Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems

This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation theory.For the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost function.For the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement data.By combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop system.The proposed decomposition design not only bypasses the numerical stiffness but also alleviates the high-dimensionality.The efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.

Event-triggered robust cooperative output regulation for a class of linear multi-agent systems with an unknown exosystem

This paper investigates the robust cooperative output regulation problem for a class of heterogeneousuncertain linear multi-agent systems with an unknown exosystem via event-triggered control (ETC). By utilizingthe internal model approach and the adaptive control technique, a distributed adaptive internal model isconstructed for each agent. Then, based on this internal model, a fully distributed ETC strategy composed ofa distributed event-triggered adaptive output feedback control law and a distributed dynamic event-triggeringmechanism is proposed, in which each agent updates its control input at its own triggering time instants. It isshown that under the proposed ETC strategy, the robust cooperative output regulation problem can be solvedwithout requiring either the global information associated with the communication topology or the bounds ofthe uncertain or unknown parameters in each agent and the exosystem. A numerical example is provided toillustrate the effectiveness of the proposed control strategy.

Dynamic Constraint-Driven Event-Triggered Control of Strict-Feedback Systems Without Max/Min Values on Irregular Constraints

This work proposes an event-triggered adaptive control approach for a class of uncertain nonlinear systems under irregular constraints.Unlike the constraints considered in most existing papers,here the external irregular constraints are considered and a constraints switching mechanism(CSM)is introduced to circumvent the difficulties arising from irregular output constraints.Based on the CSM,a new class of generalized barrier functions are constructed,which allows the control results to be independent of the maximum and minimum values(MMVs)of constraints and thus extends the existing results.Finally,we proposed a novel dynamic constraint-driven event-triggered strategy(DCDETS),under which the stress on signal transmission is reduced greatly and no constraints are violated by making a dynamic trade-off among system state,external constraints,and inter-execution intervals.It is proved that the system output is driven to close to the reference trajectory and the semi-global stability is guaranteed under the proposed control scheme,regardless of the external irregular output constraints.Simulation also verifies the effectiveness and benefits of the proposed method.

Asynchronous Learning-Based Output Feedback Sliding Mode Control for Semi-Markov Jump Systems: A Descriptor Approach

This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning technique.Compared with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization phenomenon.The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem.Based upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions.Furthermore,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion.Finally,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.

Distributed Adaptive Output Consensus of Unknown Heterogeneous Non-Minimum Phase Multi-Agent Systems

This article addresses the leader-following output consensus problem of heterogeneous linear multi-agent systems with unknown agent parameters under directed graphs.The dynamics of followers are allowed to be non-minimum phase with unknown arbitrary individual relative degrees.This is contrary to many existing works on distributed adaptive control schemes where agent dynamics are required to be minimum phase and often of the same relative degree.A distributed adaptive pole placement control scheme is developed,which consists of a distributed observer and an adaptive pole placement control law.It is shown that under the proposed distributed adaptive control scheme,all signals in the closed-loop system are bounded and the outputs of all the followers track the output of the leader asymptotically.The effectiveness of the proposed scheme is demonstrated by one practical example and one numerical example.

Anti-Disturbance Control for Tethered Aircraft System With Deferred Output Constraints

In this paper,we investigate the peaking issue of extended state observers and the anti-disturbance control problem of tethered aircraft systems subject to the unstable flight of the main aircraft,airflow disturbances and deferred output constraints.Independent of exact initial values,a modified extended state observer is constructed from a shifting function such that not only the peaking issue inherently in the observer is circumvented completely but also the accurate estimation of the lumped disturbance is guaranteed.Meanwhile,to deal with deferred output constraints,an improved output constrained controller is employed by integrating the shifting function into the barrier Lyapunov function.Then,by combining the modified observer and the improved controller,an anti-disturbance control scheme is presented,which ensures that the outputs with any bounded initial conditions satisfy the constraints after a pre-specified finite time,and the tethered aircraft tracks the desired trajectory accurately.Finally,both a theoretical proof and simulation results verify the effectiveness of the proposed control scheme.

Lyapunov-Based Output Containment Control of Heterogeneous Multi-Agent Systems With Markovian Switching Topologies and Distributed Delays

This paper considers the mean square output containment control problem for heterogeneous multi-agent systems(MASs)with randomly switching topologies and nonuniform distributed delays.By modeling the switching topologies as a continuous-time Markov process and taking the distributed delays into consideration,a novel distributed containment observer is proposed to estimate the convex hull spanned by the leaders'states.A novel distributed output feedback containment controller is then designed without using the prior knowledge of distributed delays.By constructing a novel switching Lyapunov functional,the output containment control problem is then solved in the sense of mean square under an easily-verifiable sufficient condition.Finally,two numerical examples are given to show the effectiveness of the proposed controller.

