State Feedback Research Articles

Finite-time bounded security control of networked switched stochastic systems

This paper is dedicated to discussing stochastic finite-time bounded control of switched stochastic systems with feedback information sampled by an event-triggered mechanism and transmitted by network. Besides the incomplete information because of sample, data loss and corruption during information transmission caused by hybrid cyber attacks including DoS attacks and false-data injection attacks, are also taken into consideration. Based on the above incomplete information, state feedback controllers are established to fulfil stochastic finite-time boundedness of switched stochastic systems and make it have a certain disturbance attenuation capability, i.e. have a finite-time L 2 -gain, successfully. Sufficient conditions are cast into a convex optimisation problem which can be easily solved by fixing some parameters. Simulation results are employed to verify the validity of results.

Probability‐Based Finite‐Time Security Control for Switched Stochastic Systems via a Novel Event‐Triggered Mechanism and Its Application

ABSTRACTThis article discusses the finite‐time boundedness (FTB) issue and ‐gain analysis for switched stochastic systems, particularly under the dual influence of DoS attacks and false data injection attacks, by employing a novel event‐triggered mechanism. Different from the moment calculation method, a probability‐based FTB is studied which offers more pertinence. To obtain a less conservative condition of FTB, a switched Lyapunov function is constructed. Additionally, a memory‐based dynamic event‐triggered mechanism is designed to reduce the amounts of triggering and mitigate the state response fluctuations. Based on the incomplete information above, state feedback controllers are devised to satisfy stochastic FTB, ensuring the successful attainment of finite‐time ‐gain. Sufficient conditions are cast into a convex optimization problem by LMIs which can be solved easily. Finally, a compared numerical example and an RLC series circuit are adopted to demonstrate the availability of the theoretical results.

Semi-active vibration control via a magnetorheological damper and active disturbance rejection control

This work provides an alternative for the semi-active vibration control problem via state feedback plus an active disturbance rejection control (K-ADRC) for a multistory building structure equipped with one magnetorheological damper (MRD) located between the ground and the first story. This control law introduces a disturbance observer (DOB) to estimate the total disturbance in real time, produced by the earthquake perturbation, unmodeled dynamics, and parametric uncertainties, and then cancel their effect using a part of the control signal. Moreover, using a diffeomorphism, the K-ADRC provides a proportional derivative (PD) controller designed to improve internal stability. A prominent feature of the active disturbance rejection control (ADRC) algorithm is that the value of the DOB gain is selected according to the system bandwidth. The stability of the system is verified via Lyapunov analysis. Moreover, the building structure model and the MRD are accomplished by incorporating a nonlinearity state that represents the hysteresis effect to perform real behavior in addition to assuming that acceleration is the only available measurement of building structures. Thus, integral filters are provided based on the appropriate cut-off frequency to estimate displacement and velocity, avoiding bias, offset, and phase shifts. Experimental results from a reduced-scale two-story building prototype demonstrate that the proposed K-ADRC is promising for real applications, and it has better performance than the state feedback (K) and the linear quadratic regulator (LQR) control techniques.

Real‐Time Implementation of Unknown Input Observer‐Based State and Unknown Disturbance Estimation for Series Active Filters

ABSTRACTSeries active filter (SAF) is generally utilized in compensating harmonic voltage source‐type loads. In this paper, a combined action of controller and observer is proposed for SAF. Full state feedback (SFB) and linear quadratic regulator (LQR) controllers are posited in order to estimate states, and fault. SFB utilizes the pole placement method, whereas LQR utilizes the tuning of matrices by Bryson's rule. Luenberger observer (LO), proportional–integral observer (PIO), and unknown input observer (UIO) were also designed. The efficacy of this scheme is illustrated through the simulations, in the presence of faults. The state dynamics of SFB‐ and LQR‐based control of SAF with LO, PIO, and UIO in different faulty cases are compared. It can be clearly seen through simulations that the state dynamic response of LQR‐based control of SAF is faster when compared to SFB‐based control of SAF in both cases. Further, LO and PIO established a steady‐state error between the actual state and its estimate, with reference to desired input, in the presence of a fault. UIO perfectly tracked the desired input, even in the presence of various unknown fault, when compared to LO and PIO. Furthermore, UIO also estimates the unknown faults better when compared to PIO. Finally, in a dynamic operating scenario, the effectiveness of the suggested control strategy has been assessed and verified using MATLAB/SIMULINK and the output of a real‐time simulator (OPAL‐RT OP4510).

