![]() Of course, blockchain is more complicated than a Google Doc, but the analogy is apt because it illustrates critical ideas of the technology: A significant gap to note however is that unlike Google Docs, original content and data on the blockchain cannot be modified once written, adding to its level of security. No one is locked out awaiting changes from another party, while all modifications to the document are being recorded in real-time, making changes completely transparent. This creates a decentralized distribution chain that gives everyone access to the base document at the same time. When you create a Google Doc and share it with a group of people, the document is simply distributed instead of copied or transferred. | Image: Shutterstock What Is Blockchain Technology?īlockchain, sometimes referred to as distributed ledger technology (DLT), makes the history of any digital asset unalterable and transparent through the use of a decentralized network and cryptographic hashing.Ī simple analogy for how blockchain technology operates can be compared to how a Google Docs document works. 1291–1303.Blockchain is most simply defined as a decentralized, distributed ledger technology that records the provenance of a digital asset. Stursberg, Applied hybrid system optimization: An empirical investigation of complexity, Control Eng. IFAC Symposium in Advances in Automotive Control, Salerno, Italy, 2004, pp. Krebs, Predictive powertrain control for heavy duty trucks, in Proc. Steinbach, Tree-sparse convex programs, Math. Steinbach, Structured interior point SQP methods in optimal control, Zeitschrift für Angewandte Mathematik und Mechanik, 76 (1996), pp. Steinbach, Fast recursive SQP methods for large-scale optimal control problems, PhD thesis, Universität Heidelberg, 1995. Bock, Direct methods with maximal lower bound for mixed-integer optimal control problems, Math. ![]() Bock, Fast solution of periodic optimal control problems in automobile test-driving with gear shifts, in Proc. Sager, Reformulations and algorithms for the optimization of switching decisions in nonlinear optimal control, Journal of Process Control, 19 (2009), pp. Sager, Numerical methods for mixed–integer optimal control problems, Der andere Verlag, Tönning, Lübeck, Marburg, 2005. Wright, Numerical Optimization, Springer, 2nd ed., 2006. Part I: Theoretical aspects, Computers and Chemical Engineering, 27 (2003), pp. Schlöder, An efficient multiple shooting based reduced SQP strategy for large-scale dynamic process optimization. Schlöder, Time-optimal control of automobile test drives with gear shifts, Opt. Nielsen, Look-ahead control for heavy trucks to minimize trip time and fuel consumption, Control Eng. Saunders, User’s Guide For QPOPT 1.0: A Fortran Package For Quadratic Programming, 1995.Į. Gerdts, A variable time transformation method for mixed-integer optimal control problems, Optimal Control Applications and Methods, 27 (2006), pp. Fletcher, Resolving degeneracy in quadratic programming, Numerical Analysis Report NA/135, University of Dundee, Dundee, Scotland, 1991. IFAC Workshop on Nonlinear Model Predictive Control for Fast Systems, Grenoble, 2006. Diehl, An online active set strategy for fast parametric quadratic programming in MPC applications, in Proc. 9th IFAC World Congress Budapest, 1984, pp. Plitt, A Multiple Shooting algorithm for direct solution of optimal control problems, in Proc. Biegler, Solution of dynamic optimization problems by successive quadratic programming and orthogonal collocation, Comp. on High Performance Scientific Computing, Hanoi, Vietnam, 2008, pp. Bock, Sensitivity Generation in an Adaptive BDF-Method, in Modeling, Simulation and Optimization of Complex Processes: Proc.
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