Kenneth R. Muske’s research while affiliated with Villanova University and other places

This paper presents an optimal sliding mode cascade control for stabilization of a class of underactuated nonlinear mechanical systems. A discrete-time, nonlinear model predictive control structure is used to optimally select and update the parameters of the sliding mode control surfaces at specified intervals in order to achieve a desired performance objective. The determination of these surface parameters is subject to constraints that arise from the stability conditions imposed by the sliding mode control law and the physical limits on the system such as input saturation. Nominal stability of the optimal cascade control structure is demonstrated and its robust performance is illustrated using an experimental rotary inverted pendulum system.

A new method for real-time obstacle avoidance and trajectory planning of underactuated unmanned surface vessels is presented. In this method, ordinary differential equations (ODEs) are used to define transitional trajectories that can avoid obstacles and reach a final desired target trajectory using a robust tracking control law. The obstacles are approximated and enclosed by elliptical shapes. A transitional trajectory is then defined by a set of ordinary differential equations whose solution is a stable elliptical limit cycle defining the nearest obstacle on the vessel's path to the target. When no obstacle blocks the vessel's path to its target, the transitional trajectory is defined by exponentially stable ODE whose solution is the target trajectory. The planned trajectories are tracked by the vessel through a sliding mode control law that is robust to environmental disturbances and modeling uncertainties and can be computed in real time. The method is illustrated using a complex simulation example with a moving target and multiple moving and rotating obstacles and a simpler experimental example with stationary obstacles.

An analytical stability analysis of the steady trajectory for a surface vessel with various damping models is presented in this work. The analysis is based on a control-oriented, three degrees-of-freedom model that considers vessel motion only in the horizontal plane. The goal of this study is to understand the vessel trajectories predicted by this reduced order model for model-based control design. Straight line and circular motion stability conditions for each trajectory are derived and presented for the various damping models. The results of this analysis show that either a straight line or a circular steady trajectory is possible, depending on the magnitude of the surge force and the form of the damping model used to represent viscous drag, vortex shedding, and losses due to the surface wake generated by the vessel motion. However, the straight line motion is much less likely for the vessel considered in this work. [DOI: 10.1115/1.4002976]

This paper considers the efficacy of disturbance models for ensuring offset-free control and the determination of the optimum feasible steady-state target within linear model predictive control (MPC). Previously proposed methods for steady-state target determination can address model error, disturbances, and output target changes when the desired steady state is feasible, but may fail to achieve a feasible target that is as close as possible to the desired steady-state target when the desired target is unreachable due to active constraints. Under certain conditions, the resulting ‘feasible steady-state target’ can converge to a point that is not as close as possible to the optimal feasible target. By considering the Karush–Kuhn–Tucker (KKT) conditions of optimality for the steady-state target optimizer, sufficient multi-variable conditions are established for which convergence to the optimal feasible target is guaranteed and, conversely, when convergence to a sub-optimal feasible target is expected.

Waste glycerol is a byproduct from biodiesel production and its generation increases year after year. This study investigates the possibility of anaerobic digestion of glycerol waste, which can result in beneficial energy recovery, methane. Glycerol wastes from different biodiesel production processes including acidic and basic condition were tested and their results were compared with methane production from pure glycerol for any adverse impacts. The test has been done in bench scale serum bottle reactors with a total volume of 165mL. The results show that all tested concentrations recovered roughly 80% of theoretical methane production based on COD (Chemical Oxygen Demand) measurement and the sources of glycerol waste did not play an important role in overall results. After the completion of anaerobic digestion study, mathematical models were developed to predict a performance of anaerobic digestion of glycerol waste in a batch reactor. Even though the predictive models developed in the research may be valid only in the studied condition, the mathematical models may be able to yield predictive models for continuous reactors as well.

