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In this paper, we propose further development of the generalized methodology for analogue circuit optimization. This methodology is based on optimal control theory. This approach generates many different circuit optimization strategies. We lead the problem of minimizing the CPU time needed for circuit optimization to the classical problem of minimizing a functional in optimal control theory.

The process of analogue circuit optimization is defined mathematically as a controllable dynamical system. In this context, we can formulate the problem of minimizing the CPU time as the minimization problem of a transitional process of a dynamical system. To analyse the properties of such a system, we propose to use the concept of the Lyapunov function of a dynamical system. This function allows us to analyse the stability of the optimization trajectories and to predict the CPU time for circuit optimization by analysing the characteristics of the initial part of the process.

We present numerical results that show that we can compare the CPU time for different circuit optimization strategies by analysing the behaviour of a special function. We establish that, for any optimization strategy, there is a correlation between the behaviour of this function and the CPU time that corresponds to that strategy.

The analysis shows that Lyapunov function of optimization process and its time derivative can be informative sources for searching a strategy, which has minimal processor time expense. This permits to predict the best optimization strategy by analyzing only initial part of the optimization process.

This paper aims to propose a new approach on the problem of circuit optimisation by using the generalised optimisation methodology presented earlier. This approach is focused on the application of the maximum principle of Pontryagin for searching the best structure of a control vector providing the minimum central processing unit (CPU) time.

The process of circuit optimisation is defined mathematically as a controllable dynamical system with a control vector that changes the internal structure of the equations of the optimisation procedure. In this case, a well-known maximum principle of Pontryagin is the best theoretical approach for finding of the optimum structure of control vector. A practical approach for the realisation of the maximum principle is based on the analysis of the behaviour of a Hamiltonian for various strategies of optimisation and provides the possibility to find the optimum points of switching for the control vector.

It is shown that in spite of the fact that the maximum principle is not a sufficient condition for obtaining the global minimum for the non-linear problem, the decision can be obtained in the form of local minima. These local minima provide rather a low value of the CPU time. Numerical results were obtained for both a two-dimensional case and an N-dimensional case.

The possibility of the use of the maximum principle of Pontryagin to a problem of circuit optimisation is analysed systematically for the first time. The important result is the theoretical justification of formerly discovered effect of acceleration of the process of circuit optimisation.

The purpose of this paper is to propose an approach for aircraft taking off control in wind shear, which is a challenging issue for an aircraft.

Aircraft control in wind shear needs an anti-jamming controller. Symbolic control is an effective and adaptive method for complex dynamic system. In this paper, wind shear flight control laws are developed for the dynamics of a B-747 aircraft by using symbolic control. The problem of efficiently steering dynamical systems with disturbance by using symbolic control is considered, and theoretical analysis on the proposed approach is also conducted. The implementation of an altitude scheduling strategy with symbolic controller makes it possible for aircraft to escape serious wind shear.

This work improved symbolic control algorithm so that it can be applied to aircraft control problem. A series of comparative experimental results with proportional-integral-derivative controller demonstrate the feasibility and effectiveness of the proposed approach.

The symbolic control method developed in this paper can be easily applied to another aircraft control problems.

An improved symbolic control method is proposed for solving aircraft taking off problem in wind shear.

This paper aims to devise a robust controller for the non-linear aircraft model using output feedback control topology in the presence of uncertain aerodynamic parameters.

Feedback linearization-based state feedback (SFB) controller is considered along with a robust outer loop control which is designed using Lyapunov’s second method. A high-gain observer (HGO) in accordance with the separation principle is used to implement the output feedback (OFB) control scheme. The robustness of the controller and observer is assessed by introducing uncertain aerodynamics coefficients in the dynamic model. The proposed scheme is validated using MATLAB/SIMULINK.

The efficacy of the proposed scheme is authenticated with the simulation results which show that HGO-based OFB control achieves the SFB control performance for a small value of the high-gain parameter in the presence of uncertain aerodynamic parameters.

A HGO for the non-linear model of aircraft with uncertain parameters is a novel contribution which could be further used for the unmanned aerial vehicles autopilot, flight trajectory tracking and path following.

In this paper, on the basis of a previously developed approach to circuit optimization, the main element of which is the control vector that changes the form of the basic equations, the structure of the control vector is determined, which minimizes CPU time.

The circuit optimization process is defined as a controlled dynamic system with a special control vector. This vector serves as the main tool for generalizing the problem of circuit optimization and produces a huge number of different optimization strategies. The task of finding the best optimization strategy that minimizes processor time can be formulated. There is a need to find the optimal structure of the control vector that minimizes processor time. A special function, which is a combination of the Lyapunov function of the optimization process and its time derivative, was proposed to predict the optimal structure of the control vector. The found optimal positions of the switching points of the control vector give a large gain in CPU time in comparison with the traditional approach.

The optimal positions of the switching points of the components of the control vector were calculated. They minimize processor time. Numerical results are obtained for various circuits.

The Lyapunov function, which is one of the main characteristics of any dynamic system, is used to determine the optimal structure of the control vector, which minimizes the time of the circuit optimization process.

The purpose of this paper is to propose a new method of robust parameter design for dynamic multi‐response system. The objectives are to resolve the correlations among multiple responses and the uncertainty of system with incomplete information.

