Adaptive, suboptimal and nonlinear control of an aeroelastic system

In this thesis, control systems are designed for the flutter control of a nonlinear aeroelastic system. The aeroelastic model describes the plunge and pitch motion of a wing. The model includes plunge and pitch nonlinearties, and has a single control surface for the purpose of control. First an output feedback modular adaptive control system is derived. Quasi-steady aerodynamic model is used for the output feedback modular adaptive control system. For the synthesis of the adaptive controller, it is assumed that only pitch angle and plunge displacement are measured. The control system consists of an input-to-state stabilizing controller and a passive identifier. The passive identifier provides estimates of parameters for synthesis. The second control system is based on the state dependent Riccati equation method. This design yields a suboptimal control law. Finally a nonlinear controller based on backstepping design is presented. Unsteady aerodynamic model is used for the design of the suboptimal controller using state dependent Riccati equation approach and nonlinear controller using backstepping design technique. The unsteady aerodynamic is modeled with an approximation to Theodorsens theory. For the synthesis of second and third control systems, an observer is designed for estimating the unavailable states variables. Simulation results for each controller are presented. These results show that the designed control systems are effective in flutter suppression

Converse passivity theorems

Passivity is an imperative concept and a widely utilized tool in the analysis and control of interconnected systems. It originates from the mathematical modelling of physical systems, including network synthesis and mechanical systems. It has also proved to be a key notion in adaptive and robust control. While many theorems on passivity are known in systems and control theory their converse statements have received much less attention. This paper establishes various versions of converse passivity theorems for nonlinear feedback systems. In particular, open-loop passivity is shown to be necessary to ensure closed-loop passivity from an input-output perspective. Moreover, the stability of the feedback interconnection of a specific system with an arbitrary passive system is shown to imply passivity of the system itself

Nonlinear control and its application to active tilting-pad bearings

The drawbacks of active magnetic bearings are arousing interest in the adaptation of mechanical bearings for active use. A promising mechanical bearing candidate for active operation is the tilting-pad bearing. In this research, we introduce an active tilting-pad bearing with linear actuators that translate each pad. The use of feedback in determining the actuator forces allows for the automatic, continuous adjustment of the pad position during the machine operation. In this work, we develop the dynamic model of the active bearing system such that the actuator forces are the control inputs. The hydrodynamic force is modeled as a spring/damper-like force with unknown damping and stiffness coefficients. Whereas in the literature, the damping and stiffness effects are normally considered linear, here, motivated by a numerical study based on the Reynolds equation, we use a nonlinear model for the stiffness force. An adaptive controller is designed to asymptotically regulate the rotor to the bearing center. The proposed control design is applicable to both the linear and nonlinear stiffness models. Simulations and experiments show that the active strategy improves the bearing performance in comparison to its traditional passive operation. Further, the experiments indicate the nonlinear stiffness-based controller slightly improves the active bearing regulation performance relative to the linear-based one. To the best of our knowledge, this dissertation is the first to report the experimental demonstration of an active tilting-pad bearing using feedback control. Since the model of the active tilting-pad bearing has a parametric strict-feedback-like form, the second part of this dissertation is dedicated to constructing new nonlinear control tools for this class of systems. Specifically, we consider the regulation and tracking control problems for multi-input/multi-output parametric strict-feedback systems in the presence of additive, exogenous disturbances and parametric uncertainties. For such systems, robust adaptive controllers usually cannot ensure asymptotic tracking or even regulation. In this work, under the assumption the disturbances are C2 with bounded time derivatives; we present a new C0 robust adaptive control construction that guarantees the output/tracking error is asymptotically driven to zero. Numerical examples illustrate the main results, including cases where the disturbances do not satisfy the aforementioned assumptions

Nonlinear Model-Based Control for Neuromuscular Electrical Stimulation

Neuromuscular electrical stimulation (NMES) is a technology where skeletal muscles are externally stimulated by electrodes to help restore functionality to human limbs with motor neuron disorder. This dissertation is concerned with the model-based feedback control of the NMES quadriceps muscle group-knee joint dynamics. A class of nonlinear controllers is presented based on various levels of model structures and uncertainties. The two main control techniques used throughout this work are backstepping control and Lyapunov stability theory. In the first control strategy, we design a model-based nonlinear control law for the system with the exactly known passive mechanical that ensures asymptotical tracking. This first design is used as a stepping stone for the other control strategies in which we consider that uncertainties exist. In the next four control strategies, techniques for adaptive control of nonlinearly parameterized systems are applied to handle the unknown physical constant parameters that appear nonlinearly in the model. By exploiting the Lipschitzian nature or the concavity/convexity of the nonlinearly parameterized functions in the model, we design two adaptive controllers and two robust adaptive controllers that ensure practical tracking. The next set of controllers are based on a NMES model that includes the uncertain muscle contractile mechanics. In this case, neural network-based controllers are designed to deal with this uncertainty. We consider here voltage inputs without and with saturation. For the latter, the Nussbaum gain is applied to handle the input saturation. The last two control strategies are based on a more refined NMES model that accounts for the muscle activation dynamics. The main challenge here is that the activation state is unmeasurable. In the first design, we design a model-based observer that directly estimates the unmeasured state for a certain activation model. The second design introduces a nonlinear filter with an adaptive control law to handle parametric uncertainty in the activation dynamics. Both the observer- and filter-based, partial-state feedback controllers ensure asymptotical tracking. Throughout this dissertation, the performance of the proposed control schemes are illustrated via computer simulations

A family of asymptotically stable control laws for flexible robots based on a passivity approach

A general family of asymptotically stabilizing control laws is introduced for a class of nonlinear Hamiltonian systems. The inherent passivity property of this class of systems and the Passivity Theorem are used to show the closed-loop input/output stability which is then related to the internal state space stability through the stabilizability and detectability condition. Applications of these results include fully actuated robots, flexible joint robots, and robots with link flexibility

Output consensus of nonlinear multi-agent systems with unknown control directions

In this paper, we consider an output consensus problem for a general class of nonlinear multi-agent systems without a prior knowledge of the agents' control directions. Two distributed Nussbaumtype control laws are proposed to solve the leaderless and leader-following adaptive consensus for heterogeneous multiple agents. Examples and simulations are given to verify their effectivenessComment: 10 pages;2 figure

A passivity approach to controller-observer design for robots

Passivity-based control methods for robots, which achieve the control objective by reshaping the robot system's natural energy via state feedback, have, from a practical point of view, some very attractive properties. However, the poor quality of velocity measurements may significantly deteriorate the control performance of these methods. In this paper the authors propose a design strategy that utilizes the passivity concept in order to develop combined controller-observer systems for robot motion control using position measurements only. To this end, first a desired energy function for the closed-loop system is introduced, and next the controller-observer combination is constructed such that the closed-loop system matches this energy function, whereas damping is included in the controller- observer system to assure asymptotic stability of the closed-loop system. A key point in this design strategy is a fine tuning of the controller and observer structure to each other, which provides solutions to the output-feedback robot control problem that are conceptually simple and easily implementable in industrial robot applications. Experimental tests on a two-DOF manipulator system illustrate that the proposed controller-observer systems enable the achievement of higher performance levels compared to the frequently used practice of numerical position differentiation for obtaining a velocity estimat