Observer-based Adaptive Optimal Control for Unknown Singularly Perturbed Nonlinear Systems With Input Constraints

This paper introduces an observer-based adaptive optimal control method for unknown singularly perturbed nonlinear systems with input constraints. First, a multi-Time scales dynamic neural network MTSDNN observer with a novel updating law derived from a properly designed Lyapunov function is proposed to estimate the system states. Then, an adaptive learning rule driven by the critic NN weight error is presented for the critic NN, which is used to approximate the optimal cost function. Finally, the optimal control action is calculated by online solving the Hamilton-Jacobi-Bellman HJB equation associated with the MTSDNN observer and critic NN. The stability of the overall closed-loop system consisting of the MTSDNN observer, the critic NN and the optimal control action is proved. The proposed observer-based optimal control approach has an essential advantage that the system dynamics are not needed for implementation, and only the measured input U+002F output data is needed. Moreover, the proposed optimal control design takes the input constraints into consideration and thus can overcome the restriction of actuator saturation. Simulation results are presented to confirm the validity of the investigated approach. © 2014 Chinese Association of Automation.

Designing and Optimization of Fuzzy Sliding Mode Controller for Nonlinear Systems

For enhancing the control effectiveness,we firstly design a fuzzy logic based sliding mode controller(FSMC)for nonlinear crane systems.On basis of overhead crane dynamic characteristic,the sliding mode function with regard to trolley position and payload angle.Additionally,in order to eliminate the chattering problem of sliding mode control,the fuzzy logic theory is adopted to soften the control performance.Moreover,aiming at the FSMC parameter setting problem,a DE algorithm based optimization scheme is proposed for enhancing the control performance.Finally,by implementing the computer simulation,the DE based FSMC can effectively tackle the overhead crane sway problem and avoid unexpected accident greatly.

RESEARCH OF THE SWITCHED RELUCTANCE STARTER/GENERATOR SYSTEMS

This paper focuses on the simulation and test of the switched reluctance starter/generator systems. Through the emulational analysis of the initial starting torque, the optimal turn-on section of the power switches is discovered. The fundamental theory of the generating operation is analyzed with the linearity model, and a new method is presented based on voltage pulse width modulation for the generating mode control. Through the steady-state and optimized emulation of the output power and system efficiency, the optimizational control approach for the generating mode over a wide speed range is introduced. At last, the test of the 3KW prototype system shows that the dynamic and static performance of this system is fine.

Multi-objective modeling and optimization for scheduling of cracking furnace systems

Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.

Stability Analysis of Optimal Control Systems via Liapunov Method

The controlled objects are uncertain stable,but the optimal control systems which are constituted by the controlled objects under certain conditions are certain stable. This paper analyses stability of optimal control systems which have quadric performance index via Liapunov method.

Optimal traffic light control method for a single intersecti on basedon hybrid systems

A single intersection of two phases is selected as a model to put forward a new optimal time-planning scheme for traffic light based on the model of hybrid automata for single intersection. A method of optimization is proposed for hybrid systems, and the average queue length over all queues is used as an objective function to find an optimal switching scheme for traffic light. It is illustrated that traffic light control for single intersection is a typical hybrid system, and the optimal planning-time scheme can be obtained using the optimal hybrid systems control based on the two stages method.

Guest Editorial for Special Issue on Control and Optimization in Renewable Energy Systems

I.I NTRODUCTION W ITH the advent of low-carbon economy,there has been a growing interest in harnessing renewable energy resources particularly for electricity generation.Renewable energy resources are advocated for the economic and environ-

Systems engineering optimization of Omid-2 in the conceptual design phase

Due to the importance and role of systems engineering in space mission developments, optimization of Omid＇s systems engineering as a milestone to its current and future generations is focused. In this regard systems engineering management organization as the basis of optimization work flow in the conceptual design phase is proposed for improvement. To improve the systems engineering management, an agile enhanced organization chart is developed that defines various system duties. This is a type of concurrent engineering approach that promotes direct communication and data interchange between the team members. Due to the importance of decision making in the conceptual design phase, two design matrices are constructed that portray merits of various design options in terms of improved satellite life as well as specific choices of remote sensing capability for the Omid second generation（Omid-2）. Conceptual design optimization is explored considering several structural objectives as well as optimal solar energy absorption utilizing a multiple criteria decision making approach. The Eigenvector method is utilized to formulate the objective function via expert judgment. This approach is robust with respect to designer probable miss-judgment. The optimized version of Omid-2 turned out to be a passive Z-axis spin stabilized satellite made of hexagonal honeycomb configuration with carbon-epoxy side panels and Aluminum bottom plate.

Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability

Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.

ASSESSMENT AND OPTIMIZATION OF THE PHASE DIAGRAMS AND THERMODYNAMIC DATA OF SOME BINARY SYSTEMS CONTAINING PRASEODYMIUM CHLORIDES

In this paper a critical assessment and optimization of the phase diagrams and thermodynamic properties of the PrCl_3-MCl(M=Li,Na)and PrCl_3-MCl_2(M=Mg,Ca,Sr,Ba) binary systems have been per- formed.The assessed and optimized binary phase diagrams and thermodynamic data with self consistency are a better basis for constructing multicomponent phase diagrams.

STUDY OF OPTIMAL SLIDING-MODE GUIDANCE LAW

An optimal guidance law based on missile-target line-of-sight (LOS) angular rate is presented for intercepting a nonmaneuvering target. It is then integrated with sliding-mode control theory by using reaching-law of sliding-mode, in order to derive an optimal sliding-mode guidance law for intercepting a maneuvering target. The new guidance method's robustness against target maneuvers and good miss distance performance are proved by the second method of Lyapunov and simulation results. The presented guidance law is simple to implement in practical applications.

Determining the Optimal Solution Set for Linear Fractional Programming

The structure of the optimal solution set is derived for linear fractional programming with the representation theorem of polyhedral sets. Based on an adaptation of the convex simplex method credited to Gilmore and Gomory, we give the uniqueness condition of optimal solution and the computational procedures to find all optimal solutions if the uniqueness condition is not satisfied. Finally, an illustrative example is also given.

Neuro-Optimal Guidance Control for Lunar Soft Landing

Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar parking orbit. Once the landing area has been selected and it is time to deorbit for landing, a ΔV burn of 19.4 m/s is performed to establish a 100×15 km elliptical orbit. At perilune, the landing jets are ignited, and a propulsive landing is performed. A guidance and control scheme for lunar soft landing is proposed in the paper, which combines optimal theory with nonlinear neuro-control. Basically, an optimal nonlinear control law based on artificial neural network is presented, on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index. Therefore some optimal control laws can be carried out in the soft landing system due to the nonlinear mapping function of the neural network. The feasibility and validity of the control laws are verified in a simulation experiment.

Multi-objective Optimal Design of Vibration Absorber with Simple Cell Mapping Algorithm

In this paper, we investigate a multi-objective optimal design of a tuned vibration absorber for a two degrees-of-freedom linear system, in which we take white Gaussian noise as the excitation. We use the simple cell mapping method to obtain solutions to the multi-objective optimization problem. We optimize tuned vibration absorbers in two different configurations. As our objective, we take various features of the response of the power spectrum density function. Our results show that the primary mass vibration with the optimally designed absorber has a lower peak power spectrum value. In addition, the two natural frequencies of the optimized system are further apart than in the non-optimized system, which implies that the absorber has a wider effective region in the frequency domain. © 2017, Tianjin University and Springer-Verlag GmbH Germany.

Multi-objective Optimization of Non-uniform Beam for Minimum Weight and Sound Radiation

A multi-objective optimization of non-uniform beams is presented for minimum radiated sound power and weight. The transfer matrix method is used to compute the structural and acoustic responses of a non-uniform beam accurately and efficiently. The multi-objective particle swarm optimization technique is applied to search the Pareto optimal solutions that represent various compromises between weight and sound radiation. Several constraints are imposed, which substantially reduce the volume fraction of feasible solutions in the design space. Two non-uniform beams with different boundary conditions are studied to demonstrate the multi-objective optimal designs of the structure. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg.

