Dynamic analysis of two fishery capture models with a variable search rate and fuzzy biological parameters.

The fishery resource is a kind of important renewable resource and it is closely connected with people's production and life. However, fishery resources are not inexhaustible, so it has become an important research topic to develop fishery resources reasonably and ensure their sustainability. In the current study, considering the environment changes in the system, a fishery model with a variable predator search rate and fuzzy biological parameters was established first and then two modes of capture strategies were introduced to achieve fishery resource exploitation. For the fishery model in a continuous capture mode, the dynamic properties were analyzed and the results show that predator search rate, imprecision indexes and capture efforts have a certain impact on the existence and stability of the coexistence equilibrium. The bionomic equilibrium and optimal capture strategy were also discussed. For the fishery model in a state-dependent feedback capture mode, the complex dynamics including the existence and stability of the periodic solutions were investigated. Besides the theoretical results, numerical simulations were implemented step by step and the effects of predator search rate, fuzzy biological parameters and capture efforts on the system were demonstrated. This study not only enriched the related content of fishery dynamics, but also provided certain reference for the development and utilization of fishery resources under the environment with uncertain parameters.

A fishery predator-prey model with anti-predator behavior and complex dynamics induced by weighted fishing strategies.

In this work, a fishery predator-prey model with anti-predator behavior is presented according to the anti-predator phenomenon in nature. On the basis of this model, a capture model guided by a discontinuous weighted fishing strategy is established. For the continuous model, it analyzes how anti-predator behavior affects system dynamics. On this basis, it discusses the complex dynamics (order-m periodic solution (m=1,2)) induced by a weighted fishing strategy. Besides, in order to find the capture strategy that maximizes the economic profit in the fishing process, this paper constructs an optimization problem based on the periodic solution of the system. Finally, all of the results of this study have been verified numerically in MATLAB simulation.

Prescribed performance tracking control for a class of nonlinear system considering input and state constraints.

This article develops a new anti-saturation tracking approach for effectively controlling a type of state-constrained systems under actuator failure. To construct a feedback control loop possessed the predetermined indexes, an auxiliary variable incorporated with a performance guider is first introduced into the design process. Then, a robust fault tolerant control law with the variable-gains is devised to guarantee that the tracking errors can be suppressed in the specified range after a predetermined time. In order to dispose of the input constraint problem, an anti-saturation algorithm is designed without compromising the prescribed capability indexes in control process, it is shown that the proposed feedback control loop can efficiently fulfill the fast and accurate requirement of the constraint tasks. Finally, computer simulation related with robot manipulator is taken to evaluate the validity of designed method.

Adaptive compensation control for attitude adjustment of quad-rotor unmanned aerial vehicle.

A compensation control strategy based on adaptive back-stepping technique is presented to address the problem of attitude adjustment for a quad-rotor unmanned aerial vehicle (QR- UAV) with inertia parameter uncertainties, the limited airflow disturbance and the partial loss of rotation speed effectiveness. In the design process of control system, adaptive estimation technique is introduced into the closed loop system in order to compensate the lumped disturbance term. More specifically, the designed controller utilizes "prescribed performance bounds" method, and therefore guarantees the transient performance of tracking errors, even in the presence of the lumped disturbance. Adaptive compensation algorithms under the proposed closed loop system structure are derived in the sense of Lyapunov stability analysis such that the attitude tracking error converge to a small neighborhood of equilibrium point. Finally, the simulation results demonstrate the effectiveness of the proposed controller.

Stabilization and synchronization for a mechanical system via adaptive sliding mode control.

In this paper, we investigate the synchronization problem of chaotic centrifugal flywheel governor with parameters uncertainty and lumped disturbances. A slave centrifugal flywheel governor system is considered as an underactuated following-system which a control input is designed to follow a master centrifugal flywheel governor system. To tackle lumped disturbances and uncertainty parameters, a novel synchronization control law is developed by employing sliding mode control strategy and Nussbaum gain technique. Adaptation updating algorithms are derived in the sense of Lyapunov stability analysis such that the lumped disturbances can be suppressed and the adverse effect caused by uncertainty parameters can be compensated. In addition, the synchronization tracking-errors are proven to converge to a small neighborhood of the origin. Finally, simulation results demonstrate the effectiveness of the proposed control scheme.

