Finite-time Constraint Research Articles

A new neural adaptive finite-time constraint tracking control strategy for stochastic nonlinear systems with quantized input and unknown initial condition

A new neural adaptive finite-time constraint tracking control strategy for stochastic nonlinear systems with quantized input and unknown initial condition

Fault-Tolerant Vehicle Stability Control Based on Active Steering and Direct Yaw Moment With Finite-Time Constraint Performance Recovery

Fault-Tolerant Vehicle Stability Control Based on Active Steering and Direct Yaw Moment With Finite-Time Constraint Performance Recovery

A Novel Asynchronous Sliding Mode Design for Switched Systems under Input–Output Finite-Time Stability

In this work, the input–output finite-time stability (IO-FTS) of a class of continuous-time switched systems characterized by uncertainties and subjected to external disturbances is studied under asynchronous switching by means of the sliding mode control (SMC) method. The IO-FTS poses a finite-time constraint problem, which involves addressing two main issues: firstly, ensuring that the state trajectory of the switched system reaches the given sliding mode surface within the specified time, and secondly, achieving IO-FTS for the closed-loop switched system during asynchronous switching. To address these issues, we apply a partitioning strategy and construct asynchronous sliding mode controllers with adjustable parameters to ensure the reachability of the system’s state trajectory within a finite time. Subsequently, we employ a multiple Lyapunov function (MLF) approach to provide sufficient conditions that ensure IO-FTS during the whole phase [0,T] for the resulting switched system. Additionally, we analyze the asynchronous characteristics concerning the reachability phase of the designed sliding surface, considering the system’s switching properties. Finally, we demonstrate the efficacy of the proposed approach with a numerical example.

Fuzzy adaptive event-triggered finite-time constraint control for output-feedback uncertain nonlinear systems

A fuzzy adaptive event-triggered finite-time constraint control for the uncertain nonlinear system with input hysteresis is developed. Input hysteresis, uncertain and nonlinear characteristic, widely existing in the actual control system, which seriously affect the performance and convergence time of control system. Thus, a fuzzy adaptive event-triggered control method is constructed to overcome the above issues under the limited communication recourses. Furthermore, to ensure the system converges in finite time, an event-triggered finite-time control method is proposed where the communication resources are limited. Finally, some simulation experiments verify the system converges in finite time and the bandwidth resources can be effectively saved under the proposed method.

Three-Dimensional Multi-Mission Planning of UAV Using Improved Ant Colony Optimization Algorithm Based on the Finite-Time Constraints

Three-Dimensional Multi-Mission Planning of UAV Using Improved Ant Colony Optimization Algorithm Based on the Finite-Time Constraints

Importance Splitting for Finite-Time Rare Event Simulation

In this note, a general framework is proposed for using importance splitting to estimate rare event probabilities with finite-time constraints. We prove that the splitting estimator is unbiased and characterize the optimal splitting curves. A new unbiased estimator with truncated sample paths is proposed to improve computational efficiency, and a pilot algorithm is provided to determine the optimal truncation and splitting curves. Numerical examples illustrate the optimality of the splitting curves and the effectiveness of the new estimator.

Optimum output temperature setting and an improved bed structure of metal hydride hydrogen storage reactor for thermal energy storage

As the well-known solid hydrogen storage materials, metal hydrides (MHs) have been developed systematically for decades. During recent years, due to the development of thermal energy storage (TES) market, they have also received much attention gradually as the excellent TES materials because of the high energy density, low cost, and good reversibility. In this study, the stabilized discharging performance of an MH reactor for TES was investigated by numerical simulation. A mathematical model combining multi-physics and proportional-integral controller was established. Based on finite-time thermodynamics, gravimetric exergy-output rate (GEOR) considering the control requirement, finite-material, and finite-time constraints was defined. For a given reactor, the output temperature setting could be optimized based on GEOR. Besides, the effects of the reactor parameters on the optimum output temperature setting were systematically studied. The heat transfer analysis indicated the occurrence of the axial non-uniform reaction in the bed due to the inherent increase in the temperature of heat transfer fluid, resulting in the decrease of both GEOR and material availability. Accordingly, a new tapered bed structure (L/Do = 600/50 mm) was proposed to effectively improve the discharging efficiency from 76 to 90% and GEOR from 65 to 120 W kg−1, which provides a helpful guidance for the advanced designing and construction of MH reactor for the practical TES applications.