Performance Optimization with LPV Synthesis for Disturbance Attenuation in Planar Motors

Optimizing the performance of motion control systems with variations in nonlinear parameters is not an easy task. To accomplish this task, it is important to design the controller using the linear system approach. In this study, a linear parameter varying (LPV) control method is proposed in which nonlinearities are treated as parameter variations for planar motors. The proposed control method consists of the force and torque modulation with the commutation scheme and the nonlinear current controller with H∞ state feedback control in the form of LPV synthesis to improve the position-tracking performance. An interpolated gain-scheduling controller based on LPV synthesis is determined by applying H∞ control to a linear matrix inequality technique. An interpolated gain-scheduling controller can attenuate disturbance without disturbance estimation. The effectiveness of the proposed control method is evaluated using simulation results and compared with the conventional proportional–integral–derivative control to verify both improved position-tracking performance and disturbance attenuation.

On Observer and Controller Design for Nonlinear Hadamard Fractional-Order One-Sided Lipschitz Systems

This paper presents an extensive investigation into the state feedback stabilization, observer design, and observer-based controller design for a specific category of nonlinear Hadamard fractional-order systems. The research extends the conventional integer-order derivative to the Hadamard fractional-order derivative, offering a more universally applicable method for system analysis. Furthermore, the traditional Lipschitz condition is adapted to a one-sided Lipschitz condition, broadening the range of systems amenable to analysis using these techniques. The efficacy of the proposed theoretical findings is illustrated through several numerical examples. For instance, in Example 1, we select an order of derivative r = 0.8; in Example 2, r is set to 0.9; and in Example 3, r = 0.95. This study enhances the comprehension and regulation of nonlinear Hadamard fractional-order systems, setting the stage for future explorations in this domain.

An Investigation into the Viability of Cell-Level Temperature Control in Lithium-Ion Battery Packs

Abstract This article focuses on the thermal management and temperature balancing of lithium-ion battery packs. As society transitions to relying more heavily on renewable energy, the need for energy storage rises considerably, as storage facilitates power regulation between these sources and the grid. Lithium-ion batteries are leading the market for energy storage options, but their properties are temperature sensitive, with thermal abuse resulting in shortened pack lifetime and possible safety issues. Current battery thermal management systems (BTMS) are implemented in a number of ways to ensure consistent and reliable operation. However, they are typically limited in architecture and restricted in ability to attend to temperature gradients. This work proposes a BTMS topology that permits control of the individual cooling received by a cell in a pack. First, an analysis is done using timescale separation to confirm that cell-level temperature control is capable of extending the lifetime of a pack as compared to pack-level control. The analysis is used to guide the gain tuning of a state feedback controller, which directs more cooling effort to cells of higher temperatures. Validation of the BTMS topology and control is performed through the simulation of a battery pack, with variations in total cooling power and resistance heterogeneity. The outcome of the validation studies indicates that the proposed BTMS configuration is better equipped to reduce temperature differences and extend pack life. This benefit increases as total input power increases, giving the controller more freedom to cool unhealthy cells while remaining within power constraints.

Active control for higher order micro sandwich beam with various cores integrated by piezoelectric layers based on MSGT on the Pasternak foundation

In the present article, the vibration suppression of higher order micro sandwich beams based on modified strain gradient beam theory (MSGT) and Reddy/Timoshenko beam theories is developed. Three types of core, including honeycomb, foam, and porous for a micro sandwich beam, are considered. The core’s top and bottom are integrated by piezoelectric layers as actuator and sensor, respectively. Displacement fields are defined via third-order shear deformation beam theory (TSDBT) (or Reddy beam theory (RBT)) and first-order shear deformation beam theory (FSDBT) (or Timoshenko beam theory (TBT)). The governing equations of motion are derived using MSGT to consider the small-scale effect. To optimal approaches for the controller, state feedback is designed based on a linear quadratic regulator (LQR) in the state-space form. Moreover, the effect of various parameters, including small-scale parameters, three types of core, temperature changes, Pasternak foundation, density of core, dimensionless cell thickness ([Formula: see text]), and internal aspect ratio ([Formula: see text]), angles ([Formula: see text]) of honeycomb, and the porosity parameter is performed on the active control of the smart micro sandwich beam. The numerical results indicate that the parameters mentioned significantly affect the optimal vibration control of the smart micro sandwich beam. It is found that the lightweight cores have more attenuation of the transient response and faster settling time. By analyzing the effect of temperature changes on active vibration control of lighter core, it was found that the frequency decreases as the temperature increases. Also, by considering the Pasternak foundation, it is found that the time period without considering the elastic foundation is longer than when considering the elastic foundation, and the natural frequency is vice versa. Also, the settling time by considering the elastic foundation occurs earlier. In the active control field of smart micro beams, this theoretical investigation developed widely as a benchmark for experimental research and the manufacturing process.

