Constraint-Handling Techniques for the Concurrent Design of a Five-Bar Parallel Robot

Evolutionary Algorithms have been widely used to solve difficult constrained optimization problems. However, Evolutionary algorithms are intrinsically unconstrained optimization techniques. Constraint handling is mostly incorporated additionally and its choice has great bearing on the quality of the solution. Stochastic Ranking was introduced as an improvement over Feasibility Rules for handling constraints in Evolutionary Optimization. It is widely believed that stochastic ranking is currently the best-known technique for handling constraints. However, a fair comparative study has never been attempted in the literature, where by the performance of both the constraint handling technique is compared on the same Evolutionary Algorithm. This paper fairly compares the performance of both the constraint handling techniques on the same Evolutionary Algorithm over a set of parameters like feasibility rate, successful run, success rate and success performance in addition to objective function value and number of function evaluations. The results put a question mark over the belief that Feasibility Rules are worse than Stochastic Ranking.

Currently, rehabilitation systems with closed kinematic chain mechanisms are low-cost alternatives for treatment and health care. In designing these systems, the dimensional synthesis is commonly stated as a constrained optimization problem to achieve repetitive rehabilitation movements, and metaheuristic algorithms for constrained problems are promising methods for searching solutions in the complex search space. The Constraint Handling Techniques (CHTs) in metaheuristic algorithms have different capacities to explore and exploit the search space. However, the study of the relationship in the CHT performance of the mechanism dimensional synthesis for rehabilitation systems has not been addressed, resulting in an important gap in the literature of such problems. In this paper, we present a comparative empirical study to investigate the influence of four CHTs (penalty function, feasibility rules, stochastic-ranking, and ϵ-constraint) on the performance of ten representative algorithms that have been reported in the literature for solving mechanism synthesis for rehabilitation (four-bar linkage, eight-bar linkage, and cam-linkage mechanisms). The study involves analysis of the overall performance, six performance metrics, and evaluation of the obtained mechanism. This identified that feasibility rules usually led to efficient optimization for most analyzed algorithms and presented more consistency of the obtained results in these kinds of problems.

An empirical comparison is conducted to analyze three different elements involved in population diversity management in constrained numerical optimization problems: (1) optimization algorithms, (2) constraint-handling techniques and (3) diversity promotion techniques. Combinations of basic algorithm versions, differential evolution, and real-coded genetic algorithm, applying feasibility rules, $\epsilon$ -Constrained method and stochastic ranking as constraint-handling techniques, and also implementing a diversity promotion technique, were generated. Each combination (48 in total) was tested by solving 36 well-known benchmark problems. The final results highlight the combination of differential evolution, $\epsilon$ -Constrained method and a couple of non-disruptive diversity promotion techniques, as the most promising combinations.

How to balance diversity and convergence as well as constraint violation and objective function in Constrained Optimization Problems (COPs) is an important and key issue when designing a new Constrained Optimization Evolutionary Algorithms (COEAs). C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> oDE set a good example on this point, and obtains promising results. In C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> oDE, the two Constraint Handling Techniques (CHTs) are adopted fixed in two phases. To verify whether there are some other more efficient combinations, Stochastic Ranking (SR) is adopted to balance the combination. Experimental results show a good performance, which also give some inspiration for other research.

This chapter presents an empirical comparison of six deterministic parameter control schemes based on a sinusoidal behavior that are incorporated into a differential evolution algorithm called “Differential Evolution with Combined Variants” (DECV) to solve constrained numerical optimization problems. Besides, the feasibility rules and the e-constrained method are adopted as constraint-handling techniques.

Main problems occurring in Product-Service Systems (PSSs), are due to an inadequate requirements analysis and lack of a strong PSS conceptual design. Problems vary from exceeding budgets, to missing functionalities, unsuccessful market launch, or even project abortion. Furthermore, the special characteristics of a PSS have to be considered already at an early stage of the development process. Requirements Engineering (RE) and design methodology as well as supporting Information and Communication Technologies (ICT) need to establish a common perception of the targeted PSS. At the same time, the inner complexity of PSS leaves requirements analysis, design activities and development tasks fragmented among many disciplines and sometimes conflicting, unstable, unknowable or not fully defined. In this context, a concurrent, transdisciplinary and collaborative design of PSS is required to create feasible and successful solutions. The objective of this chapter is to present a structured approach to face the specific challenges of PSS development in detail, to elaborate a general framework that features a systematic approach for PSS development, and to consider the effects of changes in specific product and service design on a systematic PSS development process.