Optimization of projectile state and trajectory of reentry body considering attainment of carrying aircraft

As an improvement of traditional maximum range trajectory optimization, both the projectile state and control sequence of reentry body are optimized to achieve the maximum range. To ensure the optimal projectile state is in the reachable domain of the carrying aircraft, the climb of the carrying aircraft and the flight of reentry body are optimized as a whole based on the hp-adaptive pseudospectral method. Meanwhile, the path constraints, control constraints and initial/terminal states constraints are considered in the optimization as well. In face of the fact that the range of the optimal control solution resulted from the pseudospectral method may be unsmooth, virtual control variables (second derivatives of the angle of attack and bank angle) are proposed in the optimization, while the angle of attack and bank angle are treated as the virtual state variables to guarantee the smoothness of the optimal control solution. The validity of the virtual control variables in smoothing the optimal control solution is verified by simulation, and the optimality of the resulting projectile state and control sequence for reaching the maximum range is confirmed using the indirect approach. © 1990-2011 Beijing Institute of Aerospace Information.

On the Solutions of the Matrix Equations in Optimal Stochastic Control

In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.

Steady-State Configuration and Tension Calculations of Marine Cables Under Complex Currents via Separated Particle Swarm Optimization?

Under complex currents, the motion governing equations of marine cables are complex and nonlinear, and the calculations of cable configuration and tension become difficult compared with those under the uniform or simple currents. To obtain the numerical results, the usual Newton-Raphson iteration is often adopted, but its stability depends on the initial guessed solution to the governing equations. To improve the stability of numerical calculation, this paper proposed separated the particle swarm optimization, in which the variables are separated into several groups, and the dimension of search space is reduced to facilitate the particle swarm optimization. Via the separated particle swarm optimization, these governing nonlinear equations can be solved successfully with any initial solution, and the process of numerical calculation is very stable. For the calculations of cable configuration and tension of marine cables under complex currents, the proposed separated swarm particle optimization is more effective than the other particle swarm optimizations.

Optimal dynamical systems of Navier-Stokes equations based on generalized helical-wave bases and the fundamental elements of turbulence

In this paper, we present the theory of constructing optimal generalized helical-wave coupling dynamical systems. Applying the helical-wave decomposition method to Navier-Stokes equations, we derive a pair of coupling dynamical systems based on optimal generalized helical-wave bases. Then with the method of multi-scale global optimization based on coarse graining analysis, a set of global optimal generalized helical-wave bases is obtained. Optimal generalized helical-wave bases retain the good properties of classical helical-wave bases. Moreover, they are optimal for the dynamical systems of Navier-Stokes equations, and suitable for complex physical and geometric boundary conditions. Then we find that the optimal generalized helical-wave vortexes fitted by a finite number of optimal generalized helical-wave bases can be used as the fundamental elements of turbulence, and have important significance for studying physical properties of complex flows and turbulent vortex structures in a deeper level.

PLANNED LEAD TIME OPTIMIZATION IN MATERIAL REQUIREMENT PLANNING ENVIRONMENT FOR MULTILEVEL PRODUCTION SYSTEMS

This paper deals with the problem of planned lead time calculation in a Material Requirement Planning （MRP） environment under stochastic lead times. The objective is to minimize the sum of holding and backlogging costs. The proposed approach is based on discrete time inventory control where the decision variables are integer. Two types of systems are considered： multi-level serial-production and assembly systems. For the serial production systems （one type of component at each level）, a mathematical model is suggested. Then, it is proven that this model is equivalent to the well known discrete Newsboy Model. This directly provides the optimal values for the planned lead times. For multilevel assembly systems, a dedicated model is proposed and some properties of the decision variables and objective function are proven. These properties are used to calculate lower and upper limits on the decision variables and lower and upper bounds on the objective function. The obtained limits and bounds open the possibility to develop an efficient optimization algorithm using, for example, a Branch and Bound approach. The paper presents the proposed models in detail with corresponding proofs and se＇~eral numerical examples. Some advantages of the suggested models and perspectives of this research are discussed.