CONTROLLING CHAOTIC OSCILLATIONS OF VISCO-ELASTIC PLATESBY THE LINEARIZATION VIA OUTPUTFEEDBACK

Controlling chaotic oscillations of viscoelastic plates are investigated in this paper. Based on the exact linearization method in nonlinear system control theory, a nonlinear feedback control law is presented for a class of non_affine control systems. The mathematical model describing motion of nonlinear viscoelastic plates is established, and it is simplified by the Galerkin method. The phase space portrait and the power spectrum are employed to demonstrate chaos in the system. The deflection is treated as an output, and is controlled to given periodic goals.

New synthesis algorithm of static output feedback sliding mode control for a class of uncertain systems

Based on a kind of regular form, a Lyapunov matrix with special structure is presented to design the sliding surface matrix conveniently and then an effective algorithm is developed on it. A simple static output feedback sliding mode control law without extra dynamic equation is given, such that the predefined sliding surface is reached in finite time for the general matching uncertainties. In the reported result, this extra dynamic equation is used for evaluating the norm bound of the unmeasured state vector. Finally, some examples are studied to illustrate the proposed approach.

The Design of Output Feedback Distributed Model Predictive Controller for a Class of Nonlinear Systems

For a class of nonlinear systems whose states are immeasurable, when the outputs of the system are sampled asynchronously, by introducing a state observer, an output feedback distributed model predictive control algorithm is proposed. It is proved that the errors of estimated states and the actual system's states are bounded. And it is guaranteed that the estimated states of the closed-loop system are ultimately bounded in a region containing the origin. As a result, the states of the actual system are ultimately bounded. A simulation example verifies the effectiveness of the proposed distributed control method.

Controlling the output power of soft switching arc welding inverter by two-stage continuous PWM method

The full bridge zero voltage zero current switching （ FB-ZVZCS ） , which could adjust the output power by keeping the duty ratio of lagging leg constant and changing the duty ratio of leading leg, was a common circuit of soft switching arc welding inverter power source. However, when the duty ratio of leading leg was reduced to zero, the output power stayed the constant value instead of becoming zero. The working status and waveforms of some major parameters were studied in this paper while the duty ratio of leading leg was zero. It was concluded that the minimum output power of soft switching inverter was related to the charging voltage of paraUel capacitors, and the output power also could be reduced by reducing the duty ratio of lagging leg. A novel two-stage continuous PWM control method that could switch working-mode between full bridge and half bridge was put forward in this paper. This kind of control method could further reduce the output power of soft switching inverter in order to meet the requirement of low heat input of sheet metal welding.

Evolution and controlling factors of the gravity flow deposits in the Miocene sequence stratigraphic framework,the Lower Congo-Congo Fan Basin,West Africa

To understand the evolution of the Miocene gravity flow deposits in the Lower Congo-Congo Fan Basin,this paper documents the Miocene sequence stratigraphic framework,the depositional characteristics and the controlling factors of the gravity flow system.Based on the establishment of high-resolution sequence stratigraphic framework,lithofacies characteristics and sedimentary units of the gravity flow deposits in the region are identified by using seismic,well logging and core data comprehensively,and the sedimentary evolution process is revealed and the controlling factors are discussed.The Miocene can be divided into four 3 rd-order sequences(SQ1-SQ4).The gravity flow deposits mainly include siliciclastic rock and pelite.The main sedimentary units include slumping deposits,mass transport deposits(MTD),channel fills,levee-overbank deposits,and frontal lobes.In the Early Miocene(SQ1),mainly gull-wing,weakly restricted to unrestricted depositional channel-overbank complexes and lobes were formed.In the early Middle Miocene(SQ2),W-shaped and weakly restricted erosional-depositional channels(multi-phase superposition)were subsequently developed.In the late Middle Miocene(SQ3),primarily U-shaped and restricted erosional channels were developed.In the Late Miocene(SQ4),largely V-shaped and deeply erosional isolated channels were formed in the study area.Climate cooling and continuous fall of the sea level made the study area change from toe of slope-submarine plain to lower continental slope,middle continental slope and finally to upper continental slope,which in turn affected the strength of the gravity flow.The three times of tectonic uplifting and climate cooling in the West African coast provided abundant sediment supply for the development of gravity flow deposits.Multistage activities of salt structures played important roles in redirecting,restricting,blocking and destroying the gravity flow deposits.Clarifying the characteristics,evolution and controlling factors of the Miocene gravity flow deposits in the Lower Congo-Congo Fan Basin can provide reference for deep-water petroleum exploration in this basin.

Robust output-feedback stabilization of a class of nonlinear systems with the nonlinearities of varied form

The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear continuous systems confined by a bound function, the nonlinearities of the systems may be of varied forms or uncertain; the designed stabilizer is robust means that a class of nonlinear continuous systems can be stabilized by the same output feedback stabilization schemes; numerical simulation examples are given.

Self-Triggered Set Stabilization of Boolean Control Networks and Its Applications

Set stabilization is one of the essential problems in engineering systems, and self-triggered control(STC) can save the storage space for interactive information, and can be successfully applied in networked control systems with limited communication resources. In this study, the set stabilization problem and STC design of Boolean control networks are investigated via the semi-tensor product technique. On the one hand, the largest control invariant subset is calculated in terms of the strongly connected components of the state transition graph, by which a graph-theoretical condition for set stabilization is derived. On the other hand, a characteristic function is exploited to determine the triggering mechanism and feasible controls. Based on this, the minimum-time and minimum-triggering open-loop, state-feedback and output-feedback STCs for set stabilization are designed,respectively. As classic applications of self-triggered set stabilization, self-triggered synchronization, self-triggered output tracking and self-triggered output regulation are discussed as well. Additionally, several practical examples are given to illustrate the effectiveness of theoretical results.