First, desirability function is used to measure dynamic system sensitivity and system variation, and principal component analyses on the two indices are conducted. Second, the grey relational grade (GRD) between principal component sequences of the two indices and their respective ideal sequences, gained by grey relational analysis, is converted to an integrated GRD (IGRD) index by means of TOPSIS method, and then the optimal level combination of controllable factors is identified based on the IGRD index.

It was found that the optimal factor level combination obtained by the proposed method is nearest the ideal solution and farthest from the negative ideal solution. The validity and superiority of the proposed method are confirmed through two illustrative examples.

It should be noted that the proposed method fails to consider the interaction effects between controllable factors and noise factors.

The method proposed in the paper effectively integrates several common methods to optimize a dynamic multiple responses system based on Taguchi's robust parameter design. These methods do not involve complicated mathematical theory, and are therefore easy for practitioners to use in engineering practice.

In order to analyze the level of independent controllability and its evolution of high-end equipment manufacturing industry from Jiangsu Province, this article introduces the dual-excitation control line method to construct a comprehensive evaluation model for independent controllability.

Through the collection of information of high-end equipment manufacturing industry's independent and controllable capabilities on different indicators, the three aspects of advancement, autonomy and controllability, an empirical evaluation of 10 enterprises in the high-end equipment cluster in Jiangsu Province was conducted in terms of advancement, autonomy and controllability.

It effectively reveals the area and evolution characteristics of the “reward” and “punishment” of different indicators of each representative enterprise and reflects the development status and different characteristics of each representative enterprise on the three indicators. The research results provide decision-making guidance for enterprises in the management and control of advanced manufacturing systems with independent and controllable capabilities.

Existing research focuses on the evaluation of enterprises' independent controllability only on a single angle or index. This paper maps the dynamic evaluation problem of multiple time-point data to the evaluation problem of single time-point multi-index data and investigates the fluctuation of the performance of the same enterprise under different indexes, so as to comprehensively evaluate the independent controllable level of high-end equipment manufacturing industry and analyze the reasons. Further, this paper first establishes an evaluation index system of independent controllable level of high-end equipment manufacturing industry and quantitatively measures the advanced, independent, controllable and other aspects of typical enterprises in this industry by constructing a double incentive control line evaluation model.

The purpose of this paper is to analyze the dynamical state of a discrete time engineering/physical dynamic system. The analysis is performed based on observability, controllability and stability first using difference equations of generalized motion obtained through discrete time equations of dissipative generalized motion derived from discrete Lagrange-dissipative model [{L,D}-model] for short of a discrete time observed dynamic system. As a next step, the same system has also been analyzed related to observability, controllability and stability concepts but this time using discrete dissipative canonical equations derived from a discrete Hamiltonian system together with discrete generalized velocity proportional Rayleigh dissipation function. The methods have been applied to a coupled (electromechanical) example in different formulation types.

An observability, controllability and stability analysis of a discrete time observed dynamic system using discrete equations of generalized motion obtained through discrete {L,D}-model and discrete dissipative canonical equations obtained through discrete Hamiltonian together with discrete generalized velocity proportional Rayleigh dissipation function.

The related analysis can be carried out easily depending on the values of classical elements.

Discrete equations of generalized motion and discrete dissipative canonical equations obtained by discrete Lagrangian and discrete Hamiltonian, respectively, together with velocity proportional discrete dissipative function are used to analyze a discrete time observed engineering system by means of observability, controllability and stability using state variable theory and in the method proposed, the physical quantities do not need to be converted one to another.

The purpose of this study is to provide the full-state mathematical model and devise a nonlinear controller for a balloon-supported unmanned aerial vehicle (BUAV).

Newtonian mechanics is used to establish the nonlinear mathematical model of the proposed vehicle assembly which incorporates the dynamics of both balloon and quadrotor UAV. A controllable form of the nine degrees of freedom model is derived. Backstepping control is designed for the proposed model and simulations are performed to assess the tracking performance of the proposed control.

The results show that the proposed methodology works well for smooth trajectories in presence of wind gusts. Moreover, the final mathematical model is affine and various nonlinear control techniques can be used in the future for improved system performance.

Multi-rotor unmanned aerial vehicles (MUAVs) are equipped with controllers but are constrained by smaller flight endurance and payload carrying capability. On the contrary, lighter than air (LTA) aerial vehicles have longer flight times but have poor control performance for outdoor operations. One of the solutions to achieve better flight endurance and payload carrying capability is to augment the LTA balloon to MUAV. The novelty of this research lies in full-order mathematical modeling along with transformation to controllable form for the BUAV assembly.

The purpose of this paper is to find an omnidirectional robust gust response stabilization (GRS) scheme with anti-disturbance and state-limited features.

Disturbance observer and barrier Lyapunov techniques, which can, respectively, estimate the lumped disturbances of the dynamic system in real-time and ensure the middle states within some prescribed ranges according to some flight safety indexes.

In the existing literature, almost all of the GRS controllers are either only for the longitudinal dynamics or only for the latitudinal dynamics. Few studies have considered the gust response alleviation problem with omnidirectional wind disturbance and full aircraft model.

This paper proposes a fresh scheme to deal with a more holistic GRS problem; the disturbance observer based (DOB) barrier Lyapunov backstepping longitudinal controller has been put forward; DOB nonlinear dynamic inversion to handle the multi-input-multi-output lateral dynamics; and to closely connect the two loops of the latitudinal dynamics, a manipulating variable conversion method is proposed.