New exergy analysis of a regenerative closed Brayton cycle

In this study, the optimal performance of a regenerative closed Brayton cycle is sought through power maximization. Optimization is performed on the output power as the objective function using genetic algorithm. In order to take into account the time and the size constraints in current problem, the dimensionless mass-flow parameter is used. The influence of the unavoidable exergy destruction due to finite-time constraint is taken into account by developing the definition of heat exergy. Finally, the improved definitions are proposed for heat exergy, and the second law efficiency. Moreover, the new definitions will be compared with the conventional ones. For example, at a specified dimensionless mass-flow parameter, exergy overestimation in conventional definition, causes about 31% lower estimation of the second law efficiency. These results could be expected to be utilized in future solar thermal Brayton cycle assessment and optimization.

Finite-time thermodynamic analysis for a chemically driven heat engine based on probability theory

This paper studies the problem of power optimization of chemically driven heat engine obeying Arrhenius law kinetics. Respectively, the first and second order reaction kinetics models taking the rate coefficients of the chemical reaction as finite-time constraints has been analyzed by the methods of finite-time thermodynamics with the synthetical consideration about the optimal configuration of the coupling process between chemical reaction and heat engines, and the effects of the finite-time thermodynamic characteristics of the coupling relation between chemical reaction and heat engine on the power optimization has been obtained. Combining the numerical results of this paper and the previous analysis, there is always a finite optimal flow rate in the reactor that yields maximum power when chemical reactions drive these three kinds of heat engine models, but a generalized Carnot heat engine driven by a chemical reaction can obtain the maximum power output in the practical case, the optimal flow rate in which the model of a generalized Carnot engine obtains the maximum power output can make the fuel efficiency of the system approaches the optimal value simultaneously. The finite-time thermodynamic method based on probability analysis can more accurately describe various performance parameters of thermodynamic system, this paper establishes the probability model of the first order reaction kinetics theory by using the probability analysis method, and obtains the power and fuel efficiency fluctuation bounds of the chemically driven heat engines. The results can not only include the mean value that is the only information obtained by classical method, but also take the fluctuations in microscale into account. The probabilistic method can provide more abundant information in the prediction of practical performance for the micro-size systems.

Finite-time state-dependent Riccati equation for time-varying nonaffine systems: Rigid and flexible joint manipulator control

This article investigates finite-time optimal and suboptimal controls for time-varying systems with state and control nonlinearities. The state-dependent Riccati equation (SDRE) controller was the main framework. A finite-time constraint imposed on the equation changes it to a differential equation, known as the state-dependent differential Riccati equation (SDDRE) and this equation was applied to the problem reported in this study that provides general formulation and stability analysis. The following four solution methods were developed for solving the SDDRE; backward integration, state transition matrix (STM) and the Lyapunov based method. In the Lyapunov approach, both positive and negative definite solutions to related SDRE were used to provide suboptimal gain for the SDDRE. Finite-time suboptimal control is applied for robotic manipulator, as finite-time constraint strongly decreases state error and operation time. General state-dependent coefficient (SDC) parameterizations for rigid and flexible joint arms (prismatic or revolute joints) are introduced. By including nonlinear control inputs in the formulation, the actuator׳s limits can be inserted directly to the state-space equation of a manipulator. A finite-time SDRE was implemented on a 6R manipulator both in theory and experimentally. And a reduced 3R arm was modeled and tested as a flexible joint robot (FJR). Evaluations of load carrying capacity and operation time were investigated to assess the capability of this approach, both of which showed significant improvement.