Temperature-Based Fan Speed Optimization Strategy

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments,research on intelligent fan speed control systems has become particularly important.This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort.Firstly,by analyzing existing fan speed control technologies,their main limitations are identified,such as the inability to achieve smooth speed transitions.To address this issue,a BP-PID speed control algorithm is designed,which dynamically adjusts fan speed based on indoor temperature changes.Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures.Furthermore,the real-time responsiveness of the system is crucial for enhancing user comfort.Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments.Ultimately,this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.

Adaptive Control Based on Neural Networks for an Uncertain 2-DOF Helicopter System With Input Deadzone and Output Constraints

In this paper, a study of control for an uncertain2-degree of freedom(DOF) helicopter system is given. The2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function(IBLF) is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser's 2-DOF helicopter.

The early-middle Miocene submarine fan system in the Pearl River Mouth Basin, South China Sea

Based on a large amount of seismic, drilling and core data, the characteristics of the early- middle Miocene submarine fans in the Baiyun Sag, northern South China Sea are investigated. By analyzing the sedimentary processes of submarine fans in SQ21 （SQ21 refers to the 3rd-order sequence with its bottom boundary 21 Ma）, a sedimentary model of the sand-rich fans is established and the main factors controlling fan deposition are detailed. The results indicate that from early to middle Miocene the Pearl River Mouth Basin developed seven 3rd-order sequences in all, with each lowstand systems tract （LST） of the sequence corresponding to submarine fans. However, only the fans in SQ13.8 and SQ21 are sand-rich fans, the others being mud-rich fans. The cores reveal that the submarine fans in the Pearl River Mouth Basin developed five lithofacies： （1） mud clast-bearing sandstone, interpreted as channel deposits; （2） typical turbidite sandstones, also interpreted as channel deposits; （3） thin-bedded sandstone and mudstone, interpreted as channel-levee complex deposits; （4） massive sandstones, interpreted as lobe deposits; （5） massive mudstone, interpreted as hemipelagic mud. The sand-rich submarine fans in the Pearl River Mouth Basin mainly developed in LST, and in LST reverse faults were active, which led to the formation of accommodation on the shelf. Different from the theory of classic sequence stratigraphy, the accommodation on the shelf captures terrigenous debris transported by the Pearl River, and the uplift at the edge of shelf serves as a ＂Linear Source＂ for the deep water area instead of the Pearl River. Therefore, the fans mainly derived from the eroded debris from the uplift. Factors controlling fan deposition include the basin＇s tectonic framework, the evolution of the slope break, relative sea-level changes as well as the evolution of the fault system, and the fans are formed under the combination of the above factors.

Data-Driven Global Robust Optimal Output Regulation of Uncertain Partially Linear Systems

In this paper, a data-driven control approach is developed by reinforcement learning (RL) to solve the global robust optimal output regulation problem (GROORP) of partially linear systems with both static uncertainties and nonlinear dynamic uncertainties. By developing a proper feedforward controller, the GROORP is converted into a global robust optimal stabilization problem. A robust optimal feedback controller is designed which is able to stabilize the system in the presence of dynamic uncertainties. The closed-loop system is ensured to be input-to-output stable regarding the static uncertainty as the external input. This robust optimal controller is numerically approximated via RL. Nonlinear small-gain theory is applied to show the input-to-output stability for the closed-loop system and thus solves the original GROORP. Simulation results validates the efficacy of the proposed methodology.

Robust H∞ output tracking control of uncertain networked control systems

This paper investigates a problem of robust output tracking control of networked control systems(NCSs) with network-induced delays, packet dropouts, parameter uncertainties and external disturbances. Firstly, an augmented model of time-delay system is proposed for networked tracking control systems. Then, considering the piecewise differentiable characteristic of time-delay, the criterion to output tracking performance analysis and controller design are derived by using an approach of free weighting matrix, reciprocally convex and cone complementarity linearization(CCL). Finally, simulation results of numerical examples show the effectiveness of the proposed approach, and illustrate the advantages of the proposed criteria which outperform previous criteria in the literature.

Adaptive Output Regulation of a Class of Nonlinear Output Feedback Systems With Unknown High Frequency Gain

This paper presents an output feedback design approach based on the adaptive control scheme developed for nonlinearly parameterized systems,to achieve global output regulation for a class of nonlinear systems in output feedback form.We solve the output regulation problem without the knowledge of the sign and the value of the high frequency gain a priori.It is not necessary to have both the limiting assumptions that the exogenous signal co and the unknown parameter ju belong to a prior known compact set and the high frequency gain has a determinate lower and upper bounds.The effectiveness of the proposed algorithm is shown with the help of an example.