Sparse and Constrained Stochastic Predictive Control for Networked Systems

This article presents a novel class of control policies for networked control of Lyapunov-stable linear systems with bounded inputs. The control channel is assumed to have i.i.d. Bernoulli packet dropouts and the system is assumed to be affected by additive stochastic noise. Our proposed class of policies is affine in the past dropouts and saturated values of the past disturbances. We further consider a regularization term in a quadratic performance index to promote sparsity in control. We demonstrate how to augment the underlying optimization problem with a constant negative drift constraint to ensure mean-square boundedness of the closed-loop states, yielding a convex quadratic program to be solved periodically online. The states of the closed-loop plant under the receding horizon implementation of the proposed class of policies are mean square bounded for any positive bound on the control and any non-zero probability of successful transmission

Robust nonlinear control of vectored thrust aircraft

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations

Application of MPC and sliding mode control to IFAC benchmark models

The comparison of Model Predictive Control (MPC) and Sliding Mode Control (SMC) are presented in this paper. This paper investigates the performance of each controller as the navigation system for IFAC benchmark ship models (cargo vessel and oil tanker). In this investigation the navigation system regulates the heading angle of the two types of marine vessel with reference to a desired heading trajectory. In this investigation, the result obtained from MPC is compared with a well-established control methodology, namely Sliding Mode control theory. Wave disturbances and actuator limits are implemented to provide a more realistic evaluation and comparison for the proposed control structure

Model based control strategies for a class of nonlinear mechanical sub-systems

This paper presents a comparison between various control strategies for a class of mechanical actuators common in heavy-duty industry. Typical actuator components are hydraulic or pneumatic elements with static non-linearities, which are commonly referred to as Hammerstein systems. Such static non-linearities may vary in time as a function of the load and hence classical inverse-model based control strategies may deliver sub-optimal performance. This paper investigates the ability of advanced model based control strategies to satisfy a tolerance interval for position error values, overshoot and settling time specifications. Due to the presence of static non-linearity requiring changing direction of movement, control effort is also evaluated in terms of zero crossing frequency (up-down or left-right movement). Simulation and experimental data from a lab setup suggest that sliding mode control is able to improve global performance parameters

Integrated fault-tolerant control for a 3-DOF helicopter with actuator faults and saturation

© The Institution of Engineering and Technology 2017. This study proposes a fault estimation (FE)-based fault-tolerant control (FTC) strategy to maintain system reliability and achieve desirable control performance for a 3-DOF helicopter system with both actuator drift and oscillation faults and saturation. The effects of the faults and saturation are combined into a composite non-differentiable actuator fault function, which is approximated by a differentiable function and estimated together with the system state using a non-linear unknown input observer. An adaptive sliding mode controller based on the estimates is developed to compensate the effects of the faults and saturation. Taking into account the bi-directional robustness interactions between the FE and FTC functions, an integrated design approach is proposed to obtain the observer and controller gains in a single step, so as to achieve robust overall FTC system performance. In fault-free cases, the proposed strategy can be considered as a new approach for anti-windup control to compensate the effect of input saturation. Comparative simulations are provided to verify the effectiveness of the proposed design under different actuator fault scenarios