Desired Closed Loop Behavior Research Articles

Linear Algebra Controller Design Based on the Integral of Desired Closed-Loop Behavior: Application to Regulation and Trajectory Tracking in a Typical Chemical Process

This work presents a novel control technique that combines linear algebra-based controller (LABC) methodology with sliding surface concepts. An LABC is developed from a first-order plus dead time model of the process, which is improved to work under uncertainties by the use of sliding surface concepts. Two different strategies are proposed to reject constant and variable uncertainties. The result is two linear controllers, which are tuned using four parameters at most. Results of the control of two level tanks connected in series, a mixing tank with variable dead time, and a laboratory batch reactor using this novel technique are presented, including experimental and simulated results. The efficiency of the proposed controller is tested under nominal operating conditions and under parametric uncertainty and persistent process disturbances. Proof of convergence to zero of tracking errors is analyzed and included in this article.

Event-triggered reset trajectory tracking control for unmanned surface vessel system

This article considers the trajectory tracking control for unmanned surface vessels with unknown time-variant external disturbances and input saturation. The strategy mainly consists of event-triggered reset sub-controller and nonlinear disturbance observer–based compensation sub-controller. To reduce network transmissions, and in the meanwhile, guarantee the desirable closed-loop behavior, the event-triggered reset control is proposed where the reset law and the event-triggered mechanism are designed separately. Both of static and dynamic event-triggered reset controllers are designed. Their corresponding stability is demonstrated using Lyapunov stability theory. Finally, numerical simulation results are presented to demonstrate the effectiveness and robustness of the proposed trajectory tracking control strategy.

Combining Homogeneous High Order Sliding Mode and Nonlinear Dynamic Inversion for fixed wing aircraft attitude and speed control

Abstract This paper addresses the problem of robust flight control for fixed wing aircrafts. Such systems are generally of Multi-Input Multi-Output (MIMO) form, tightly coupled and highly nonlinear whereby the nonlinearity resides both in the dynamic equations and in the aerodynamic coefficients. Consequently, we propose to combine Homogeneous High Order Sliding Mode (HHOSM) and Nonlinear Dynamic Inversion (NDI) approaches in order to deal with the piloting controller. The overall controller is designed so as to ensure the tracking of desired longitudinal velocity and attitude angles. The dynamics inversion uses nonlinear full-state feedback to globally linearize the dynamics of the selected controlled variables so that a linear controller can then be applied to regulate these variables with a desirable closed-loop behavior. To handle the nonlinearity, the desired closed-loop dynamics are given by an HHOSM controller. Simulations are carried out on a real-time virtual simulation platform for the development of Aircraft Control Systems (ACS). The obtained results demonstrate the effectiveness of the proposed controller. It is shown that HHOSM-NDI autopilot delivers a high dynamic tracking performance and can alleviate the chattering effect. Moreover, finite time convergence to the origin is ensured.

Self-triggered linear quadratic control

Self-triggered control is a recently proposed paradigm that abandons the more traditional periodic time-triggered execution of control tasks with the objective of reducing the utilization of communication resources, while still guaranteeing desirable closed-loop behavior. In this paper, we introduce a self-triggered strategy based on performance levels described by a quadratic discounted cost. The classical LQR problem can be recovered as an important special case of the proposed self-triggered strategy. The self-triggered strategy proposed in this paper possesses three important features. Firstly, the control laws and triggering mechanisms are synthesized so that a priori chosen performance levels are guaranteed by design. Secondly, they realize significant reductions in the usage of communication resources. Thirdly, we address the co-design problem of jointly designing the feedback law and the triggering condition. By means of a numerical example, we show the effectiveness of the presented strategy. In particular, for the self-triggered LQR strategy, we show quantitatively that the proposed scheme can outperform conventional periodic time-triggered solutions.

Interactive Medical Image Segmentation Using PDE Control of Active Contours

Segmentation of injured or unusual anatomic structures in medical imagery is a problem that has continued to elude fully automated solutions. In this paper, the goal of easy-to-use and consistent interactive segmentation is transformed into a control synthesis problem. A nominal level set PDE is assumed to be given; this open-loop system achieves correct segmentation under ideal conditions, but does not agree with a human expert's ideal boundary for real image data. Perturbing the state and dynamics of a level set PDE via the accumulated user input and an observer-like system leads to desirable closed-loop behavior. The input structure is designed such that a user can stabilize the boundary in some desired state without needing to understand any mathematical parameters. Effectiveness of the technique is illustrated with applications to the challenging segmentations of a patellar tendon in MR and a shattered femur in CT.

Admissible Pole Locations for Tracking Random References

Admissible pole locations for tracking step inputs are well known and widely used for designing tracking controllers. In some applications, however, references are random signals rather than steps. What are admissible pole locations for tracking such references? This is the question addressed in this note. Specifically, a method for constructing admissible domains, which lead to the desired closed loop behavior, is developed and illustrated by a hard disk drive controller design.

Design of Multivariable Controllers by Direct Synthesis: Theory and Experimental Implementation

A technique for designing truly multivariable controllers by direct synthesis is presented for multivariable processes with and without time delays. The technique generalizes the SISO direct synthesis method in which feedback controllers are designed to achieve a pre-specified desired closed loop behavior. As with the SISO counterpart, the multivariable and time delay extensions are shown to take on the form of truly multivariable versions of the popular conventional PID feedback controllers for certain choices of the desired closed loop behavior. The procedure is illustrated via simulation and on an experimental laboratory scale mixing tank, where the performance is shown, as expected, to be far superior to that obtained with multiloop controllers.

A model reference & sensitivity model-based self-learning fuzzy logic controller as a solution for control of nonlinear servo systems

In this paper, the design, simulation and experimental verification of a self-learning fuzzy logic controller (SLFLC) suitable for the control of nonlinear servo systems are described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been tested in the position control loops of two chopper-fed DC servo systems, first by simulation in the presence of a backlash nonlinearity, then by experiment in the presence of a gravity-dependent shaft load and fairly high static friction. The simulation and experimental results have proved that the SLFLC provides desired closed loop behavior and eliminates a steady-state position error.