widely used in modern mechanical systems to satisfy various control requirements, such as precision, motion range, fault tolerance, and energy efficiency. This thesis is particularly motivated by an over-actuated hybrid feed drive (HFD) which combines two complementary actuators with the aim to reduce energy consumption without sacrificing positioning accuracy in precision manufacturing. This work addresses the control challenges in achieving energy optimality without sacrificing control performance in so-called weakly input-redundant systems, which characterize the HFD and most other over-actuated systems used in practice. Using calculus of variations, an optimal control ratio/subspace is derived to specify the optimal relationship among the redundant actuators irrespective of external disturbances, leading to a new technique termed optimal control subspace-based (OCS) control allocation. It is shown that the optimal control ratio/subspace is non-causal; accordingly, a causal approximation is proposed and employed in energy-efficient structured controller design for the HFD. Moreover, the concept of control proxy is proposed as an accurate causal measurement of the deviation from the optimal control ratio/subspace. The proxy enables control allocation for weakly redundant systems to be converted into regulation problems, which can be tackled using standard controller design methodologies. Compared to an existing allocation technique, proxy-based control allocation is shown to dynamically allocate control efforts optimally without sacrificing control performance. The relationship between the proposed OCS control allocation and the traditional linear quadratic control approach is discussed for weakly input redundant systems. The two approaches are shown to be equivalent given perfect knowledge of disturbances; however, the OCS control allocation approach is shown to be more desirable for practical applications like the HFD, where disturbances are typically unknown. The OCS control allocation approach is validated in simulations and machining experiments on the HFD; significant reductions in control energy without sacrificing positioning accuracy are achieved.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146104/1/molong_1.pd

Identification and Adaptive Control for High-performance AC Drive Systems.

High-performance AC machinery and drive systems can be found in a variety of applications ranging from motion control to vehicle propulsion. However, machine parameters can vary significantly with electrical frequency, flux levels, and temperature, degrading the performance of the drive system. While adaptive control techniques can be used to estimate machine parameters online, it is sometimes desirable to estimate certain parameters offline. Additionally, parameter identification and control are typically conflicting objectives with identification requiring plant inputs which are rich in harmonics, and control objectives often consisting of regulation to a constant set-point. In this dissertation, we present research which seeks to address these issues for high-performance AC machinery and drive systems. The first part of this dissertation concerns the offline identification of induction machine parameters. Specifically, we have developed a new technique for induction machine parameter identification which can easily be implemented using a voltage-source inverter. The proposed technique is based on fitting steady-state experimental data to the circular stator current locus in the stator flux linkage reference-frame for varying steady-state slip frequencies, and provides accurate estimates of the magnetic parameters, as well as the rotor resistance and core loss conductance. Experimental results for a 43 kW induction machine are provided which demonstrate the utility of the proposed technique by characterizing the machine over a wide range of flux levels, including magnetic saturation. The remainder of this dissertation concerns the development of generalizable design methodologies for Simultaneous Identification and Control (SIC) of overactuated systems via case studies with Permanent Magnet Synchronous Machines (PMSMs). Specifically, we present different approaches to the design of adaptive controllers for PMSMs which exploit overactuation to achieve identification and control objectives simultaneously. The first approach utilizes a disturbance decoupling control law to prevent the excitation input from perturbing the regulated output. The second approach uses a Lyapunov-based adaptive controller to constrain the states to the output error-zeroing manifold on which they are varied to provide excitation for parameter identification. Finally, a receding-horizon control allocation approach is presented which includes a metric for generating persistently exciting reference trajectories.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120862/1/davereed_1.pd

Design of the Annular Suspension and Pointing System (ASPS) (including design addendum)

The Annular Suspension and Pointing System is an experiment pointing mount designed for extremely precise 3 axis orientation of shuttle experiments. It utilizes actively controlled magnetic bearing to provide noncontacting vernier pointing and translational isolation of the experiment. The design of the system is presented and analyzed

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

Controller design of a robotic orthosis using sinusoidal-input describing function model