Reliable Finite‐Time Control for Nonlinear Chaotic Semi‐Markov Jump Systems With Incomplete Transition Rates

ABSTRACTThis article studies the finite‐time control problem for a class of nonlinear chaotic semi‐Markov jump systems with incomplete transition rates described by the T‐S fuzzy model approach. As a means to depict the dynamical properties pertaining to the examined system, parametric uncertainties, faults, external disturbances and input saturation are taken into consideration. The foremost objective of this study is to come up with a composite control mechanism that effectively rejects and attenuates the repercussions of faults and disturbances. In particular, we primarily built a disturbance observer in order to obtain a precise estimation of the external disturbances. After which, the fault diagnosis observer is designated to effectively estimate the faults. Specifically, a composite reliable control mechanism is developed by fusing the output of the constructed observers with the mode‐dependent fuzzy‐rule based state feedback controller. By employing suitable Lyapunov functions in conjunction with the linear matrix inequality technique, a set of mode‐dependent conditions is derived to ensure the finite‐time stochastic boundedness of the underlying closed‐loop and estimation error systems. Following this, the anticipated controller and observer gain matrices are elicited by resolving the established linear matrix inequalities. Thereafter, intending to ascertain the efficacy and usefulness of accrued theoretical findings, simulation results performed on Chua's circuit system is endowed.

Dynamic Sliding Mode Control of Spherical Bubble for Cavitation Suppression

Cavitation is a disadvantageous phenomenon that occurs when fluid pressure drops below its vapor pressure. Under these conditions, bubbles form in the fluid. When these bubbles flow into a high-pressure area or tube, they erupt, causing harm to mechanical parts such as centrifugal pumps. The difference in pressure in a fluid is the result of varying temperatures. One way to eliminate cavitation is to reduce the radius of the bubbles to zero before they reach high-pressure areas, using a robust approach. In this paper, sliding mode control is used for this purpose due to its invariance property. To force the radius of the bubbles toward zero and prevent chattering, a new dynamic sliding mode control approach is used. In dynamic sliding mode control, chattering is removed by passing the input control through a low-pass filter, such as an integrator. A general model of the spherical bubble is used, transferred to the state space, and then a state proportional-integral feedback is applied to obtain a linear system with a new input control signal. A comparison is also made with traditional sliding mode control using state feedback, providing a trusted comparison.

Bayesian inference of state feedback control parameters for fo perturbation responses in cerebellar ataxia.

Behavioral speech tasks have been widely used to understand the mechanisms of speech motor control in typical speakers as well as in various clinical populations. However, determining which neural functions differ between typical speakers and clinical populations based on behavioral data alone is difficult because multiple mechanisms may lead to the same behavioral differences. For example, individuals with cerebellar ataxia (CA) produce atypically large compensatory responses to pitch perturbations in their auditory feedback, compared to typical speakers, but this pattern could have many explanations. Here, computational modeling techniques were used to address this challenge. Bayesian inference was used to fit a state feedback control (SFC) model of voice fundamental frequency (fo) control to the behavioral pitch perturbation responses of speakers with CA and typical speakers. This fitting process resulted in estimates of posterior likelihood distributions for five model parameters (sensory feedback delays, absolute and relative levels of auditory and somatosensory feedback noise, and controller gain), which were compared between the two groups. Results suggest that the speakers with CA may proportionally weight auditory and somatosensory feedback differently from typical speakers. Specifically, the CA group showed a greater relative sensitivity to auditory feedback than the control group. There were also large group differences in the controller gain parameter, suggesting increased motor output responses to target errors in the CA group. These modeling results generate hypotheses about how CA may affect the speech motor system, which could help guide future empirical investigations in CA. This study also demonstrates the overall proof-of-principle of using this Bayesian inference approach to understand behavioral speech data in terms of interpretable parameters of speech motor control models.