Theoretical study and control optimization of an integrated pest management predator-prey model with power growth rate.

This work presents a pest control predator-prey model, where rate of change in prey density follows a scaling law with exponent less than one and the control is by an integrated management strategy. The aim is to investigate the change in system dynamics and determine a pest control level with minimum control price. First, the dynamics of the proposed model without control is investigated by taking the exponent as an index parameter. And then, to determine the frequency of spraying chemical pesticide and yield releases of the predator, the existence of the order-1 periodic orbit of the control system is discussed in cases. Furthermore, to ensure a certain robustness of the adopted control, i.e., for an inaccurately detected species density or a deviation, the control system could be stabilized at the order-1 periodic orbit, the stability of the order-1 periodic orbit is verified by an stability criterion for a general semi-continuous dynamical system. In addition, to minimize the total cost input in pest control, an optimization problem is formulated and the optimum pest control level is obtained. At last, the numerical simulations with a specific model are carried out to complement the theoretical results.

Studies on generalized kinetic model and Pareto optimization of a product-driven self-cycling bioprocess.

The aim of this study is the optimization of a product-driven self-cycling bioprocess and presentation of a way to determine the best possible decision variables out of a set of alternatives based on the designed model. Initially, a product-driven generalized kinetic model, which allows a flexible choice of the most appropriate kinetics is designed and analysed. The optimization problem is given as the bi-objective one, where maximization of biomass productivity and minimization of unproductive loss of substrate are the objective functions. Then, the Pareto fronts are calculated for exemplary kinetics. It is found that in the designed bioprocess, a decrease of emptying/refilling fraction and an increase of substrate feeding concentration cause an increase of the biomass productivity. An increase of emptying/refilling fraction and a decrease of substrate feeding concentration cause a decrease of unproductive loss of substrate. The preferred solutions are calculated using the minimum distance from an ideal solution method, while giving proposals of their modifications derived from a decision maker's reactions to the generated solutions.

Adaptive backstepping sliding mode control with fuzzy monitoring strategy for a kind of mechanical system.

A novel adaptive backstepping sliding mode control (ABSMC) law with fuzzy monitoring strategy is proposed for the tracking-control of a kind of nonlinear mechanical system. The proposed ABSMC scheme combining the sliding mode control and backstepping technique ensure that the occurrence of the sliding motion in finite-time and the trajectory of tracking-error converge to equilibrium point. To obtain a better perturbation rejection property, an adaptive control law is employed to compensate the lumped perturbation. Furthermore, we introduce fuzzy monitoring strategy to improve adaptive capacity and soften the control signal. The convergence and stability of the proposed control scheme are proved by using Lyaponov's method. Finally, numerical simulations demonstrate the effectiveness of the proposed control scheme.

Finite-time control for nonlinear spacecraft attitude based on terminal sliding mode technique.

In this paper, a fast terminal sliding mode control (FTSMC) scheme with double closed loops is proposed for the spacecraft attitude control. The FTSMC laws are included both in an inner control loop and an outer control loop. Firstly, a fast terminal sliding surface (FTSS) is constructed, which can drive the inner loop tracking-error and the outer loop tracking-error on the FTSS to converge to zero in finite time. Secondly, FTSMC strategy is designed by using Lyaponov's method for ensuring the occurrence of the sliding motion in finite time, which can hold the character of fast transient response and improve the tracking accuracy. It is proved that FTSMC can guarantee the convergence of tracking-error in both approaching and sliding mode surface. Finally, simulation results demonstrate the effectiveness of the proposed control scheme.

Tensor product model transformation based adaptive integral-sliding mode controller: equivalent control method.

This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

Theoretical approach to modelling and analysis of the bioprocess with product inhibition and impulse effect.

This work presents the first mathematical model of a bioprocess with product inhibition and impulse effect. To begin with, an exemplary mathematical bioprocess model with product inhibition and impulse effect is formulated. Then, according to the model, the analysis of bioprocess stability is presented. The article expresses the product oscillation period, which provides the precise feeding time frame for the regulator bioprocess to achieve an equivalent stable output as that of a bioprocess with impulse effect in the same production environment. Moreover, in this work, the optimization of the production process with respect to the tunable parameters is investigated, and analytical expressions of their optimal values are provided. Numerical simulations using biological data are presented to illustrate the main results.