Stroke is one of top leading causes of death in the world and it happens to more than 15 million people yearly. According to the National Stroke Association of Malaysia (NASAM), stroke is the third leading cause of death in Malaysia with around 40,000 cases reported annually. Forty percent of stroke survivors suffer from movement impairments after stroke. My grandfather was one of the victims and he was unable to attend any rehabilitation sessions due to several reasons. Hence, he lost the golden time to regain his movement and freedom. There are a lot of similar cases that happen daily in Malaysia. Besides, as the number of stroke patients increases yearly, the need for physiotherapists or rehabilitation machines equally increases. Hence, a low-cost clinical rehabilitation device is essential to provide assistance for an effective rehabilitation program and substitute the conventional method, as well as to reduce the burden of physiotherapists. In future, the proposed rehabilitation device would benefit not only stroke patients, but any patients who lost their normal walking ability including post-accident patients or those who suffer from spinal cord injury. The rehabilitation device aims to provide training assistance to patients not only in rehabilitation centres but also at home for daily training. The robotic orthosis is planned to be configured based on moving joint angles of human lower extremities. In the first stage of this research, angle-time characteristics for knee and hip swinging motion are utilised as a sagittal motion reference for the rehabilitation devices. The aim of following a proper gait cycle during rehabilitation training is to train patients to perform standing and swinging phases at proper timing and simultaneously provide the correct position reference to the patient during rehabilitation training. This can prevent patients from walking abnormally with an asymmetric gait cycle along or after the rehabilitation program. Besides, various limitations and the bulky structure of other rehabilitation devices lead to the design of the two-link lower limb rehabilitation device. This project aims to develop an assistive robotic rehabilitation device that generates a human gait trajectory for hemiplegic stroke patient gait rehabilitation in future. The shortcomings of other control applications due to environmental conditions and disturbances lead to the implementation of the describing function approach in the development of the devices. A sinusoidal-input describing function (SIDF) approach was implemented to linearize the nonlinear robotic orthosis with linear transfer function. The reason for utilising the SIDF approach is due to the nonlinear actual plant model with the present of load torque disturbances, discontinuous nonlinearities such as saturation and backlash, and also multivariable in the system. The nonlinear properties of the plant were proven in the preliminary stage of the research. A conventional controller, PID control combined with position and trajectory inputs were also applied to the system in the early stage of research. However, the experimental results were not satisfying. Finally, the SIDF approach was chosen to linearize the nonlinear system. Hence, generating a controller is much easier with a linear model of the nonlinear system. A SIDF approach was implemented to generate a controller for the multivariable, nonlinear closed loop system. Firstly, the SIDF approach enables the determination of the linear function of the nonlinear model known as the SIDF model. By utilising the linear model to mimic the behaviour of the nonlinear rehabilitation system, the controller for the nonlinear plant was able to be generated. In this research a controller based on linear control theory technique was used. The MATLAB library was used to design the lead-lag controller for the rehabilitation device. Various simulations such as step responses, tracking and decoupling of both links were performed on the generated controller with the nonlinear model to study the capability of the controller. Besides that, real life experiment testing was carried out to validate the feasibility of the controller designed via the SIDF approach. Simulation and experimental results were obtained, compared, and discussed. The highly accurate responses gained from experimental setup showed the robustness of the controller generated via SIDF approach. The implementation of the SIDF approach in a rehabilitation device (vertical two-link manipulator) is a first and hence, fulfils a novelty requirement for this research

