On reduced variance overparametrized pole assignment control

A Single-Input Single-Output (SISO) linear system can represent various physical systems. One of the challenges in controlling practical systems is that the settling point and settling time cannot be prescribed together. In this paper, a novel Self-Tuning Control (STC) algorithm is presented, which ensures system stability while allowing the simultaneous determination of the settling time and settling point. Four possible scenarios will be defined to investigate the effectiveness of the proposed control method. Three different practices will be described in the simulation section for each scenario. Linear Quadratic Regulation (LQR) will be employed for comparison purposes. MATLAB software will be used to test and simulate these practices. The simulations will demonstrate that the STC is an optimal solution for SISO linear systems, comparable to LQR, with the significant advantage of guaranteeing the attainment of the settling point at the predefined settling time.

ABSTRACTThe main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.

This paper uses a linear quadratic Gaussian regulator with loop transfer recovery (LQG/LTR) to control the speed demand of a nuclear steam generator. The controller is simulated. Its performance and stability robustness are analyzed. The simulation results are presented and discussed in the paper.

For a single-output linear time-invariant system, output controllability is shown to be a necessary and sufficient condition for the existence of linear state variable feedback that freely assigns the eigenvalues of the closed-loop system that are observable from the output. An application of this result to the single-output linear servomechanism shows that the ability of such a system to track with zero steady-state error and an arbitrary transient response is equivalent to output controllability of the plant, and is independent of the class of command signals and disturbances.

A Self-Tuning Control Algorithm in the Presence of Plant-Model Order Mismatch

The ability to compensate for disturbances resulting from nonlinear phenomena such as Coulomb friction in inertial stabilization systems has been demonstrated to be feasible when the plant dynamics of the system are accurately modeled. However, for cases where the plant is unknown or changing, a self-tuning control algorithm is desired to provide robustness. This paper formulates such a self-tuning control algorithm with specific application to systems with inherent nonlinearities. The ability of the algorithm to self-tune and compensate for nonlinear induced disturbances is demonstrated for an inertial stabilization gimbal control system with Coulomb type bearing friction.

X-ray pulsar-based GNC system for formation flying in high Earth orbits

DESIGN AND CONTROL OF A THERMAL STABILIZING SYSTEM FOR AN OPTOMECHANICAL UNCOOLED INFRARED IMAGING CAMERA

This study investigates the linear quadratic Gaussian state regulation problem over a packet‐dropping network. A linear predictive compensation scheme is proposed to counteract the uncontrollable packet loss. To characterise the operating state of the system, differently from the widely used Markov jump linear systems theory or multi‐mode Markov chain, in this study the actual control command executed to the plant is expressed as a stochastic sequence. Moreover, the original information set is divided into several subsets, which benefits to establish the quantitative relationship between the infinite‐horizon quadratic performance index and the prediction horizon. A numerical example is provided to show that there exists an optimal prediction horizon to minimise the performance index.

This work addresses the output feedback stabilisation problem for a class of linear single-input single-output systems subject to I/O network delays. More precisely, we are interested in the characterisation of the set of delay and gain parameters guaranteeing the stability of the closed-loop system. To perform such an analysis, we adopt an eigenvalue perturbation based approach. Various illustrative numerical examples complete the presentation.

The Nyquist stability criterion and the notion of type n systems have been extended from lumped parameter systems to a larger class of linear single-loop single-input single-output time-invariant systems, with constraints presented in the text.

On optimality of the impulse input for linear system identification

The design of a multi-level fuzzy-logic control system for the control of turbine engines using type-1 fuzzy-logic is presented in this paper. A Matlab-Simulink model of an advanced turbine engine was used to test and validate the performance of the developed fuzzy control system. The model provided comprehensive and complex model of a turbine engine. As with most modeling of turbine engines, it was assumed that the fundamental dynamic characteristics of a turbine engine can be achieved by control of the engine fuel flow. In this model a single input single output (SISO) system is used to control the engine fuel flow, where the input to the SISO system is the low spool speed error signal and the output is the fuel flow actuator control signal. A fuzzy controller was developed for the SISO system and its performance is compared with that of the existing proportional integral (PI) controller. Both controllers were tested under normal operating conditions and with introduction of engine faults embedded in the model.

The demand for ubiquitous telecommunications services forces operators to have a special concern about signal quality and the coverage area they offer to their customers. This was usually checked by using suitable propagation models for Single Input Single Output (SISO) systems, which are no longer the case for new and future mobile generations, such as 5G and beyond. To guarantee good signal quality coverage, operators started to replace these models with Multiple Input Multiple Output (MIMO) ones. To achieve the best results, these models are usually calibrated with Drive Test (DT) measures; however, the DTs available for MIMO propagation models are sparse, in contrast to SISO ones. The main contribution presented in this paper is a methodology to extend the propagation models of SISO systems so they can be applied in MIMO sytems with Single-Carrier and Frequency-Domain Equalization (SC-FDE), while still using DTs acquired for SISO systems. This paper presents the impact on Bit Error Rate (BER) performance and its coverage area resulting from the application of our proposed method. We consider a MIMO SC-FDE system with an Iterative Block Decision Feedback Equalization (IB-DFE) receiver and we present the improvement expressions for the BER that we illustrate with some simulations.

It is shown in this paper that any state space realization (A, b, c) of a given transfer function T(s) = β(s/α(s with α(s) monic and dim(A) = deg(α(s)), satisfies the identity β(A) = Qc(A, b)SαQo(A, c) where Qc(A, b) and Qo(A, c) are the controllability matrix and observability matrix of the matrix triple (A, b, c), respectively, and Sα is a nonsingular symmetric matrix. Such an identity gives a deep relationship between the state space description and the transfer function description of single-input single-output (SISO) linear systems. As a direct conclusion, we arrive at the well-known result that a realization of any transfer function is minimal if and only if the numerator and the denominator of the transfer function is coprime. Such a result is also extended to the SISO descriptor linear system case. As an applications, a complete solution to the commuting matrix equation AX = XA is proposed and the minimal realization of multi-input multi-output (MIMO) linear system is considered.