In this paper we present a boundary search based ACO algorithm for solving nonlinear constrained optimization problems. The aim of this work is twofold. Firstly, we present a modified search engine which implements a boundary search approach based on a recently proposed ACO metaheuristic for continues problems. Secondly, we propose the incorporation of the stochastic ranking technique to deal with feasible and infeasible solutions during the search which focuses on the boundary region. In our experimental study we compare the overall performance of the proposed ACO algorithm by including two different complementary constraint-handling techniques: a penalty function and stochastic ranking. In addition, we include in our comparison of results the stochastic ranking algorithm, which was originally implemented using an evolution strategy as its search engine.

Although control algorithms have been conceived for industrial chemical systems, their acceptance by industry has been slow due to a lack of direct experimental evidence of their effectiveness and to volumes of conflicting, or at least incompatible, recommendations on control structure design. This thesis provides the basis for a concerted theoretical and experimental program in multivariable process control structure design for packed bed chemical reactors by presenting an in-depth control analysis of a practical, multivariable, distributed parameter system-the heat conduction problem defined by the simple diffusion equation-using both frequency-domain and time-domain analyses and the formulation, numerical solution, and analysis of a detailed model for packed bed reactors, along with reduction to a low-order state-space representation suitable for on-line process control. The study of the heat conduction system allowed for consideration of various control design techniques and the relation between measurement structure and control system design. This study shows that the choice of measurements and their locations significantly affects the optimal control design and the usefulness of the different design techniques and the importance of an accurate process model and the necessity of model reduction to a low-order state-space representation for control structure design and implementation. The second portion of this study provides a detailed mathematical modeling analysis of packed bed catalytic reactors that significantly extends previous studies in the detail of the model and in the consideration of all aspects of the model development and reduction to a state-space control representation. The general view that modeling simplifications are desired since they lead to a reduction in numerical solution effort is contested, and it is shown that many simplifications are no longer necessary with today's advanced computational capabilities. A unified approach to dynamic reactor modeling is developed and its importance in the accurate description of dynamic and steady state reactor behavior, in the investigation of reactor start-up or the effects of process disturbances, and in the development of an accurate reduced state-space model for the design of control structures to stabilize the reactor under various disturbances or to provide optimal system recovery from input changes is shown.

Design changes are frequently encountered in the product development process. The complexity of the design changes is multiplied when the product design involves multiple engineering disciplines. Very often, a simple change in one part may propagate to its neighboring parts, therefore, affects the entire product assembly. Both parts and assembly must be regenerated for a physically valid product model, at the same time, the regenerated product model must meet designer’s expectations. When a product is being developed in a Concurrent Design and Manufacturing (CDM) environment, the design changes are usually implemented first by altering geometry of the product represented in computer-aided design (CAD) solid models. If the product solid model is not parameterized properly, the changes in geometry often lead to invalid parts or assembly. At the part level, the changes may yield a solid model with invalid geometric features if it is not properly parameterized. In this case, the entire product assembly is in vain. Even when individual parts of the product are regenerated correctly, parts may still penetrate to their neighboring parts or leave excessive gaps among them, if the solid model is not properly parameterized at the assembly level. In this paper, solid modeling and assembly techniques implemented in two major CAD tools, Pro/ENGINEER and SolidWorks, will be discussed. A set of guidelines will be proposed for the designers to parameterize the solid models in order to capture the design intents more effectively in the product virtual mockup. These guidelines at both part and assembly levels will support designers to successfully conduct product design in the CDM environment. A number of examples, including a slider-crank mechanism and its crankshaft, a single-piston airplane engine and its components, as well as a number of simpler parts are presented to illustrate and demonstrate the parameterization method and guidelines proposed for both Pro/ENGINEER and SolidWorks.

An integrated graphical user interface (GUI) for concurrent engineering design of mechanical parts

The conventional product development process employs a design-build-break philosophy. The sequentially executed product development process often results in a prolonged lead-time and an elevated product cost. The proposed concurrent design and manu facturing (CDM) paradigm employs physics-based computational methods together with computer graphics techniques for product de sign. This proposed approach employs Virtual Prototyping (VP) technology to support a cross-functional team in analyzing product per formance, reliability, and manufacturing cost early in the product development stage; and in conducting quantitative trade-off for design decision making. Physical prototypes of the product design are then produced using Rapid Prototyping (RP) technique primarily for de sign verification purposes. The proposed CDM approach holds potential for shortening the overall product development cycle, improving product quality, and reducing product cost. A software tool environment that supports CDM for mechanical systems is being built at the Concurrent Design and Manufacturing Research Laboratory (http://cdm.ou.edu) at the University of Oklahoma. A snapshot of the envi ronment is illustrated using a two-stroke engine example. This paper presents three unique concepts and methods for product develop ment : (1) bringing product performance, quality, and manufacturing cost together in early design stage for design considerations, (2) supporting design decision-making through a quantitative approach, and (3) incorporating rapid prototyping for design verification through physical prototypes.