Modeling Of Legged Locomotion With A Suspended Load In The Sagittal Plane

Walking or running while carrying loads has always been a tedious task, more so when the loads are heavy. Such a task of carrying loads not only requires extra effort but also leads to physical pain and in some cases injury. Prior studies on human locomotion with a suspended load have used models that are restricted in their DOFs and so are not able to take into account the fore aft movement in human beings. The objective of this thesis is to model the dynamics of sagittal plane center-of-mass locomotion with a suspended load and apply findings to carrying loads with an elastic pole. The approach taken was to develop and analyze a variant of the Hip Actuated Spring-Loaded Inverted Pendulum (SLIP) model of locomotion that has a second sprung mass added to represent a suspended load. This model showed a large increment in human running speed and stride frequency as the suspension stiffness was increased. A stability analysis on the model showed branching among fixed points with one branch nearly stable while the other branch has greater stability. This particular model was able to show a reduction in peak forces and amplitude of the load for very compliant suspensions. In order to limit velocity change that occurs with changing suspension stiffness, a variable torque model was developed. This model was able to limit the velocity magnitude and stride frequency near target values. It also showed reduction in peak shoulder forces and has better stability. One direct application of this work is to inform and potentially influence better practices involving the ancient human behavior of carrying heavy loads with bamboo poles, which remains common in some regions of Asia. The dynamic aspects of the hip actuated SLIP were synthesized with those of the beam bending model to design a compliant pole. Optimizing the design parameters of bamboo helped us to obtain a region which provided suitable reduction in peak shoulder forces within the safety limits of avoiding fracture

Controller design of a robotic orthosis using sinusoidal-input describing function model

Stroke is one of top leading causes of death in the world and it happens to more than 15 million people yearly. According to the National Stroke Association of Malaysia (NASAM), stroke is the third leading cause of death in Malaysia with around 40,000 cases reported annually. Forty percent of stroke survivors suffer from movement impairments after stroke. My grandfather was one of the victims and he was unable to attend any rehabilitation sessions due to several reasons. Hence, he lost the golden time to regain his movement and freedom. There are a lot of similar cases that happen daily in Malaysia. Besides, as the number of stroke patients increases yearly, the need for physiotherapists or rehabilitation machines equally increases. Hence, a low-cost clinical rehabilitation device is essential to provide assistance for an effective rehabilitation program and substitute the conventional method, as well as to reduce the burden of physiotherapists. In future, the proposed rehabilitation device would benefit not only stroke patients, but any patients who lost their normal walking ability including post-accident patients or those who suffer from spinal cord injury. The rehabilitation device aims to provide training assistance to patients not only in rehabilitation centres but also at home for daily training. The robotic orthosis is planned to be configured based on moving joint angles of human lower extremities. In the first stage of this research, angle-time characteristics for knee and hip swinging motion are utilised as a sagittal motion reference for the rehabilitation devices. The aim of following a proper gait cycle during rehabilitation training is to train patients to perform standing and swinging phases at proper timing and simultaneously provide the correct position reference to the patient during rehabilitation training. This can prevent patients from walking abnormally with an asymmetric gait cycle along or after the rehabilitation program. Besides, various limitations and the bulky structure of other rehabilitation devices lead to the design of the two-link lower limb rehabilitation device. This project aims to develop an assistive robotic rehabilitation device that generates a human gait trajectory for hemiplegic stroke patient gait rehabilitation in future. The shortcomings of other control applications due to environmental conditions and disturbances lead to the implementation of the describing function approach in the development of the devices. A sinusoidal-input describing function (SIDF) approach was implemented to linearize the nonlinear robotic orthosis with linear transfer function. The reason for utilising the SIDF approach is due to the nonlinear actual plant model with the present of load torque disturbances, discontinuous nonlinearities such as saturation and backlash, and also multivariable in the system. The nonlinear properties of the plant were proven in the preliminary stage of the research. A conventional controller, PID control combined with position and trajectory inputs were also applied to the system in the early stage of research. However, the experimental results were not satisfying. Finally, the SIDF approach was chosen to linearize the nonlinear system. Hence, generating a controller is much easier with a linear model of the nonlinear system. A SIDF approach was implemented to generate a controller for the multivariable, nonlinear closed loop system. Firstly, the SIDF approach enables the determination of the linear function of the nonlinear model known as the SIDF model. By utilising the linear model to mimic the behaviour of the nonlinear rehabilitation system, the controller for the nonlinear plant was able to be generated. In this research a controller based on linear control theory technique was used. The MATLAB library was used to design the lead-lag controller for the rehabilitation device. Various simulations such as step responses, tracking and decoupling of both links were performed on the generated controller with the nonlinear model to study the capability of the controller. Besides that, real life experiment testing was carried out to validate the feasibility of the controller designed via the SIDF approach. Simulation and experimental results were obtained, compared, and discussed. The highly accurate responses gained from experimental setup showed the robustness of the controller generated via SIDF approach. The implementation of the SIDF approach in a rehabilitation device (vertical two-link manipulator) is a first and hence, fulfils a novelty requirement for this research