Kinodynamic Model-Based UAV Trajectory Optimization for Wireless Communication Support of Internet of Vehicles in Smart Cities

Unmanned aerial vehicles (UAVs) are utilized for wireless communication support of Internet of Intelligent Vehicles (IoVs). Intelligent vehicles (IVs) need vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) wireless communication for real-time perception knowledge exchange and dynamic environment modeling for safe autonomous driving and mission accomplishment. UAVs autonomously navigate through dense urban areas to provide aerial line-of-sight (LoS) communication links for IoVs. Real-time UAV trajectory design is required for minimum energy consumption and maximum channel performance. However, this is multidisciplinary research including (1) dynamic-aware kinematic (kinodynamic) planning by considering UAVs’ motion and nonholonomic constraints; (2) channel modeling and channel performance improvement in future wireless networks (i.e., beyond 5G and 6G) that are limited to beamforming to LoS links with the aid of reconfigurable intelligent surfaces (RISs); and (3) real-time obstacle-free crash avoidance 3D trajectory optimization in dense urban areas by modeling obstacles and LoS paths in convex programming. Modeling and solving this multilateral problem in real-time are computationally prohibitive unless extensive computational and overhead processing costs are imposed. To pave the path for computationally efficient yet feasible real-time trajectory optimization, this paper presents UAV kinodynamic modeling. Then, it proposes a convex trajectory optimization problem with the developed linear kinodynamic models. The optimality and smoothness of the trajectory optimization problem are improved by utilizing model predictive control and quadratic state feedback control. Simulation results are provided to validate the methodology.

Integrated Motion Control Strategy Considering Parameter Robustness for Distributed Vehicle by Wire

<div>To address the issues of functional conflicts in execution subsystems and the deterioration of control performance due to model parameter uncertainties in the motion control of distributed vehicle by wire, this article proposes an integrated control strategy considering parameter robustness. This strategy aims to compensate for model mismatch, resolve functional conflicts, and achieve motion coordination. Based on the over-actuation characteristics of distributed vehicle by wire, this article constructs the dynamic model and utilizes the tire cornering properties along with phase portraits to delineate the working regions of the execution subsystems. To deal with model parameter uncertainties and mismatch, tube-based model predictive control (tube-based MPC) is applied to the control strategy design, which compensates for model deviations through state feedback and constructs a robust positively invariant set (RPI) to constrain the system state. Correspondingly, the weights of control inputs are adjusted adaptively, according to the working regions, to optimize the coordination logic of integrated control. In order to verify the effectiveness and feasibility of the strategy, extreme driving condition tests are executed on hardware-in-the-loop (HIL) and real vehicle test platforms. The test results indicate that the strategy proposed in this article is able to reduce the sideslip angle and tracking error of yaw rate, improve driving stability under extreme conditions through integrated control, and especially, it can still maintain precise stability control performance under severe model mismatch, exhibiting strong robustness facing parameter uncertainties.</div>

A comprehensive survey of space robotic manipulators for on-orbit servicing.

On-Orbit Servicing (OOS) robots are transforming space exploration by enabling vital maintenance and repair of spacecraft directly in space. However, achieving precise and safe manipulation in microgravity necessitates overcoming significant challenges. This survey delves into four crucial areas essential for successful OOS manipulation: object state estimation, motion planning, and feedback control. Techniques from traditional vision to advanced X-ray and neural network methods are explored for object state estimation. Strategies for fuel-optimized trajectories, docking maneuvers, and collision avoidance are examined in motion planning. The survey also explores control methods for various scenarios, including cooperative manipulation and handling uncertainties, in feedback control. Additionally, this survey examines how Machine learning techniques can further propel OOS robots towards more complex and delicate tasks in space.