In this paper maximum torque per ampere and loss minimization control methods for an interior permanent magnet synchronous generator are compared. Permanent magnet synchronous generators have wide application in wind energy conversion systems due to high efficiency, high power density, high power factor and wide speed operating range. Maximum torque per ampere control method finds optimal d-and q-axis stator currents that produce desired electromagnetic torque while minimizing stator current magnitude. Loss minimization control method takes into account both copper and iron losses and finds optimal d- and q-axis stator currents that produce desired electromagnetic torque while minimizing total power loss. Characteristic curves for both control methods considering magnetic saturation are presented. Feed-forward torque control model developed in MATLAB/Simulink was used to verify described control methods.

This manuscript presents an innovative control strategy for the Hybrid Excitation Permanent Magnet Synchronous Motor (HEPMSM) designed for electric vehicle (EV) applications. The strategy combines Maximum Torque Point Tracking (MTPT) and Maximum Torque Per Ampere (MTPA) techniques to track the ideal torque-speed profile, ensuring maximum torque at low speeds for starting and climbing, and high power at higher speeds for cruising. A novel unidirectional excitation current method is proposed to replace traditional bidirectional field current control, eliminating the risk of permanent magnet demagnetization, reducing copper losses, and increasing efficiency. This approach extends the constant power (CP) region by a 4.2:1 ratio. The manuscript also introduces a detailed mathematical model, considering both iron core losses and their impact on the EV profile. Additionally, the Multi-Objective Ant Lion Optimizer (MOALO) algorithm is used in two stages: first to optimize the hybridization ratio (HR) and base speed (Nb), and second to analyze the effect of varying the hybridization ratio while maintaining constrained output power. The proposed strategy is validated through MATLAB simulations, demonstrating its effectiveness in achieving high acceleration, efficiency, and reliability for EV applications.

In response to the need for cost-effective systems than can be quickly adapted to changes in product design and manufacturing processes, the next generation of machine tools should be reconfigurable and intelligent. Reconfigurability allows for the reduction of machine design lead time, machine set-up and ramp-up time. The principal characteristics of the Reconfigurable and Intelligent Machines are modularity, convertibility, flexibility and cost-effectiveness. This paper applies a concurrent design reference model to Reconfigurable Machine Tool development. A methodology for this purpose is introduced, and the bottlenecks in the process are identified, namely, the procedure to design modules. In response, a technique for the development of modules that are consistent with the product portfolio of the machine tool builder is outlined.KeywordsModularityReconfigurabilityConcurrent DesignMachine Tool

Electronic components and LEDs used in lighting products have started to work in more and more limited volumes due to aesthetic concerns and design. This has led to the demand for increasingly higher luminous intensity from LEDs. This causes the operating temperature of the LEDs to increase. Therefore, thermal management has become important for LEDs operating at high power. Natural convection method can be used frequently by using heat fins for cooling LEDs. In such cases, forced convection is an alternative solution. In this study, the comparison of natural convection and forced design in a sample fog light was made numerically. In natural convection, the design with fins to benefit from the outside air in the fog lights and the natural convection analysis where there is no design change, the analysis results were obtained by creating the fan definition in the forced design and the air velocity of 10 m/s. In addition, the heat transfer coefficient and temperature results at different fan speeds were obtained and verified with the literature. In the study, our analyzes were carried out by verifying with tests on a different geometry. In the analysis, independence from the number of elements was studied. Numerical analyzes were performed with ANSYS 2022 R2 software. Results were obtained at different fan speeds in forced discharge. While the results obtained in forced transport are confirmed by the literature. It has been determined that the forced convection performance is achieved in LED cooling with the original design and fin, and even better results are obtained with the fin effect. It has been determined in the study that while the LED Tj temperature is 170 °C in natural convection, it is 149 °C in forced convection, but with the design change and the addition of fins, the Tj value can be reduced to 133 °C in natural convection