Development of a finite-difference neighboring optimal control law and application to the optimal landing of a reusable launch vehicle

A new neighboring optimal control methodology is developed and applied to the fuel-optimal landing of a reusable launch vehicle. Two new methods, both based on perturbation analysis, are explored. A fast open-loop optimal trajectory solver is developed to handle the numerically intensive perturbation analysis phase of control law synthesis. High accuracy closed-loop simulation of both the optimal control law and plant model shows that the optimal control law is robust for a number of different off-nominal conditions

Nonlinear position and stiffness Backstepping controller for a two Degrees of Freedom pneumatic robot

This paper presents an architecture of a 2 Degrees of Freedom pneumatic robot which can be used as a haptic interface. To improve the haptic rendering of this device, a nonlinear position and stiffness controller without force measurement based on a Backstepping synthesis is presented. Thus, the robot can follow a targeted trajectory in Cartesian position with a variable compliant behavior when disturbance forces are applied. An appropriate tuning methodology of the closed-loop stiffness and closed-loop damping of the robot is given to obtain a desired disturbance response. The models, the synthesis and the stability analysis of this controller are described in this paper. Two models are presented in this paper, the first one is an accurate simulation model which describes the mechanical behavior of the robot, the thermodynamics phenomena in the pneumatic actuators, and the servovalves characteristics. The second model is the model used to synthesize the controller. This control model is obtained by simplifying the simulation model to obtain a MIMO strict feedback form. Finally, some simulation and experimental results are given and the controller performances are discussed and compared with a classical linear impedance controller

Optimization of DC - DC boost converter using fuzzy logic controller

DC-DC converters are electronic devices used to change DC electrical power efficiently from one voltage level to another. Operation of the switching devices causes the inherently nonlinear characteristic of the DC-DC converters including one known as the Boost converter. Consequently, this converter requires a controller with a high degree of dynamic response. Proportional-Integral- Differential (PID) controllers have been usually applied to the converters because of their simplicity. However, the main drawback of PID controller is unable to adapt and approach the best performance when applied to nonlinear system. It will sufer from dynamic response, produces overshoot, longer rise time and settling time which in turn will influenced the output voltage regulation of the Boost converter. Therefore, the implementation of practical Fuzzy Logic controller that will deal to the issue must be investigated. Fuzzy logic controller using voltage output as feedback for significantly improving the dynamic performance of boost dc-dc converter by using MATLAB@Simulink software. The design and calculation of the components especially for the inductor has been done to ensure the converter operates in continuous conduction mode. The evaluation of the output has been carried out and compared by software simulation using MATLAB software between the open loop and closed loop circuit between fuzzy logic control (FLC) and PID control. The simulation results are shown that voltage output is able to be control in steady state condition for DC-DC boost converter by using this methodology. Scope of this project limited only one types that is Triangle membership function for fuzzy logic control

Design and analysis of ripple-based controls based on the discrete modeling and Floquet theory

Ripple-based controls can strongly reduce the required output capacitance in PowerSoC converter thanks to a very fast dynamic response. Unfortunately, these controls are prone to sub-harmonic oscillations and several parameters affect the stability of these systems. This paper derives and validates a simulation-based modeling and stability analysis of a closed-loop V 2Ic control applied to a 5 MHz Buck converter using discrete modeling and Floquet theory to predict stability. This allows the derivation of sensitivity analysis to design robust systems. The work is extended to different V 2 architectures using the same methodology

Passive dynamic controllers for nonlinear mechanical systems

A methodology for model-independant controller design for controlling large angular motion of multi-body dynamic systems is outlined. The controlled system may consist of rigid and flexible components that undergo large rigid body motion and small elastic deformations. Control forces/torques are applied to drive the system and at the same time suppress the vibration due to flexibility of the components. The proposed controller consists of passive second-order systems which may be designed with little knowledge of the system parameter, even if the controlled system is nonlinear. Under rather general assumptions, the passive design assures that the closed loop system has guaranteed stability properties. Unlike positive real controller design, stabilization can be accomplished without direct velocity feedback. In addition, the second-order passive design allows dynamic feedback controllers with considerable freedom to tune for desired system response, and to avoid actuator saturation. After developing the basic mathematical formulation of the design methodology, simulation results are presented to illustrate the proposed approach to a flexible six-degree-of-freedom manipulator

An application of the individual channel analysis and design approach to control of a two-input two-output coupled-tanks system

Frequency-domain methods have provided an established approach to the analysis and design of single-loop feedback control systems in many application areas for many years. Individual Channel Analysis and Design (ICAD) is a more recent development that allows neo-classical frequency-domain analysis and design methods to be applied to multi-input multi-output control problems. This paper provides a case study illustrating the use of the ICAD methodology for an application involving liquid-level control for a system based on two coupled tanks. The complete nonlinear dynamic model of the plant is presented for a case involving two input flows of liquid and two output variables, which are the depths of liquid in the two tanks. Linear continuous proportional plus integral controllers are designed on the basis of linearised plant models to meet a given set of performance specifications for this two-input two-output multivariable control system and a computer simulation of the nonlinear model and the controllers is then used to demonstrate that the overall closed-loop performance meets the given requirements. The resulting system has been implemented in hardware and the paper includes experimental results which demonstrate good agreement with simulation predictions. The performance is satisfactory in terms of steady-state behaviour, transient responses, interaction between the controlled variables, disturbance rejection and robustness to changes within the plant. Further simulation results, some of which involve investigations that could not be carried out in a readily repeatable fashion by experimental testing, give support to the conclusion that this neo-classical ICAD framework can provide additional insight within the analysis and design processes for multi-input multi-output feedback control systems

Reasoning About Liquids via Closed-Loop Simulation

Simulators are powerful tools for reasoning about a robot's interactions with its environment. However, when simulations diverge from reality, that reasoning becomes less useful. In this paper, we show how to close the loop between liquid simulation and real-time perception. We use observations of liquids to correct errors when tracking the liquid's state in a simulator. Our results show that closed-loop simulation is an effective way to prevent large divergence between the simulated and real liquid states. As a direct consequence of this, our method can enable reasoning about liquids that would otherwise be infeasible due to large divergences, such as reasoning about occluded liquid.Comment: Robotics: Science & Systems (RSS), July 12-16, 2017. Cambridge, MA, US