Robustness of linear time‐invariant systems with feedback control protocols under random disturbances

AbstractIn this paper, the robustness of global exponentially stable (ES) linear time‐invariant (LTI) systems with feedback control protocols is examined under the influence of random disturbances (RDs). For a given LTI system with global ES, a state feedback (SF) control protocol and a output feedback (OF) control protocol are proposed to keep the robustness of the discussed system, respectively. Meanwhile, how much the intensity of RDs that LTI system can withstand is obtained by the transcendental equation, in which the feedback gains are also designed and calculated by a proposed iterative algorithm. The theoretical analysis results demonstrate that the perturbed LTI systems may remain ES when the RDs are smaller than the upper bounds obtained in this paper. Finally, three cases are proposed to illustrate the effectiveness of the theoretical research.

Stability analysis and stabilization of discrete-time switched nonlinear systems with mode-dependent average dwell time under nested actuator saturation

In this paper, the stability analysis and stabilization of a class of mode-dependent mean residence time-based discrete-time switching nonlinear systems are addressed. More specifically, under the mode-dependent average dwell time (MDADT) switching mode, combined with the practical problem, the nonlinear factor of nested actuator saturation (NAS) is introduced. Firstly, in order to ensure the system stability, based on the parameter-dependent discontinuous switching Lyapunov function and several basic lemmas, a state feedback controller is designed that makes the closed-loop system (CLS) achieve local exponential stability (LES) by solving the optimal problem in terms of linear matrix inequalities (LMIs). Secondly, the system considers the maximum attraction domain that can be achieved by the NAS system under the conditions. The simulation results show the effectiveness of the proposed design method. At the same time, the efficiency of the proposed method is verified via a water tank example.

Sliding mode control to stabilization of coupled time fractional parabolic PDEs subject to disturbances

AbstractIn this article, the stabilization of coupled time fractional parabolic partial differential equations subject to external disturbances is investigated. By using sliding mode control method and backstepping approach, a boundary state feedback controller is designed to reject the matched disturbance and achieve the Mittag‐Leffler input‐to‐state stability of closed‐loop system. The existence of the generalized solution to the closed‐loop system is proven by Galerkin approximation scheme. Simulations are presented to illustrate the validity of our theoretical results.

Non-fragile event-triggered control for switched positive linear systems using state-dependent switching method

This article is concerned with the issues of stability and L1-gain characteristic for switched positive linear systems utilizing bumpless transfer (BT) technique and event-triggered (ET) strategy. Under the state-driven switching policy, a regulatory approach that couples BT and ET is introduced to attenuate the hybrid bumps stemming from switching and triggering moments. Compared with traditional state-driven switching, the proposed hysteresis switching can delay the occurrence of switching. Based on multiple copositive Lyapunov functions, a state feedback controller with an ET mechanism is constructed for positive systems, which reduces the update frequency of the actuator, and this control strategy is extended to the case of actuator faults. It is confirmed that the proposed control scheme can assure the positivity, stability, and L1-gain performance of the system. Additionally, the Zeno phenomenon is addressed via establishing a positive lower bound for the ET interval. Ultimately, simulation examples containing a turbofan engine model are provided to demonstrate the effectiveness of the proposed approach.

Robust non-fragile hybrid control for delayed uncertain singular impulsive jump systems based on improved impulse instant-dependent auxiliary functions method

This article researches the issue of robust non-fragile hybrid control for delayed uncertain singular impulsive jump systems (USIMJSs). The key aim is to design non-fragile hybrid state feedback controllers (including a non-fragile normal state feedback controller and a non-fragile impulsive state feedback controller), which are insensitive to the uncertainties of gains of controllers and can provide sufficient tuning margins. The non-fragile normal state feedback controller can eliminate the internal impulses and overcome the external disturbances; the non-fragile impulsive state feedback controller can suppress the interference of external unstable impulses and restrain the instantaneous jumps caused by Markovian modes switching. By introducing impulse instant-dependent auxiliary functions, the improved impulse-time-dependent Lyapunov–Krasovskii functional is constructed, which can capture the information of the impulse instants and Markovian jump modes. Novel criteria of robust admissibilization for delayed USIMJSs are acquired under linear matrix inequalities framework. Lastly, the effectiveness of the derived algorithm and designed method is confirmed by simulation examples including a direct current motor-controlled inverted pendulum device and a Quarter-Car active suspension model.

Modification of Infinite and Unstable Invariant Zeros in Linear Systems Using Stability-Preserving State Feedback

Modification of Infinite and Unstable Invariant Zeros in Linear Systems Using Stability-Preserving State Feedback