Babak Tavassoli

Rahim Delavar, Babak Tavassoli, Mohammad Taghi Hamidi Beheshti

In this paper, we consider a nonlinear networked control system (NCS) in which controllers, sensors and actuators are connected via several communication links. In each link, networking effects such as the transmission delay, packet loss, sampling jitter and data packet miss-ordering are captured by time-varying delays. Stability analysis is carried out based on the Lyapunov Krasovskii method to obtain a condition for stability of the nonlinear NCS in the form of linear matrix inequality (LMI). The results are applied to a two degrees of freedom robot arm NCS which shows a considerable improvement with respect to the previous works.

Babak Tavassoli

In this work, solution of the finite horizon hybrid optimal control problem as the central element of the receding horizon optimal control (model predictive control) is investigated based on the indirect approach. The response of a hybrid system within the prediction horizon is composed of both discrete-valued sequences and continuous-valued time-trajectories. Given a cost functional, the optimal continuous trajectories can be calculated given the discrete sequences by the means of the recent results on the hybrid maximum principle. It is shown that these calculations reduce to solving a system of algebraic equations in the case of affine hybrid systems. Then, a branch and bound algorithm is proposed which determines both the discrete and continuous control inputs by iterating on the discrete sequences. It is shown that the algorithm finds the correct solution in a finite number of steps if the selected cost functional satisfies certain conditions. Efficiency of the proposed method is demonstrated during a case study through comparisons with the main existing method.

Babak Tavassoli

The problem of step tracking control with a switching input and without any continuous-valued inputs is considered. The control objective is to reduce the number of switchings to a minimal value. This approach finds interesting applications when switching comprises costs and should be avoided. To solve the problem, a state dependent switching strategy should be designed and the resulting closed loop is indeed a hybrid system. Therefore, first we investigate the conditions on a hybrid system for being the desired solution. Then, we propose a method for designing the switching strategy such that the closed loop as a hybrid system solves the problem. The proposed method is applied to the induction motor control problem which results in relatively simple and efficient control algorithm. Comparison with the direct torque control for induction motors show that our method has a superior performance in reducing the number of mode switches.

Babak Tavassoli

The problem of finding a finite state symbolic model which is bisimilar to a hybrid dynamical system (HDS) and has the minimum number of states is considered. The considered class of HDS allows for discrete-valued inputs that only affect the jumps (events) of the HDS. Representation of the HDS in the form of a transition system is revisited in comparison with prior works. An algorithm is proposed for solving the problem which gives the bisimulation with the minimum number of states if it already exists and also a parameter of the algorithm is properly tuned. There is no need for stability assumptions and no time discretization is applied. The results are applied to an example

Amir Noori, Babak Tavassoli, Alireza Fereidunian

Renewable prosumers face the complex challenge of balancing self-sufficiency with seamless grid and market integration. This paper introduces a novel prosumers network framework aimed at mitigating peak loads in Iran, particularly under the uncertainties inherent in renewable energy generation and demand. A cost-oriented integrated prediction and optimization approach is proposed, empowering prosumers to make informed decisions within a distributed contextual stochastic optimization (DCSO) framework. The problem is formulated as a bi-level two-stage multi-time scale optimization to determine optimal operation and interaction strategies under various scenarios, considering flexible resources. To facilitate grid integration, a novel consensus-based contextual information sharing mechanism is proposed. This approach enables coordinated collective behaviors and leverages contextual data more effectively. The overall problem is recast as a mixed-integer linear program (MILP) by incorporating optimality conditions and linearizing complementarity constraints. Additionally, a distributed algorithm using the consensus alternating direction method of multipliers (ADMM) is presented for computational tractability and privacy preservation. Numerical results highlights that integrating prediction with optimization and implementing a contextual information-sharing network among prosumers significantly reduces peak loads as well as total costs.

Babak Tavassoli

Oscillations between swing modes of electric machines is an important limitation in achieving a high level of transient performance and reliability in power grids. Based on the new advances in measurement and transmission of wide-area information, this work proposes a distributed networked control scheme by considering the communication delays. The results are applied to reduce the inter-area swing oscillations in a power grid. In comparison with the previous works, we provide a more realistic modeling of the resulting networked control system with data sampling and delays. The exactness of the proposed modeling allows for precise evaluation and comparison between the distributed and decentralized schema. A symmetric a dual machine power system is highly oscillatory and we focus on this case to evaluate the ability of the proposed control design in dampening of the oscillations. The design can be done either based on optimization of a quadratic cost function or a disturbance attenuation level