A sliding mode control law is presented and experimentally implemented for setpoint control of an underactuated autonomous surface vessel. The control law is developed by defining a single sliding surface for orientation stabilization that determines the required yaw moment and three additional surfaces that determine the surge force. The trajectories are shown to converge to each of the surfaces in finite time and the sliding phase is shown to be asymptotically stable. Two setpoint control scenarios are simulated and then demonstrated experimentally. The experimental results show that the surface vessel converges to the desired setpoint with reasonable accuracy.

A novel method for coordinated trajectory planning and real-time obstacle avoidance of autonomous systems is presented. The desired autonomous system trajectories are generated from a set of first order ODEs. The solution to this system of ODEs converges to either a desired target position or a closed orbit defined by a limit cycle. Coordinated control is achieved by utilizing the nature of limit cycles where independent, non-crossing paths are automatically generated from different initial positions that smoothly converge to the desired closed orbits. Real-time obstacle avoidance is achieved by specifying a transitional elliptically shaped closed orbit around the nearest obstacle blocking the path. This orbit determines an alternate trajectory that avoids the obstacle. When the obstacle no longer blocks a direct path to the original target trajectory, a transitional trajectory that returns to the original path is defined. The coordination and obstacle avoidance methods are demonstrated experimentally using differential-drive wheeled mobile robots.

In this paper, we implement the recently developed energy- and entropy-based hybrid control framework for stabilization of Lagrangian systems on the experimental testbed of the Rotational/Translational Proof-Mass Actuator (RTAC) system. In addition, on the same experimental platform, we implement the sliding mode control framework for stabilization of underactuated dynamical systems and compare the performances of all three controllers. The concept of an energy-based hybrid controller involves a hybrid controller that exploits the feature that the states of the dynamic controller may be reset to enhance the overall energy dissipation in the closed-loop system. We give a detailed description of the hardware layout for the testbed and present the experimental results. The real-time data indicate that the energy- and entropy-based hybrid controllers result in almost the same closed-loop system behavior with the same control effort. However, hybrid controllers use significantly less control effort and stabilize the system in a shorter period of time than the sliding mode controller.

In this study we explored the use of liquid and supercritical carbon dioxide for the creation of a sustained release drug delivery device. An anti-inflammatory (ketoprofen) was dissolved into carbon dioxide at various temperatures (25−55 °C) and pressures (65−300 bar) and then exposed to biodegradable braided sutures made of poly(lactide-co-glycolide) copolymers. The effect of temperature, pressure (and hence density), and exposure time were explored on the ability of the sutures to absorb ketoprofen. The diffusion of the drug into the suture was modeled, and diffusion coefficients were calculated. The amount of ketoprofen loaded into the suture increased with pressure and density and decreased with temperature; however, increasing temperature tended to speed up the absorption process.

In this paper, an analysis of knock signals suggests that the knock intensity is a cyclically uncorrelated random process, and that it is therefore not possible to control individual cycles to a specified knock intensity in a deterministic manner. A new knock control algorithm is therefore developed on the basis of a stochastic interpretation of the knock signal, and on the basis of a control objective specified as a certain percentage of knocking cycles. Unlike traditional controllers, the new algorithm does not respond to knock events provided that these are occurring within a specified tolerance of the target knock rate. The new controller uses the cumulative summation of knock events to make this determination, thereby avoiding the slow transient response times sometimes associated with 'stochastic' knock controllers. When a spark adjustment is deemed necessary, the magnitude of the control action is scaled according to the likelihood ratio of the observed events since the last spark adjustment was made. A theoretical analysis of the new controller is presented and a simulation tool which is closely based on experimental data is used to assess its performance. The results show that the new controller is able to achieve the same target knock rate as a traditional controller while operating at a more advanced mean spark angle. There is also less cyclic variance about this mean and the regulatory response is significantly improved. The transient response to overly advanced or retarded conditions is similar to the traditional controller. These results suggest that the new controller will deliver increased torque and engine efficiency under knock-limited conditions without increasing the risk of engine damage.