A Finite-Time Dual Method for Negotiation between Dynamical Systems

This work presents a distributed algorithm for online negotiations of an optimal control policy between dynamical systems. We consider a network of self-interested agents that must agree upon a common state within a specified finite time. The proposed algorithm exploits the distributed structure of the corresponding dual problem and uses a “shrinking horizon” property to enforce the finite-time constraint. It is shown that this algorithm evolves like a time-varying and linear dynamical system, parameterized by a scalar variable analogous to the step-size rule in subgradient methods. The convergence and performance properties of the system are studied in the context of error systems between the algorithm trajectories and a sequence of centralized optimal control trajectories. This analysis provides a simple linear matrix inequality condition for choosing a proper step-size rule and also gives conditions for when no step-size rule can guarantee uniform convergence of the error systems. These conditions are ...

An attempt to introduce dynamics into generalised exergy considerations

In previous research, the author developed a general abstract framework for the exergy content of a system of finite objects [Grubbström RW. Towards a generalized exergy concept. In: van Gool W, Bruggink JJC, editors. Energy and time in the economic and physical sciences. Amsterdam: North-Holland; 1985. p. 41–56]. Each such object is characterised by its initial extensive properties and has an inner energy written as a function of these properties. It was shown that if these objects were allowed to interact, there is a maximum amount of work that can be extracted from the system as a whole, and a general formula for this potential was provided. It was also shown that if one of the objects was allowed to be of infinite magnitude initially, taking on the role as an environment having constant intensive properties, then the formula provided took on the same form as the classical expression for exergy. As a side result, the theoretical considerations demonstrated that the second law of thermodynamics could be interpreted as the inner energy function being a (weakly) convex function of its arguments, when these are chosen as the extensive properties. Since exergy considerations are based on the principle that total entropy is conserved when extracting work, these processes would take an infinite time to complete. In the current paper, instead, a differential-equation approach is introduced to describe the interaction in finite time between given finite objects of a system. Differences in intensive properties between the objects provide a force enabling an exchange of energy and matter. An example of such an interaction is heat conduction. The resulting considerations explain how the power extracted from the system will be limited by the processes being required to perform within finite-time constraints. Applying finite-time processes, in which entropy necessarily is generated, leads to formulating a theory for a maximal power output from the system. It is shown that such a theory is possible to develop, and the resulting equilibrium conditions are compared with to those of the exergetic equilibrium.

Study of the improvement in the performance coefficient of machines operating with three reservoirs

The authors propose, in the first step of this paper, a unified description of machines operating with three reservoirs: refrigerating machines, heat pumps, thermotransformers, using a finite time thermodynamic approach. The incidence on the COP definitions is presented. A sensitivity study is made: performance coefficient function of variables and parameters. The calculation for each machine type is conducted for two possible cases: endoreversible machine (without internal entropy creation) and endo et exo irreversible machine (with entropy creation). The influence of the heat transfer law type is enlightened. In the second step of this paper, we propose an optimisation of performance coefficient for each type of machine with finite time constraints on the total conductance of the system.

Entropy generation minimization: The new thermodynamics of finite-size devices and finite-time processes

Entropy generation minimization (finite time thermodynamics, or thermodynamic optimization) is the method that combines into simple models the most basic concepts of heat transfer, fluid mechanics, and thermodynamics. These simple models are used in the optimization of real (irreversible) devices and processes, subject to finite-size and finite-time constraints. The review traces the development and adoption of the method in several sectors of mainstream thermal engineering and science: cryogenics, heat transfer, education, storage systems, solar power plants, nuclear and fossil power plants, and refrigerators. Emphasis is placed on the fundamental and technological importance of the optimization method and its results, the pedagogical merits of the method, and the chronological development of the field.

Analytical and numerical estimates of efficiency for an irreversible heat engine with distributed working fluid

Previous work on estimating power output from heat engines is extended to estimating efficiency under finite-time constraints. A numerical method for estimating efficiencies for a class of finite-time thermodynamic models with variable-temperature reservoirs and arbitrary heat-exchange laws is proposed. The method is based on energy and entropy balances, and on the use of optimal control, Lagrange multipliers, and convex optimization. It is applicable both to lumped-parameter and distributed-parameter models. An analytical expression for the upper bound of the efficiency is obtained for constant-temperature reservoirs and Newtonian heat-exchange laws. Results of computations for two efficiency definitions are presented.