Haitham Hindi

Market-based control mechanisms for electric power demand response

We propose a settlement mechanism for optimally scheduling real time electricity consumption which is suitable for an automated demand response control system. Our proposed settlement mechanism, supply function bidding, is interpreted as a Newton algorithm for optimization problems with decomposable structure, and it is shown to satisfy the second fundamental theorem of welfare economics for the case of affine supply function bids. We simulate the behavior of our proposed control mechanism for the case of demand response via home temperature control, and we demonstrate how a suboptimal control policy can have adverse impacts both in terms of system performance and also in terms of economic incentives.

A tutorial on convex optimization II: duality and interior point methods

In recent years, convex optimization has become a computational tool of central importance in engineering, thanks to its ability to solve very large, practical engineering problems reliably and efficiently. The goal of this tutorial is to continue the overview of modern convex optimization from where our ACC2004 Tutorial on Convex Optimization left off, to cover important topics that were omitted there due to lack of space and time, and highlight the intimate connections between them. The topics of duality and interior point algorithms will be our focus, along with simple examples. The material in this tutorial is excerpted from the recent book on convex optimization, by Boyd and Vandenberghe, who have made available a large amount of free course material and freely available software. These can be downloaded and used immediately by the reader both for self-study and to solve real problems

Coordinating regulation and demand response in electric power grids using multirate model predictive control

We propose a framework for reducing demand-supply imbalances in the grid, by jointly controlling both the supply-side electric power regulation together with the demand-side energy consumption by residential and commercial consumers demand response. We focus on performance improvements that arise from the complementary dynamics: regulation allows for frequent control updates but suffers from slower dynamics; demand response has faster dynamics but does not allow as frequent control updates. We propose a multirate model predictive control (MPC) approach for coordinating the two services, and we refer to this coordinator as an aggregator. Multirate MPC captures the varying dynamics and update rates, and nonlinearities due to saturation and ramp rate limits, and a total variation constraint limits the switching of the demand response signal. Our approach can operate with both direct reference or indirect market price based imbalance signal. Numerical examples are presented to show the efficacy of this joint control approach.

Synchronized control in a large-scale networked distributed printing system

As engineered systems that have traditionally been controlled centrally become more modular, distributed, and autonomous, techniques are needed to maintain control coordination among independent elements, often across a network with delays and bandwidth limitations. In particular, manufacturing systems may require tight coordination, or synchronization, among components acting on the same physical object. This paper addresses the problem of controller synchronization in such a system. We present an implementation of exact controller synchronization for independent controllers in a highly modular printing domain. Our approach, which allows networked controllers to join and leave a task dynamically, has produced excellent results on a high-speed printer prototype.

Optimal routing and scheduling in flexible manufacturing systems using integer programming

Here we consider the problem of maximum throughput routing and scheduling for flexible manufacturing systems/cells (FMS/FMC) and processing networks. Such a system consists of a set of machines which process materials and a transport network for moving materials among the machines. The goal in this problem is to find a policy for introducing jobs into the network and routing jobs through the network that maximizes the average number of jobs entering the system per unit time. We present an 0-1 linear program formulation of the maximum throughput routing and scheduling problem. This formulation is based on an extension of the linear programming formulation of the multistage network flow problem. For small problem instances, existing 0-1 solvers can be used to find an optimal schedule. For larger problem instances, we discuss the use of linear programming relaxations to find performance guarantees and rounding techniques for extracting feasible 0-1 solutions from the linear program solution. Finally, we demonstrate the general techniques described in the paper on a large-scale example. For this example, solving the linear programming relaxation and extracting a feasible schedule produces an optimal solution.

Coordinated control for highly reconfigurable systems

The remarkable drop in the cost of embedded computing, sensing, and actuation is creating an explosion in applications for embedded software. As manufacturers make use of these technologies, they attempt to reduce complexity and contain cost by modularizing their systems and building reconfigurable products from simpler but smarter components. Of particular interest have recently been highly reconfigurable systems, i.e., systems that can be customized, repaired, and upgraded at a fine level of granularity throughout their lifetime. High reconfigurability is putting new demands on the software that is dynamically calibrating, controlling, and coordinating the operations of the systems modules. There is much promise in existing software approaches, in particular in model-based approaches; however, current techniques face a number of new challenges before they can be embedded in the kind of real-time, distributed, and dynamic environment found in highly reconfigurable systems. Here, we discuss challenges, solutions, and lessons learned in the context of a long-term project at PARC to bring such techniques to a highly reconfigurable paper path system.

Coordinating Regulation and Demand Response in Electric Power Grids: Direct and Price-Based Tracking Using Multirate Economic Model Predictive Control

∗Based on “Coordinating regulation and demand response in electric power grids using multirate model predictive control,” by H. Hindi, D. Greene, C. Laventall, which appeared in the IEEE Innovative Smart Grid Technologies Conference ISGT 2011, ©2011 IEEE.

Efficient waypoint tracking hybrid controllers for double integrators using classical time optimal control

This paper is a response to requests from several respected colleagues in academia for a careful writeup of the classical time-optimal control based hybrid controllers that we have been using for material transport control in our modular reconfigurable manufacturing systems application. Specifically, we show how classical closed form time optimal control, which exploits the special structure of double integrator systems (ie ones with point-mass Newton¿s Law dynamics) can be used to design hybrid controllers for waypoint tracking. While double integrator dynamics are very simple, they are extremely prevalent in many domains, beyond manufacturing systems, eg, transportation, disk drives, robotics, and aerospace. We present two methods, one which will track general way point specs, and another which will track waypoints that lie on convex or concave trajectories. Both approaches are based on appropriate setting (switching) of the state of a reference generator with the same point mass dynamics in a two-degree-of-freedom controller topology. The techniques we present admit very compact implementations, suitable for use in low cost micro controllers and DSP chips used in modular reconfigurable embedded systems applications. Since these controllers were to be integrated with a discrete planner, as part of the control software of a large complex new research platform, every effort was made to keep the controllers as simple as possible. Our controllers can be viewed as examples of basic hybrid controllers that are being used successfully in practice, and can be used as benchmarks by controls researchers for more sophisticated hybrid control design methods.

Decompose Document Image Using Integer Linear Programming

Document decomposition is a basic but crucial step for many document related applications. This paper proposes a novel approach to decompose document images into zones. It first generates overlapping zone hypotheses based on generic visual features. Then, each candidate zone is evaluated quantitatively by a learned generative zone model. We formulate the zone inference problem into a constrained optimization problem, so as to select an optimal set of non-overlapping zones that cover a given document image. The experimental results demonstrate that the proposed method is very robust to document structure variation and noise.

Network Flow Modeling for Flexible Manufacturing Systems with Re-entrant Lines

A relaxed version of the process planning problem for flexible manufacturing systems/cells (FMS/FMC) and processing networks, such as flexible flow shops and general job shops, is formulated using a simple extension of multicommodity network flow problems. Our multistage multicommodity network formulation allows for simultaneous routing and resource allocation and also captures the case of re-entrant lines (recirculation). It can be used to perform rapid, albeit crude, explorations of the combinatorial space of possible configurations and failure scenarios. The technique can also provide bounds on the limits of system performance (eg: throughput, link usage, bottlenecks, etc). This can be used to guide the design of robust FMS architectures with high degree of redundancy in machines and routes, as demonstrated in numerical examples. Being a relaxation to the full discrete problem, our method could potentially be used as an admissible heuristic for pruning Al-based planning methods. We demonstrate our approach on a realistic industrial problem