A new solution approach to polynomial LPV system analysis and synthesis

Based on sum-of-squares (SOS) decomposition, we propose a new solution approach for polynomial LPV system analysis and control synthesis problems. Instead of solving matrix variables over a positive definite cone, the SOS approach tries to find a suitable decomposition to verify the positiveness of given polynomials. The complexity of the SOS-based numerical method is polynomial of the problem size. This approach also leads to more accurate solutions to LPV systems than most existing relaxation methods. Several examples have been used to demonstrate benefits of the SOS-based solution approach

Filtering for nonlinear genetic regulatory networks with stochastic disturbances

In this paper, the filtering problem is investigated for nonlinear genetic regulatory networks with stochastic disturbances and time delays, where the nonlinear function describing the feedback regulation is assumed to satisfy the sector condition, the stochastic perturbation is in the form of a scalar Brownian motion, and the time delays exist in both the translation process and the feedback regulation process. The purpose of the addressed filtering problem is to estimate the true concentrations of the mRNA and protein. Specifically, we are interested in designing a linear filter such that, in the presence of time delays, stochastic disturbances as well as sector nonlinearities, the filtering dynamics of state estimation for the stochastic genetic regulatory network is exponentially mean square stable with a prescribed decay rate lower bound beta. By using the linear matrix inequality (LMI) technique, sufficient conditions are first derived for ensuring the desired filtering performance for the gene regulatory model, and the filter gain is then characterized in terms of the solution to an LMI, which can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures

Stationary Cycling Induced by Switched Functional Electrical Stimulation Control

Functional electrical stimulation (FES) is used to activate the dysfunctional lower limb muscles of individuals with neuromuscular disorders to produce cycling as a means of exercise and rehabilitation. However, FES-cycling is still metabolically inefficient and yields low power output at the cycle crank compared to able-bodied cycling. Previous literature suggests that these problems are symptomatic of poor muscle control and non-physiological muscle fiber recruitment. The latter is a known problem with FES in general, and the former motivates investigation of better control methods for FES-cycling.In this paper, a stimulation pattern for quadriceps femoris-only FES-cycling is derived based on the effectiveness of knee joint torque in producing forward pedaling. In addition, a switched sliding-mode controller is designed for the uncertain, nonlinear cycle-rider system with autonomous state-dependent switching. The switched controller yields ultimately bounded tracking of a desired trajectory in the presence of an unknown, time-varying, bounded disturbance, provided a reverse dwell-time condition is satisfied by appropriate choice of the control gains and a sufficient desired cadence. Stability is derived through Lyapunov methods for switched systems, and experimental results demonstrate the performance of the switched control system under typical cycling conditions.Comment: 8 pages, 3 figures, submitted to ACC 201

On Incremental Stability of Interconnected Switched Systems

In this letter, the incremental stability of interconnected systems is discussed. In particular, we consider an interconnection of switched nonlinear systems. The incremental stability of the switched interconnected system is a stronger property as compared to conventional stability. Guaranteeing such a notion of stability for an overall interconnected nonlinear system is challenging, even if individual subsystems are incrementally stable. Here, preserving incremental stability for the interconnection is ensured with a set of sufficient conditions. Contraction theory is used as a tool to achieve incremental convergence. For the feedback interconnection, the small gain characterisation is presented for the overall system's incremental stability. The results are derived for a special case of feedback, i.e., cascade interconnection. Matrix-measure-based conditions are presented, which are computationally tractable. Two numerical examples are demonstrated and supported with simulation results to verify the theoretical claims

Robust Adaptive Control of Switched Systems

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