3d model identification of a soft robotic neck

Soft robotics is becoming an emerging solution to many of the problems in robotics, such as weight, cost and human interaction. In order to overcome such problems, bio-inspired designs have introduced new actuators, links and architectures. However, the complexity of the required models for control has increased dramatically and geometrical model approaches, widely used to model rigid dynamics, are not enough to model these new hardware types. In this paper, different linear and non-linear models will be used to model a soft neck consisting of a central soft link actuated by three motor-driven tendons. By combining the force on the different tendons, the neck is able to perform a motion similar to that of a human neck. In order to simplify the modeling, first a system input¿output redefinition is proposed, considering the neck pitch and roll angles as outputs and the tendon lengths as inputs. Later, two identification strategies are selected and adapted to our case: set membership, a data-driven, nonlinear and non-parametric identification strategy which needs no input redefinition; and Recursive least-squares (RLS), a widely recognized identification technique. The first method offers the possibility of modeling complex dynamics without specific knowledge of its mathematical representation. The selection of this method was done considering its possible extension to more complex dynamics and the fact that its impact in soft robotics is yet to be studied according to the current literature. On the other hand, RLS shows the implication of using a parametric and linear identification in a nonlinear plant, and also helps to evaluate the degree of nonlinearity of the system by comparing the different performances. In addition to these methods, a neural network identification is used for comparison purposes. The obtained results validate the modeling approaches proposed.Funding: The research leading to these results has received funding from the project Desarrollo de articulaciones blandas para aplicaciones robóticas, with reference IND2020/IND-1739, funded by the Comunidad Autónoma de Madrid (CAM) (Department of Education and Research), and from RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, FaseIV; S2018/NMT-4331), funded by “Programas de Actividades I+D en la Comunidad de Madrid” and cofunded by Structural Funds of the EU

Identification and Optimal Linear Tracking Control of ODU Autonomous Surface Vehicle

Autonomous surface vehicles (ASVs) are being used for diverse applications of civilian and military importance such as: military reconnaissance, sea patrol, bathymetry, environmental monitoring, and oceanographic research. Currently, these unmanned tasks can accurately be accomplished by ASVs due to recent advancements in computing, sensing, and actuating systems. For this reason, researchers around the world have been taking interest in ASVs for the last decade. Due to the ever-changing surface of water and stochastic disturbances such as wind and tidal currents that greatly affect the path-following ability of ASVs, identification of an accurate model of inherently nonlinear and stochastic ASV system and then designing a viable control using that model for its planar motion is a challenging task. For planar motion control of ASV, the work done by researchers is mainly based on the theoretical modeling in which the nonlinear hydrodynamic terms are determined, while some work suggested the nonlinear control techniques and adhered to simulation results. Also, the majority of work is related to the mono- or twin-hull ASVs with a single rudder. The ODU-ASV used in present research is a twin-hull design having two DC trolling motors for path-following motion. A novel approach of time-domain open-loop observer Kalman filter identifications (OKID) and state-feedback optimal linear tracking control of ODU-ASV is presented, in which a linear state-space model of ODU-ASV is obtained from the measured input and output data. The accuracy of the identified model for ODU-ASV is confirmed by validation results of model output data reconstruction and benchmark residual analysis. Then, the OKID-identified model of the ODU-ASV is utilized to design the proposed controller for its planar motion such that a predefined cost function is minimized using state and control weighting matrices, which are determined by a multi-objective optimization genetic algorithm technique. The validation results of proposed controller using step inputs as well as sinusoidal and arc-like trajectories are presented to confirm the controller performance. Moreover, real-time water-trials were performed and their results confirm the validity of proposed controller in path-following motion of ODU-ASV